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data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/126397440/TEMPORARY_FLOODWATER_STORAGE_VOLUME_ESTIMATIONS_USING_1_m_LiDAR_AND_30_m_NED_DEMS_OF_THE_RED_RIVER_OF_THE_NORTH_BASIN"><img alt="Research paper thumbnail of TEMPORARY FLOODWATER STORAGE VOLUME ESTIMATIONS USING 1-m LiDAR AND 30-m NED DEMS OF THE RED RIVER OF THE NORTH BASIN" class="work-thumbnail" src="https://attachments.academia-assets.com/120279805/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/126397440/TEMPORARY_FLOODWATER_STORAGE_VOLUME_ESTIMATIONS_USING_1_m_LiDAR_AND_30_m_NED_DEMS_OF_THE_RED_RIVER_OF_THE_NORTH_BASIN">TEMPORARY FLOODWATER STORAGE VOLUME ESTIMATIONS USING 1-m LiDAR AND 30-m NED DEMS OF THE RED RIVER OF THE NORTH BASIN</a></div><div class="wp-workCard_item 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href="https://www.academia.edu/85592081/Reading_North_Dakota_s_Contemporary_Landscapes_Stories_of_Devolution_Dereliction_Dynamism_and_Curation">Reading North Dakota’s Contemporary Landscapes: Stories of Devolution, Dereliction, Dynamism, and Curation</a></div><div class="wp-workCard_item"><span>Handbook of the Changing World Language Map</span><span>, 2019</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="85592081"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="85592081"><i class="fa fa-spinner 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paper thumbnail of Characteristics and Geography of Oil Spills in North Dakota" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/85592060/Characteristics_and_Geography_of_Oil_Spills_in_North_Dakota">Characteristics and Geography of Oil Spills in North Dakota</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="85592060"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa 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Dakota","internal_url":"https://www.academia.edu/85592060/Characteristics_and_Geography_of_Oil_Spills_in_North_Dakota","owner_id":138386,"coauthors_can_edit":true,"owner":{"id":138386,"first_name":"Bradley","middle_initials":null,"last_name":"Rundquist","page_name":"BradleyRundquist","domain_name":"und","created_at":"2010-02-26T04:13:55.837-08:00","display_name":"Bradley Rundquist","url":"https://und.academia.edu/BradleyRundquist"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="85592050"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/85592050/Spectral_characterization_of_the_invasive_shrub_saltcedar_Tamarix_spp_in_North_Dakota"><img alt="Research paper thumbnail of Spectral characterization of the invasive shrub saltcedar ( Tamarix spp. ) in North Dakota" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/85592050/Spectral_characterization_of_the_invasive_shrub_saltcedar_Tamarix_spp_in_North_Dakota">Spectral characterization of the invasive shrub saltcedar ( Tamarix spp. ) in North Dakota</a></div><div class="wp-workCard_item"><span>Geocarto International</span><span>, 2007</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">A large infestation of the invasive shrub saltcedar (Tamarix ramosissima and Tamarix chinensis) w...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">A large infestation of the invasive shrub saltcedar (Tamarix ramosissima and Tamarix chinensis) was first detected east of the Montana–North Dakota border in 2001. Saltcedar has since spread from Montana along the Yellowstone and Missouri River corridors into the Lake Sakakawea region of west-central North Dakota, and has currently halted its progress at the reservoir&#39;s Garrison Dam. A receding lake level since 2001, the result of a moderate regional drought, has allowed saltcedar to quickly invade newly exposed shoreline. The infestation in some locations is severe, and there is concern among the lake managers that, left unchecked, the shrub will move upland and displace native species, degrade shoreline aesthetics, and damage wildlife habitat. Eradication efforts are underway, yet there is much interest among land managers in North Dakota in characterizing saltcedar spectrally to assist future remote detection efforts, especially in areas that are difficult to access on foot. To this end, close-range hyperspectral data collection was conducted on three dates during the 2003 growing season. 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Lake area has nearly tripled, resulting in more than $400 million dollars in direct flood damages. Beginning in 1999 Devils Lake began to overflow into Stump Lake, a smaller closed lake sub-basin located in Nelson County. Outflow from Devils Lake has combined with local runoff to produce a 1.5-m rise in Stump Lake over the past three years. Extensive rural flooding marked by an increase in the number, size, and permanence of wetlands has also occurred within both lake basins over the same period. The authors document the flood history of Stump Lake and rural Nelson County, assess the flood damages resulting from the rise of Stump Lake and the growth of rural wetlands in Nelson County, and survey the flood mitigation efforts associated with this closed-basin flood hazard. Remote sensing image interpretation, field work, personal interview...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="44aae77f50d0451f385335ff5859d9fe" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":79418879,"asset_id":69252511,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/79418879/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="69252511"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="69252511"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 69252511; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=69252511]").text(description); $(".js-view-count[data-work-id=69252511]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 69252511; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='69252511']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="69252510"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/69252510/TEMPORARY_FLOODWATER_STORAGE_VOLUME_ESTIMATIONS_USING_1_m_LiDAR_AND_30_m_NED_DEMS_OF_THE_RED_RIVER_OF_THE_NORTH_BASIN"><img alt="Research paper thumbnail of TEMPORARY FLOODWATER STORAGE VOLUME ESTIMATIONS USING 1-m LiDAR AND 30-m NED DEMS OF THE RED RIVER OF THE NORTH BASIN" class="work-thumbnail" src="https://attachments.academia-assets.com/79418876/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/69252510/TEMPORARY_FLOODWATER_STORAGE_VOLUME_ESTIMATIONS_USING_1_m_LiDAR_AND_30_m_NED_DEMS_OF_THE_RED_RIVER_OF_THE_NORTH_BASIN">TEMPORARY FLOODWATER STORAGE VOLUME ESTIMATIONS USING 1-m LiDAR AND 30-m NED DEMS OF THE RED RIVER OF THE NORTH BASIN</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Compared here are storage volumes determined for 120 transect locations from 1-m Light Detection ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Compared here are storage volumes determined for 120 transect locations from 1-m Light Detection and Ranging (LiDAR) and 30-m National Elevation Dataset (NED) Digital Elevation Models (DEMs). The transects represent flat-, moderate-, and high-relief terrain in the Forest River Watershed of the Red River of the North Basin. Results indicate that either DEM yields acceptable storage estimates for terrain with flat to moderate-relief and LiDAR provides the more accurate estimate in areas of high-relief. In general, storage depths derived from LiDAR DEMs are greater than those extracted from NED DEMs, although storage estimates are not significantly different between the two datasets for flat-and moderate-relief areas. Each dataset can be used for storage estimation as a function of the local relief conditions, and certain section characteristics, which provided a basis to explain the patterns of observed discrepancies.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="df2984ca4f6da32b4cf95a89a999c983" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":79418876,"asset_id":69252510,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/79418876/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="69252510"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="69252510"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 69252510; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "df2984ca4f6da32b4cf95a89a999c983" } } $('.js-work-strip[data-work-id=69252510]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":69252510,"title":"TEMPORARY FLOODWATER STORAGE VOLUME ESTIMATIONS USING 1-m LiDAR AND 30-m NED DEMS OF THE RED RIVER OF THE NORTH BASIN","internal_url":"https://www.academia.edu/69252510/TEMPORARY_FLOODWATER_STORAGE_VOLUME_ESTIMATIONS_USING_1_m_LiDAR_AND_30_m_NED_DEMS_OF_THE_RED_RIVER_OF_THE_NORTH_BASIN","owner_id":138386,"coauthors_can_edit":true,"owner":{"id":138386,"first_name":"Bradley","middle_initials":null,"last_name":"Rundquist","page_name":"BradleyRundquist","domain_name":"und","created_at":"2010-02-26T04:13:55.837-08:00","display_name":"Bradley Rundquist","url":"https://und.academia.edu/BradleyRundquist"},"attachments":[{"id":79418876,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/79418876/thumbnails/1.jpg","file_name":"Pachhai_S.pdf","download_url":"https://www.academia.edu/attachments/79418876/download_file","bulk_download_file_name":"TEMPORARY_FLOODWATER_STORAGE_VOLUME_ESTI.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/79418876/Pachhai_S-libre.pdf?1642952594=\u0026response-content-disposition=attachment%3B+filename%3DTEMPORARY_FLOODWATER_STORAGE_VOLUME_ESTI.pdf\u0026Expires=1740502953\u0026Signature=Yf-sS672KERyKHj9j26hh4mkDpsvUrRbrHLcbdovXzFd6VQaqD4iVozs1ZQ33MsAfl5qUPtPg2ApDxPp2t2Q-n8NogDYwXSm8m4tX~lDEeoY-0MPfAWOKg71mhADtO88SJ28bPRkRGSHWOlwaOwJwIMlw0xnqeomlL~4NuLMR60nEzegow8jL7KnvrzlAfhSA03u1rwCU4BGWFKhLgimYn2IZBjtYYnfikRlx-P-OOFgH-QgJ8dU5PV6zkApj2b1duLz3yJ567mp90Eojv9Y~jJDaHqFaVbgcd9OtRVsVBfotNW-mbaFQw64PXey52YZNtFhpQ8xO0U9FaDY~JQ2DA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":79418878,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/79418878/thumbnails/1.jpg","file_name":"Pachhai_S.pdf","download_url":"https://www.academia.edu/attachments/79418878/download_file","bulk_download_file_name":"TEMPORARY_FLOODWATER_STORAGE_VOLUME_ESTI.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/79418878/Pachhai_S-libre.pdf?1642952595=\u0026response-content-disposition=attachment%3B+filename%3DTEMPORARY_FLOODWATER_STORAGE_VOLUME_ESTI.pdf\u0026Expires=1740502953\u0026Signature=dLcyd3tic8XVkiEyTpHRSUmFIQvDxnd0xWHnTc0JNUXNd4oxxl5P5Nl1oUBS37vIBdeS65fDTpwHmqA1FHcExpIoP1gG~n-B7hkZKb73J9JuPeZKehd6XCYWGZ67wPBxtwZnnnlKIcJb5Ziq1sIdm1Gz8BoZgmu1cj9FzgBR1VpPIpJ5e~MDY9tTPYDq8uj6m7DV-9BrdkVscgXEMY53aPplrxWdbAKWKhz8J9IQf1uK0WXYGYrGAsfBRr8djhz518ZRKZIMG2uEUOlc7Fzb8bsV5hwljF4B0leZdu1wxvvYPHPqVZvOCMXkfukVUBVPPxCD4IoDusyOgrHsLKjR3w__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="69252509"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/69252509/Remembering_Neil_Armstrong_the_scientist"><img alt="Research paper thumbnail of Remembering Neil Armstrong – the scientist" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/69252509/Remembering_Neil_Armstrong_the_scientist">Remembering Neil Armstrong – the scientist</a></div><div class="wp-workCard_item"><span>Geocarto International</span><span>, 2012</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We, at Geocarto International, pay tribute to the life and legacy of Neil Armstrong who is widely...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">We, at Geocarto International, pay tribute to the life and legacy of Neil Armstrong who is widely known as the first man on the Moon. We would like to remember Neil Armstrong – the scientist who conducted scientific investigations on the Moon on behalf of Earth-bound researchers and collected geologic samples for global geoscience communities. It is well known that geologic samples from Apollo missions are distributed on loan to investigators world-wide. It is true that Neil Armstrong’s first love was flying. He was a pilot, a test pilot and a research pilot. His engineering mind was devoted to all aspects of flying. Neil Armstrong also took his duties as scientist during his space missions seriously. He trained with NASA geologists to make sure he understood complex lunar landscapes and that he collected scientifically useful samples. His imagery and scientific photography was also valuable to those who were going to analyse sample on the ground. Neil Armstrong excelled in duties as a scientist as well. In the words of Rice University Historian Douglas Brinkley ‘what mattered to him [Neil] was old fashioned public service, iron discipline, and never making a mistake’. We salute Neil Armstrong – the scientist, the pilot, the explorer. In this issue, Bayramov et al. discuss quantitative assessment of vegetation cover and soil degradation while Kumar et al. use WorldView-II to extract information on vegetation and built-up environments. Abdideh and Bargahi design a 3D model for prediction of oilfield tops using geostatistical methods. Hernandez et al. assess the impact of climate change on bark bettle attacks on coniferous forests in Honduras. Ogunbadwa uses Nigeriasat-1 data for mapping malaria severity. These papers make this issue worth your time. We are always eager to hear from you.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="69252509"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="69252509"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 69252509; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=69252509]").text(description); $(".js-view-count[data-work-id=69252509]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 69252509; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='69252509']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=69252509]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":69252509,"title":"Remembering Neil Armstrong – the scientist","internal_url":"https://www.academia.edu/69252509/Remembering_Neil_Armstrong_the_scientist","owner_id":138386,"coauthors_can_edit":true,"owner":{"id":138386,"first_name":"Bradley","middle_initials":null,"last_name":"Rundquist","page_name":"BradleyRundquist","domain_name":"und","created_at":"2010-02-26T04:13:55.837-08:00","display_name":"Bradley Rundquist","url":"https://und.academia.edu/BradleyRundquist"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="69252459"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/69252459/Riparian_and_landscape_disturbance_effects_on_stream_fish_community_composition_in_an_agriculturally_dominated_drainage"><img alt="Research paper thumbnail of Riparian and landscape disturbance effects on stream fish community composition in an agriculturally-dominated drainage" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/69252459/Riparian_and_landscape_disturbance_effects_on_stream_fish_community_composition_in_an_agriculturally_dominated_drainage">Riparian and landscape disturbance effects on stream fish community composition in an agriculturally-dominated drainage</a></div><div class="wp-workCard_item"><span>Aquatic Ecosystem Health & Management</span><span>, 2017</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We compared historical stream fish community sampling and remote sensing data from 1993–2011 in a...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">We compared historical stream fish community sampling and remote sensing data from 1993–2011 in an agriculturally-dominated drainage basin to determine the effects of varying levels of riparian and landscape disturbances on fish communities. Stream fish guilds were analyzed with National Land Cover Database and aerial imagery products to quantify disturbance levels at a local and watershed scale. Insectivores and benthic insectivores were associated with intact riparian areas, whereas environmentally tolerant and omnivorous species were found in environments with degraded riparian areas. Riparian disturbances had the greatest effect near the stream (0–10 m), and the effects diminished with increasing distance from the stream. This spatial scale corresponds with those reported in the literature whereby allocthonous inputs and riparian filtering influenced stream fish communities and water quality. The landscape disturbance was not a strong predictor for any fish guild, indicating tha...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="69252459"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="69252459"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 69252459; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=69252459]").text(description); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="54833641"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/54833641/Semi_Automatic_Fractional_Snow_Cover_Monitoring_from_Near_Surface_Remote_Sensing_in_Grassland"><img alt="Research paper thumbnail of Semi-Automatic Fractional Snow Cover Monitoring from Near-Surface Remote Sensing in Grassland" class="work-thumbnail" src="https://attachments.academia-assets.com/71004381/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/54833641/Semi_Automatic_Fractional_Snow_Cover_Monitoring_from_Near_Surface_Remote_Sensing_in_Grassland">Semi-Automatic Fractional Snow Cover Monitoring from Near-Surface Remote Sensing in Grassland</a></div><div class="wp-workCard_item"><span>Remote Sensing</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Snow cover is an important variable in both climatological and hydrological studies because of it...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Snow cover is an important variable in both climatological and hydrological studies because of its relationship to environmental energy and mass flux. However, variability in snow cover can confound satellite-based efforts to monitor vegetation phenology. This research explores the utility of the PhenoCam Network cameras to estimate Fractional Snow Cover (FSC) in grassland. The goal is to operationalize FSC estimates from PhenoCams to inform and improve the satellite-based determination of phenological metrics. The study site is the Oakville Prairie Biological Field Station, located near Grand Forks, North Dakota. We developed a semi-automated process to estimate FSC from PhenoCam images through Python coding. Compared with previous research employing RGB images only, our use of the monochrome RGB + NIR (near-infrared) reduced pixel misclassification and increased accuracy. The results had an average RMSE of less than 8% FSC compared to visual estimates. Our pixel-based accuracy ass...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="d34577f0de05c85d9546604a5b991774" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71004381,"asset_id":54833641,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71004381/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="54833641"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="54833641"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 54833641; 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window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=54833640]").text(description); $(".js-view-count[data-work-id=54833640]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 54833640; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='54833640']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=54833640]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":54833640,"title":"Scaling Phenocam GCC, NDVI, and EVI2 with Harmonized Landsat-Sentinel using Gaussian Processes","internal_url":"https://www.academia.edu/54833640/Scaling_Phenocam_GCC_NDVI_and_EVI2_with_Harmonized_Landsat_Sentinel_using_Gaussian_Processes","owner_id":138386,"coauthors_can_edit":true,"owner":{"id":138386,"first_name":"Bradley","middle_initials":null,"last_name":"Rundquist","page_name":"BradleyRundquist","domain_name":"und","created_at":"2010-02-26T04:13:55.837-08:00","display_name":"Bradley Rundquist","url":"https://und.academia.edu/BradleyRundquist"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="54833639"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/54833639/Geocarto_International_s_on_going_long_term_mission_to_publish_research_on_Earth_Observations_and_GIS_our_notable_contributions_to_Sustainability_Development_Goals_of_the_United_Nations_2030_Agenda_for_Sustainable_Development"><img alt="Research paper thumbnail of Geocarto International’s on-going long-term mission to publish research on Earth Observations and GIS: our notable contributions to Sustainability Development Goals of the United Nations 2030 Agenda for Sustainable Development" class="work-thumbnail" src="https://attachments.academia-assets.com/71004374/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/54833639/Geocarto_International_s_on_going_long_term_mission_to_publish_research_on_Earth_Observations_and_GIS_our_notable_contributions_to_Sustainability_Development_Goals_of_the_United_Nations_2030_Agenda_for_Sustainable_Development">Geocarto International’s on-going long-term mission to publish research on Earth Observations and GIS: our notable contributions to Sustainability Development Goals of the United Nations 2030 Agenda for Sustainable Development</a></div><div class="wp-workCard_item"><span>Geocarto International</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">During our long history of 35 years of publication, Geocarto International's primary mission has ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">During our long history of 35 years of publication, Geocarto International's primary mission has been to publish research focused on Earth observations and GIS with an emphasis on disseminating this vital information to developing nations in many regions of the world. In addition, Geocarto International has encouraged papers that discuss applications and utilization of Remote Sensing and GIS technologies and sciences to societal issues such as deforestation and environmental, and land degradation, water availability and quality, urban growth and climate variability to name a few. Geocarto International has been on the forefront by publishing special issues-for example on Global Environmental Change (Lee et al. 1993), and NASA earth science data for application to public health that highlighted how the Center for Disease Control (CDC) uses remote sensing data as applied to monitor disease vectors (Quattrochi et al. 2014). The current global public health emergency caused by the COVID-19 will further spur development of GIS and other geospatial technologies that will enable future first responders to rapidly track the spread and locations of disease hot spots. We are encouraged to note that Remote sensing and Geographic Information Systems (GIS) (and related research published in Geocarto International will continue to play an ever more important role in support of the United Nations 2030 Agenda for Sustainable Development (<a href="http://sustainabledevelopnment.un.org/sdgs" rel="nofollow">http://sustainabledevelopnment.un.org/sdgs</a> 2020). This agenda, adopted by all United Nations (UN) Member States in 2015, provides a blueprint for peace and prosperity for people and the planet, both now and in the future. Complementing the 17 sustainability development goals (SDGs) associated with this UN agenda, spatial technology scientists can work hand and hand with strategies that improve health and education, reduce inequality and spur economic growth, through research efforts that tackle climate change and provide spatial analytical approaches that preserve our oceans and terrestrial landscapes including our croplands and forests. The UN's Division for Sustainable Development Goals (DSDG) in the United Nations Department of Economic and Social Affairs (UNDESA) provides substantive support and capacity building for these key themes. Such themes as water, energy, climate, oceans, urbanization, transportation, and science and technology are all key earth system dynamics that can be monitored using spatial technologies and are consistently summarized through research published in Geocarto International. Goals 1,2 and 3 focusing on 'No Poverty, Zero Hunger and Good Health and Well-Being' are related to our planet's agricultural productivity and capacity-an area where Earth observations and Geospatial technologies play a significant role from precision</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="a3d30048952762e1447e6a9d6fdc6044" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71004374,"asset_id":54833639,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71004374/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="54833639"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="54833639"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 54833639; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=54833639]").text(description); $(".js-view-count[data-work-id=54833639]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 54833639; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='54833639']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "a3d30048952762e1447e6a9d6fdc6044" } } $('.js-work-strip[data-work-id=54833639]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":54833639,"title":"Geocarto International’s on-going long-term mission to publish research on Earth Observations and GIS: our notable contributions to Sustainability Development Goals of the United Nations 2030 Agenda for Sustainable Development","internal_url":"https://www.academia.edu/54833639/Geocarto_International_s_on_going_long_term_mission_to_publish_research_on_Earth_Observations_and_GIS_our_notable_contributions_to_Sustainability_Development_Goals_of_the_United_Nations_2030_Agenda_for_Sustainable_Development","owner_id":138386,"coauthors_can_edit":true,"owner":{"id":138386,"first_name":"Bradley","middle_initials":null,"last_name":"Rundquist","page_name":"BradleyRundquist","domain_name":"und","created_at":"2010-02-26T04:13:55.837-08:00","display_name":"Bradley Rundquist","url":"https://und.academia.edu/BradleyRundquist"},"attachments":[{"id":71004374,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71004374/thumbnails/1.jpg","file_name":"10106049.2020.pdf","download_url":"https://www.academia.edu/attachments/71004374/download_file","bulk_download_file_name":"Geocarto_International_s_on_going_long_t.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71004374/10106049.2020-libre.pdf?1633205997=\u0026response-content-disposition=attachment%3B+filename%3DGeocarto_International_s_on_going_long_t.pdf\u0026Expires=1740502953\u0026Signature=hBa4s5fmV582rqmns4N~8EklgLR3EiY7San49k0rfk0M8R6nFRoDqXdvBZ5~e4-4gV~6o3l3ZBVVfKu3Eb9kV4u0nErc6A89djJWq20R12EVruodm95Tp6ECwPA11PuHba1cMxFJfP68RJeOkmJPa1A4reee7l0gsLxQhZ-NtDCrZTNSoWuuliGVqD5udeubBDTJI-7JwsttkGonupaKGKTG3Ecn-gSemziHXQ7qg1uJwzFd8wQnfRqWI2T2VKAsqGDplxQNDSAUNsV5kDWKpipTeSR3~cmJ0eMFR-M6U0dnvMYItZRQZe1qWZJCQBqHpQQgArkwTUn8M3STRwPg3w__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="54833638"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/54833638/An_exploration_of_colorectal_cancer_incidence_rates_in_North_Dakota_USA_via_structural_equation_modeling"><img alt="Research paper thumbnail of An exploration of colorectal cancer incidence rates in North Dakota, USA, via structural equation modeling" class="work-thumbnail" src="https://attachments.academia-assets.com/71004371/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/54833638/An_exploration_of_colorectal_cancer_incidence_rates_in_North_Dakota_USA_via_structural_equation_modeling">An exploration of colorectal cancer incidence rates in North Dakota, USA, via structural equation modeling</a></div><div class="wp-workCard_item"><span>International Journal of Colorectal Disease</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Purpose The state of North Dakota has one of the highest incidence rates for colorectal cancer in...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Purpose The state of North Dakota has one of the highest incidence rates for colorectal cancer in the USA. Its high incidence rate, coupled with a large variation in incidence rates among counties within the state, makes North Dakota a "natural laboratory" in which to investigate environmental clues to colorectal cancer. We conducted a hypothesis-generating study to explore potential determinants of colorectal cancer in North Dakota. Methods We obtained county-specific incidence rates for North Dakota's 53 counties from the statewide cancer registry and corresponding data on county demographic, agricultural, and geophysical features from population-based sources. Candidate demographic/agricultural variables included median household income, population density, colorectal cancer screening rates, average farm size (in acres), and the percent of county fertilized. Geophysical variables included the uranium content of soil, residential radon levels, and source of drinking water (municipal or well water). Statistical analyses were performed via multivariate regression and structural equation modeling. Results Colorectal cancer incidence rates across North Dakota counties varied 3-fold. The structural equation model identified a significant role for well water use (p < 0.05). This finding is consistent with studies that implicate well water in colorectal cancer. Conclusions Well water contains several agents, e.g., bacteria, disinfection by-products, and nitrates that are potent colorectal carcinogens. Studies of well water use and colorectal cancer risk at the individual level in North Dakota are warranted.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="13e130e171fc68c8bac725bcf9ede170" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71004371,"asset_id":54833638,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71004371/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="54833638"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="54833638"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 54833638; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=54833638]").text(description); $(".js-view-count[data-work-id=54833638]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 54833638; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='54833638']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="54833635"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/54833635/Monitoring_Landscape_Dynamics_in_Central_U_S_Grasslands_with_Harmonized_Landsat_8_and_Sentinel_2_Time_Series_Data"><img alt="Research paper thumbnail of Monitoring Landscape Dynamics in Central U.S. Grasslands with Harmonized Landsat-8 and Sentinel-2 Time Series Data" class="work-thumbnail" src="https://attachments.academia-assets.com/71004376/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/54833635/Monitoring_Landscape_Dynamics_in_Central_U_S_Grasslands_with_Harmonized_Landsat_8_and_Sentinel_2_Time_Series_Data">Monitoring Landscape Dynamics in Central U.S. Grasslands with Harmonized Landsat-8 and Sentinel-2 Time Series Data</a></div><div class="wp-workCard_item"><span>Remote Sensing</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Remotely monitoring changes in central U.S. grasslands is challenging because these landscapes te...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Remotely monitoring changes in central U.S. grasslands is challenging because these landscapes tend to respond quickly to disturbances and changes in weather. Such dynamic responses influence nutrient cycling, greenhouse gas contributions, habitat availability for wildlife, and other ecosystem processes and services. Traditionally, coarse-resolution satellite data acquired at daily intervals have been used for monitoring. Recently, the harmonized Landsat-8 and Sentinel-2 (HLS) data increased the temporal frequency of the data. Here we investigated if the increased data frequency provided adequate observations to characterize highly dynamic grassland processes. We evaluated HLS data available for 2016 to (1) determine if data from Sentinel-2 contributed to an improvement in characterizing landscape processes over Landsat-8 data alone, and (2) quantify how observation frequency impacted results. Specifically, we investigated into estimating annual vegetation phenology, detecting burn ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="a68d222c489275ebe3e002c08c6c9c2b" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71004376,"asset_id":54833635,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71004376/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="54833635"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="54833635"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 54833635; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "a68d222c489275ebe3e002c08c6c9c2b" } } $('.js-work-strip[data-work-id=54833635]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":54833635,"title":"Monitoring Landscape Dynamics in Central U.S. Grasslands with Harmonized Landsat-8 and Sentinel-2 Time Series Data","internal_url":"https://www.academia.edu/54833635/Monitoring_Landscape_Dynamics_in_Central_U_S_Grasslands_with_Harmonized_Landsat_8_and_Sentinel_2_Time_Series_Data","owner_id":138386,"coauthors_can_edit":true,"owner":{"id":138386,"first_name":"Bradley","middle_initials":null,"last_name":"Rundquist","page_name":"BradleyRundquist","domain_name":"und","created_at":"2010-02-26T04:13:55.837-08:00","display_name":"Bradley Rundquist","url":"https://und.academia.edu/BradleyRundquist"},"attachments":[{"id":71004376,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71004376/thumbnails/1.jpg","file_name":"pdf.pdf","download_url":"https://www.academia.edu/attachments/71004376/download_file","bulk_download_file_name":"Monitoring_Landscape_Dynamics_in_Central.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71004376/pdf-libre.pdf?1633206004=\u0026response-content-disposition=attachment%3B+filename%3DMonitoring_Landscape_Dynamics_in_Central.pdf\u0026Expires=1740502953\u0026Signature=FDLty33-dNAPfGAEoD1at7kzLEFcGZUfHqmOtliWAEHRWQx~FnNQ~AAWvXIWJdJteKhNlWBvkEJZskJ05xWH2tVlhj0o-sszFPN1eqM2zk6bNJt9--oTA~HkqWKWXrKZCHPGJquLRi60YOs1QLvkg1z1PhYkGXuellxGJae58m-Wf6icr4EqrUy~0NfPlRB8BoixcX~8n2qpPTMBM9O~w6u~9kmcVlSHKQhfQ~KckX6O07HMby0~fUtFblwuLKzjp712cpi11PqQYcQycr1FYWVI7DDA9ydwkO~r6i43~f3U~8NUtELuPBrqM3lgMiXLmf6uCuUXDjZAFX6XsnR8hA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":71004378,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71004378/thumbnails/1.jpg","file_name":"pdf.pdf","download_url":"https://www.academia.edu/attachments/71004378/download_file","bulk_download_file_name":"Monitoring_Landscape_Dynamics_in_Central.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71004378/pdf-libre.pdf?1633206005=\u0026response-content-disposition=attachment%3B+filename%3DMonitoring_Landscape_Dynamics_in_Central.pdf\u0026Expires=1740502953\u0026Signature=BHMQ7fkGnocF--vPAB3GZ1v8tw6qR9hQmUUAUy61xDGBCQXj0lbsBT94GriXGpJM5uL83iqH8o1Pl4Qs5E4Vjh3UtEUq19z0m1pXOaJu8C7jGJeJO0boP6SfmesKFzbU1QGjiPbe3Xcs7qBW1VGCK419VA0Ukb1tppZ8WpnQI3MZJhGY59tnuh9NvY2cycpfB7pa3VAaQY4Q0Lf-fbullsGPRPia2s7I83VTJaV2ez4ORVCA2xvPEbnqPOTxH154yQ9WbalTe8ozDB7Bc16YxB8ivIk0NM6da1MXHnf0t54pdmr8GV~XLrUl62p4zE8LEFupd620rOEtJFf7pn21yw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="54833634"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/54833634/Seasonal_home_ranges_and_habitat_selection_of_three_elk_Cervus_elaphus_herds_in_North_Dakota"><img alt="Research paper thumbnail of Seasonal home ranges and habitat selection of three elk (Cervus elaphus) herds in North Dakota" class="work-thumbnail" src="https://attachments.academia-assets.com/71004467/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/54833634/Seasonal_home_ranges_and_habitat_selection_of_three_elk_Cervus_elaphus_herds_in_North_Dakota">Seasonal home ranges and habitat selection of three elk (Cervus elaphus) herds in North Dakota</a></div><div class="wp-workCard_item"><span>PLOS ONE</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Changes in land use have resulted in range shifts of many wildlife species, including those enter...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Changes in land use have resulted in range shifts of many wildlife species, including those entering novel environments, resulting in the critical need to understand their spatial ecology to inform ecosystem effects and management decisions. Dispersing elk (Cervus elaphus) were colonizing areas of suitable habitat in the Northern Great Plains, USA, resulting in crop depredation complaints in these areas. Although state resource managers had little information on these elk herds, limited evidence suggested temporal movements into Canada. We collected and analyzed essential information on home range and habitat selection for 3 elk herds residing in North Dakota. We captured 5 adult female elk in each study area, affixed global positioning system collars, and monitored them for 1 year (2016-2017). We estimated diel period, seasonal, and hunting season home ranges using Brownian Bridge Movement Models for each individual. We analyzed habitat selection using multinomial logit models to test for differences in use of land classes, and for departures from proportionate use based on random sampling; our predictor variables included individual elk, diel period, and season. Home ranges differed between the 3 herds, seasons, and diel period; gun and winter season home ranges were both larger than in summer, as was night when compared with day. Female elk generally restricted themselves to cover during the day and entered open areas at night and during winter months. Our results also suggest that elk in our study areas tended to seek more cover, and in the case of our Turtle Mountain study area, some cross into Canada during gun season. Our study provides a better understanding of the spatial ecology of elk in the Northern Great Plains while highlighting the need for enhanced international cooperative management efforts.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="d7c3999b85bd1f12cf769094ce81f30f" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71004467,"asset_id":54833634,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71004467/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="54833634"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="54833634"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 54833634; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="54833632"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/54833632/Detection_of_Shelterbelt_Density_Change_Using_Historic_APFO_and_NAIP_Aerial_Imagery"><img alt="Research paper thumbnail of Detection of Shelterbelt Density Change Using Historic APFO and NAIP Aerial Imagery" class="work-thumbnail" src="https://attachments.academia-assets.com/71004379/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/54833632/Detection_of_Shelterbelt_Density_Change_Using_Historic_APFO_and_NAIP_Aerial_Imagery">Detection of Shelterbelt Density Change Using Historic APFO and NAIP Aerial Imagery</a></div><div class="wp-workCard_item"><span>Remote Sensing</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Grand Forks County, North Dakota, boasts the highest concentration of shelterbelts in the World. ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Grand Forks County, North Dakota, boasts the highest concentration of shelterbelts in the World. As trees age and reach their lifespan limits, renovations should have taken place with new trees being planted. However, in recent years, the rate of tree removal is thought to exceed the rate of replanting, which can result in a net loss of shelterbelts. Through manual digitization and geographic object-based image analysis (GEOBIA), we mapped shelterbelt densities in the Grand Forks County using historical and contemporary aerial photography, and estimated actual changes in density over 54 years. Our results showed a doubling in shelterbelt densities from 1962 to 2014, with an increase of 6402 m2/km2 over the 52 years (or 123 m2/km2/year). From 2014 to 2016, we measured 1,040,178 m2 of shelterbelt areas removed from the county, creating a density loss of −157 m2/km2/year. The total change over two years was relatively small compared with that seen over the previous 52 years. However, t...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="d6520b71f4cb595cd74926a32c5b30d9" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71004379,"asset_id":54833632,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71004379/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="54833632"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="54833632"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 54833632; 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</script> </div><div class="profile--tab_content_container js-tab-pane tab-pane" data-section-id="12161286" id="papers"><div class="js-work-strip profile--work_container" data-work-id="126397440"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/126397440/TEMPORARY_FLOODWATER_STORAGE_VOLUME_ESTIMATIONS_USING_1_m_LiDAR_AND_30_m_NED_DEMS_OF_THE_RED_RIVER_OF_THE_NORTH_BASIN"><img alt="Research paper thumbnail of TEMPORARY FLOODWATER STORAGE VOLUME ESTIMATIONS USING 1-m LiDAR AND 30-m NED DEMS OF THE RED RIVER OF THE NORTH BASIN" class="work-thumbnail" src="https://attachments.academia-assets.com/120279805/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/126397440/TEMPORARY_FLOODWATER_STORAGE_VOLUME_ESTIMATIONS_USING_1_m_LiDAR_AND_30_m_NED_DEMS_OF_THE_RED_RIVER_OF_THE_NORTH_BASIN">TEMPORARY FLOODWATER STORAGE VOLUME ESTIMATIONS USING 1-m LiDAR AND 30-m NED DEMS OF THE RED RIVER OF THE NORTH BASIN</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="9d9444bdf312a90d2cd2b810c1855bcd" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":120279805,"asset_id":126397440,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/120279805/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="126397440"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="126397440"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 126397440; 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</script> <div class="js-work-strip profile--work_container" data-work-id="85592060"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/85592060/Characteristics_and_Geography_of_Oil_Spills_in_North_Dakota"><img alt="Research paper thumbnail of Characteristics and Geography of Oil Spills in North Dakota" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/85592060/Characteristics_and_Geography_of_Oil_Spills_in_North_Dakota">Characteristics and Geography of Oil Spills in North Dakota</a></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="85592060"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="85592060"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 85592060; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=85592060]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":85592060,"title":"Characteristics and Geography of Oil Spills in North Dakota","internal_url":"https://www.academia.edu/85592060/Characteristics_and_Geography_of_Oil_Spills_in_North_Dakota","owner_id":138386,"coauthors_can_edit":true,"owner":{"id":138386,"first_name":"Bradley","middle_initials":null,"last_name":"Rundquist","page_name":"BradleyRundquist","domain_name":"und","created_at":"2010-02-26T04:13:55.837-08:00","display_name":"Bradley Rundquist","url":"https://und.academia.edu/BradleyRundquist"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="85592050"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/85592050/Spectral_characterization_of_the_invasive_shrub_saltcedar_Tamarix_spp_in_North_Dakota"><img alt="Research paper thumbnail of Spectral characterization of the invasive shrub saltcedar ( Tamarix spp. ) in North Dakota" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/85592050/Spectral_characterization_of_the_invasive_shrub_saltcedar_Tamarix_spp_in_North_Dakota">Spectral characterization of the invasive shrub saltcedar ( Tamarix spp. ) in North Dakota</a></div><div class="wp-workCard_item"><span>Geocarto International</span><span>, 2007</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">A large infestation of the invasive shrub saltcedar (Tamarix ramosissima and Tamarix chinensis) w...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">A large infestation of the invasive shrub saltcedar (Tamarix ramosissima and Tamarix chinensis) was first detected east of the Montana–North Dakota border in 2001. Saltcedar has since spread from Montana along the Yellowstone and Missouri River corridors into the Lake Sakakawea region of west-central North Dakota, and has currently halted its progress at the reservoir&#39;s Garrison Dam. A receding lake level since 2001, the result of a moderate regional drought, has allowed saltcedar to quickly invade newly exposed shoreline. The infestation in some locations is severe, and there is concern among the lake managers that, left unchecked, the shrub will move upland and displace native species, degrade shoreline aesthetics, and damage wildlife habitat. Eradication efforts are underway, yet there is much interest among land managers in North Dakota in characterizing saltcedar spectrally to assist future remote detection efforts, especially in areas that are difficult to access on foot. To this end, close-range hyperspectral data collection was conducted on three dates during the 2003 growing season. This study reports the findings of close-range sensor data analyses.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="85592050"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="85592050"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 85592050; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=85592050]").text(description); $(".js-view-count[data-work-id=85592050]").attr('title', description).tooltip(); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="69252512"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/69252512/Measurements_Over_Native_Tallgrass"><img alt="Research paper thumbnail of Measurements Over Native Tallgrass" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/69252512/Measurements_Over_Native_Tallgrass">Measurements Over Native Tallgrass</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">influence of canopy green vegetation fraction on spectral</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="69252512"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="69252512"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 69252512; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=69252512]").text(description); $(".js-view-count[data-work-id=69252512]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 69252512; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='69252512']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=69252512]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":69252512,"title":"Measurements Over Native Tallgrass","internal_url":"https://www.academia.edu/69252512/Measurements_Over_Native_Tallgrass","owner_id":138386,"coauthors_can_edit":true,"owner":{"id":138386,"first_name":"Bradley","middle_initials":null,"last_name":"Rundquist","page_name":"BradleyRundquist","domain_name":"und","created_at":"2010-02-26T04:13:55.837-08:00","display_name":"Bradley Rundquist","url":"https://und.academia.edu/BradleyRundquist"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="69252511"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/69252511/Flood_damage_assessment_and_survey_of_mitigation_efforts_at_Stump_Lake_North_Dakota_a_study_of_a_closed_basin_lake_flood"><img alt="Research paper thumbnail of Flood damage assessment and survey of mitigation efforts at Stump Lake, North Dakota : a study of a closed-basin lake flood" class="work-thumbnail" src="https://attachments.academia-assets.com/79418879/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/69252511/Flood_damage_assessment_and_survey_of_mitigation_efforts_at_Stump_Lake_North_Dakota_a_study_of_a_closed_basin_lake_flood">Flood damage assessment and survey of mitigation efforts at Stump Lake, North Dakota : a study of a closed-basin lake flood</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Since 1993, Devils Lake, a terminal lake in northeastern North Dakota, has risen 7.3 m in respons...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Since 1993, Devils Lake, a terminal lake in northeastern North Dakota, has risen 7.3 m in response to an unprecedented ten-year regional wet cycle. Lake area has nearly tripled, resulting in more than $400 million dollars in direct flood damages. Beginning in 1999 Devils Lake began to overflow into Stump Lake, a smaller closed lake sub-basin located in Nelson County. Outflow from Devils Lake has combined with local runoff to produce a 1.5-m rise in Stump Lake over the past three years. Extensive rural flooding marked by an increase in the number, size, and permanence of wetlands has also occurred within both lake basins over the same period. The authors document the flood history of Stump Lake and rural Nelson County, assess the flood damages resulting from the rise of Stump Lake and the growth of rural wetlands in Nelson County, and survey the flood mitigation efforts associated with this closed-basin flood hazard. Remote sensing image interpretation, field work, personal interview...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="44aae77f50d0451f385335ff5859d9fe" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":79418879,"asset_id":69252511,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/79418879/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="69252511"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="69252511"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 69252511; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=69252511]").text(description); $(".js-view-count[data-work-id=69252511]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 69252511; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='69252511']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "44aae77f50d0451f385335ff5859d9fe" } } $('.js-work-strip[data-work-id=69252511]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":69252511,"title":"Flood damage assessment and survey of mitigation efforts at Stump Lake, North Dakota : a study of a closed-basin lake flood","internal_url":"https://www.academia.edu/69252511/Flood_damage_assessment_and_survey_of_mitigation_efforts_at_Stump_Lake_North_Dakota_a_study_of_a_closed_basin_lake_flood","owner_id":138386,"coauthors_can_edit":true,"owner":{"id":138386,"first_name":"Bradley","middle_initials":null,"last_name":"Rundquist","page_name":"BradleyRundquist","domain_name":"und","created_at":"2010-02-26T04:13:55.837-08:00","display_name":"Bradley Rundquist","url":"https://und.academia.edu/BradleyRundquist"},"attachments":[{"id":79418879,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/79418879/thumbnails/1.jpg","file_name":"qr164.pdf","download_url":"https://www.academia.edu/attachments/79418879/download_file","bulk_download_file_name":"Flood_damage_assessment_and_survey_of_mi.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/79418879/qr164-libre.pdf?1642952594=\u0026response-content-disposition=attachment%3B+filename%3DFlood_damage_assessment_and_survey_of_mi.pdf\u0026Expires=1740502953\u0026Signature=gdsHGDV5bmLr6guZ2-mq1BkzI~NPA-R-YN2Exa3llPyWia65d0DWUjdkIuDwomTIdRUYNJY9mGadI9mvDQPFnjxhhhCs-~i6TiZfNg-TFAySHk5vSRc9a-MNsGUNp5IDAq-XTwtDhslh5PNcq~ST39L5Q9PLiXXdwVTMVQct9YovMdoQuErtdqr4FnaQDNWqWgNbtfR21RObrBGoVR-qv~i25-UNfXc48ro5tTgtEw4hRilv7yaIxehYoNtOVAfUhFTlJm1pRVwn4TR10SayBqq1IhTf4iOSB9fWLM9egDP18oBhD6LsmR-r1NzQOO6xB8Ze-mD4MZTu-GyGcxYKQg__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":79418880,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/79418880/thumbnails/1.jpg","file_name":"qr164.pdf","download_url":"https://www.academia.edu/attachments/79418880/download_file","bulk_download_file_name":"Flood_damage_assessment_and_survey_of_mi.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/79418880/qr164-libre.pdf?1642952594=\u0026response-content-disposition=attachment%3B+filename%3DFlood_damage_assessment_and_survey_of_mi.pdf\u0026Expires=1740502953\u0026Signature=P7ORK3ow6odDFOESRZ6Et~tnq77ofeqRZ86MnO5vmdDRjjbK4FC56MWJt1Geg4zV9-PKaXvu4imwab2qHyV6FtEO8AFiG5347ActQNJPp~brwKbeJW6rc3rYDAraKAA-xD~Ld~d39an4iCUW~ksvsN181elWceSWADIDsURnTehNwRs1bkiz6ubgvcVoKxQDNvr9ibwG7xd-tHDjOh1KAf0~tU7F~HsJplkEhgMHGpq4pzy5o6weuWR0734hjOrVc0ahewVQQHj0emfjLYcE7lnd24arAzGnFFN8pVklHpnfw27Bjj76JtyeC4egxAzC5Y4pn6AN0ZCGkuMxUK428w__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="69252510"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/69252510/TEMPORARY_FLOODWATER_STORAGE_VOLUME_ESTIMATIONS_USING_1_m_LiDAR_AND_30_m_NED_DEMS_OF_THE_RED_RIVER_OF_THE_NORTH_BASIN"><img alt="Research paper thumbnail of TEMPORARY FLOODWATER STORAGE VOLUME ESTIMATIONS USING 1-m LiDAR AND 30-m NED DEMS OF THE RED RIVER OF THE NORTH BASIN" class="work-thumbnail" src="https://attachments.academia-assets.com/79418876/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/69252510/TEMPORARY_FLOODWATER_STORAGE_VOLUME_ESTIMATIONS_USING_1_m_LiDAR_AND_30_m_NED_DEMS_OF_THE_RED_RIVER_OF_THE_NORTH_BASIN">TEMPORARY FLOODWATER STORAGE VOLUME ESTIMATIONS USING 1-m LiDAR AND 30-m NED DEMS OF THE RED RIVER OF THE NORTH BASIN</a></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Compared here are storage volumes determined for 120 transect locations from 1-m Light Detection ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Compared here are storage volumes determined for 120 transect locations from 1-m Light Detection and Ranging (LiDAR) and 30-m National Elevation Dataset (NED) Digital Elevation Models (DEMs). The transects represent flat-, moderate-, and high-relief terrain in the Forest River Watershed of the Red River of the North Basin. Results indicate that either DEM yields acceptable storage estimates for terrain with flat to moderate-relief and LiDAR provides the more accurate estimate in areas of high-relief. In general, storage depths derived from LiDAR DEMs are greater than those extracted from NED DEMs, although storage estimates are not significantly different between the two datasets for flat-and moderate-relief areas. Each dataset can be used for storage estimation as a function of the local relief conditions, and certain section characteristics, which provided a basis to explain the patterns of observed discrepancies.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="df2984ca4f6da32b4cf95a89a999c983" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":79418876,"asset_id":69252510,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/79418876/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="69252510"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="69252510"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 69252510; 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="69252509"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/69252509/Remembering_Neil_Armstrong_the_scientist"><img alt="Research paper thumbnail of Remembering Neil Armstrong – the scientist" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/69252509/Remembering_Neil_Armstrong_the_scientist">Remembering Neil Armstrong – the scientist</a></div><div class="wp-workCard_item"><span>Geocarto International</span><span>, 2012</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We, at Geocarto International, pay tribute to the life and legacy of Neil Armstrong who is widely...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">We, at Geocarto International, pay tribute to the life and legacy of Neil Armstrong who is widely known as the first man on the Moon. We would like to remember Neil Armstrong – the scientist who conducted scientific investigations on the Moon on behalf of Earth-bound researchers and collected geologic samples for global geoscience communities. It is well known that geologic samples from Apollo missions are distributed on loan to investigators world-wide. It is true that Neil Armstrong’s first love was flying. He was a pilot, a test pilot and a research pilot. His engineering mind was devoted to all aspects of flying. Neil Armstrong also took his duties as scientist during his space missions seriously. He trained with NASA geologists to make sure he understood complex lunar landscapes and that he collected scientifically useful samples. His imagery and scientific photography was also valuable to those who were going to analyse sample on the ground. Neil Armstrong excelled in duties as a scientist as well. In the words of Rice University Historian Douglas Brinkley ‘what mattered to him [Neil] was old fashioned public service, iron discipline, and never making a mistake’. We salute Neil Armstrong – the scientist, the pilot, the explorer. In this issue, Bayramov et al. discuss quantitative assessment of vegetation cover and soil degradation while Kumar et al. use WorldView-II to extract information on vegetation and built-up environments. Abdideh and Bargahi design a 3D model for prediction of oilfield tops using geostatistical methods. Hernandez et al. assess the impact of climate change on bark bettle attacks on coniferous forests in Honduras. Ogunbadwa uses Nigeriasat-1 data for mapping malaria severity. These papers make this issue worth your time. We are always eager to hear from you.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="69252509"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="69252509"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 69252509; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=69252509]").text(description); $(".js-view-count[data-work-id=69252509]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 69252509; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='69252509']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (false){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=69252509]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":69252509,"title":"Remembering Neil Armstrong – the scientist","internal_url":"https://www.academia.edu/69252509/Remembering_Neil_Armstrong_the_scientist","owner_id":138386,"coauthors_can_edit":true,"owner":{"id":138386,"first_name":"Bradley","middle_initials":null,"last_name":"Rundquist","page_name":"BradleyRundquist","domain_name":"und","created_at":"2010-02-26T04:13:55.837-08:00","display_name":"Bradley Rundquist","url":"https://und.academia.edu/BradleyRundquist"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="69252459"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" rel="nofollow" href="https://www.academia.edu/69252459/Riparian_and_landscape_disturbance_effects_on_stream_fish_community_composition_in_an_agriculturally_dominated_drainage"><img alt="Research paper thumbnail of Riparian and landscape disturbance effects on stream fish community composition in an agriculturally-dominated drainage" class="work-thumbnail" src="https://a.academia-assets.com/images/blank-paper.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" rel="nofollow" href="https://www.academia.edu/69252459/Riparian_and_landscape_disturbance_effects_on_stream_fish_community_composition_in_an_agriculturally_dominated_drainage">Riparian and landscape disturbance effects on stream fish community composition in an agriculturally-dominated drainage</a></div><div class="wp-workCard_item"><span>Aquatic Ecosystem Health & Management</span><span>, 2017</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">We compared historical stream fish community sampling and remote sensing data from 1993–2011 in a...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">We compared historical stream fish community sampling and remote sensing data from 1993–2011 in an agriculturally-dominated drainage basin to determine the effects of varying levels of riparian and landscape disturbances on fish communities. Stream fish guilds were analyzed with National Land Cover Database and aerial imagery products to quantify disturbance levels at a local and watershed scale. Insectivores and benthic insectivores were associated with intact riparian areas, whereas environmentally tolerant and omnivorous species were found in environments with degraded riparian areas. Riparian disturbances had the greatest effect near the stream (0–10 m), and the effects diminished with increasing distance from the stream. This spatial scale corresponds with those reported in the literature whereby allocthonous inputs and riparian filtering influenced stream fish communities and water quality. The landscape disturbance was not a strong predictor for any fish guild, indicating tha...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="69252459"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="69252459"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 69252459; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=69252459]").text(description); 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$(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="54833641"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/54833641/Semi_Automatic_Fractional_Snow_Cover_Monitoring_from_Near_Surface_Remote_Sensing_in_Grassland"><img alt="Research paper thumbnail of Semi-Automatic Fractional Snow Cover Monitoring from Near-Surface Remote Sensing in Grassland" class="work-thumbnail" src="https://attachments.academia-assets.com/71004381/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/54833641/Semi_Automatic_Fractional_Snow_Cover_Monitoring_from_Near_Surface_Remote_Sensing_in_Grassland">Semi-Automatic Fractional Snow Cover Monitoring from Near-Surface Remote Sensing in Grassland</a></div><div class="wp-workCard_item"><span>Remote Sensing</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Snow cover is an important variable in both climatological and hydrological studies because of it...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Snow cover is an important variable in both climatological and hydrological studies because of its relationship to environmental energy and mass flux. However, variability in snow cover can confound satellite-based efforts to monitor vegetation phenology. This research explores the utility of the PhenoCam Network cameras to estimate Fractional Snow Cover (FSC) in grassland. The goal is to operationalize FSC estimates from PhenoCams to inform and improve the satellite-based determination of phenological metrics. The study site is the Oakville Prairie Biological Field Station, located near Grand Forks, North Dakota. We developed a semi-automated process to estimate FSC from PhenoCam images through Python coding. Compared with previous research employing RGB images only, our use of the monochrome RGB + NIR (near-infrared) reduced pixel misclassification and increased accuracy. The results had an average RMSE of less than 8% FSC compared to visual estimates. Our pixel-based accuracy ass...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="d34577f0de05c85d9546604a5b991774" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71004381,"asset_id":54833641,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71004381/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="54833641"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="54833641"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 54833641; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "-1" } } $('.js-work-strip[data-work-id=54833640]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":54833640,"title":"Scaling Phenocam GCC, NDVI, and EVI2 with Harmonized Landsat-Sentinel using Gaussian Processes","internal_url":"https://www.academia.edu/54833640/Scaling_Phenocam_GCC_NDVI_and_EVI2_with_Harmonized_Landsat_Sentinel_using_Gaussian_Processes","owner_id":138386,"coauthors_can_edit":true,"owner":{"id":138386,"first_name":"Bradley","middle_initials":null,"last_name":"Rundquist","page_name":"BradleyRundquist","domain_name":"und","created_at":"2010-02-26T04:13:55.837-08:00","display_name":"Bradley Rundquist","url":"https://und.academia.edu/BradleyRundquist"},"attachments":[]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="54833639"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/54833639/Geocarto_International_s_on_going_long_term_mission_to_publish_research_on_Earth_Observations_and_GIS_our_notable_contributions_to_Sustainability_Development_Goals_of_the_United_Nations_2030_Agenda_for_Sustainable_Development"><img alt="Research paper thumbnail of Geocarto International’s on-going long-term mission to publish research on Earth Observations and GIS: our notable contributions to Sustainability Development Goals of the United Nations 2030 Agenda for Sustainable Development" class="work-thumbnail" src="https://attachments.academia-assets.com/71004374/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/54833639/Geocarto_International_s_on_going_long_term_mission_to_publish_research_on_Earth_Observations_and_GIS_our_notable_contributions_to_Sustainability_Development_Goals_of_the_United_Nations_2030_Agenda_for_Sustainable_Development">Geocarto International’s on-going long-term mission to publish research on Earth Observations and GIS: our notable contributions to Sustainability Development Goals of the United Nations 2030 Agenda for Sustainable Development</a></div><div class="wp-workCard_item"><span>Geocarto International</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">During our long history of 35 years of publication, Geocarto International's primary mission has ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">During our long history of 35 years of publication, Geocarto International's primary mission has been to publish research focused on Earth observations and GIS with an emphasis on disseminating this vital information to developing nations in many regions of the world. In addition, Geocarto International has encouraged papers that discuss applications and utilization of Remote Sensing and GIS technologies and sciences to societal issues such as deforestation and environmental, and land degradation, water availability and quality, urban growth and climate variability to name a few. Geocarto International has been on the forefront by publishing special issues-for example on Global Environmental Change (Lee et al. 1993), and NASA earth science data for application to public health that highlighted how the Center for Disease Control (CDC) uses remote sensing data as applied to monitor disease vectors (Quattrochi et al. 2014). The current global public health emergency caused by the COVID-19 will further spur development of GIS and other geospatial technologies that will enable future first responders to rapidly track the spread and locations of disease hot spots. We are encouraged to note that Remote sensing and Geographic Information Systems (GIS) (and related research published in Geocarto International will continue to play an ever more important role in support of the United Nations 2030 Agenda for Sustainable Development (<a href="http://sustainabledevelopnment.un.org/sdgs" rel="nofollow">http://sustainabledevelopnment.un.org/sdgs</a> 2020). This agenda, adopted by all United Nations (UN) Member States in 2015, provides a blueprint for peace and prosperity for people and the planet, both now and in the future. Complementing the 17 sustainability development goals (SDGs) associated with this UN agenda, spatial technology scientists can work hand and hand with strategies that improve health and education, reduce inequality and spur economic growth, through research efforts that tackle climate change and provide spatial analytical approaches that preserve our oceans and terrestrial landscapes including our croplands and forests. The UN's Division for Sustainable Development Goals (DSDG) in the United Nations Department of Economic and Social Affairs (UNDESA) provides substantive support and capacity building for these key themes. Such themes as water, energy, climate, oceans, urbanization, transportation, and science and technology are all key earth system dynamics that can be monitored using spatial technologies and are consistently summarized through research published in Geocarto International. Goals 1,2 and 3 focusing on 'No Poverty, Zero Hunger and Good Health and Well-Being' are related to our planet's agricultural productivity and capacity-an area where Earth observations and Geospatial technologies play a significant role from precision</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="a3d30048952762e1447e6a9d6fdc6044" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71004374,"asset_id":54833639,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71004374/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="54833639"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="54833639"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 54833639; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "a3d30048952762e1447e6a9d6fdc6044" } } $('.js-work-strip[data-work-id=54833639]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":54833639,"title":"Geocarto International’s on-going long-term mission to publish research on Earth Observations and GIS: our notable contributions to Sustainability Development Goals of the United Nations 2030 Agenda for Sustainable Development","internal_url":"https://www.academia.edu/54833639/Geocarto_International_s_on_going_long_term_mission_to_publish_research_on_Earth_Observations_and_GIS_our_notable_contributions_to_Sustainability_Development_Goals_of_the_United_Nations_2030_Agenda_for_Sustainable_Development","owner_id":138386,"coauthors_can_edit":true,"owner":{"id":138386,"first_name":"Bradley","middle_initials":null,"last_name":"Rundquist","page_name":"BradleyRundquist","domain_name":"und","created_at":"2010-02-26T04:13:55.837-08:00","display_name":"Bradley Rundquist","url":"https://und.academia.edu/BradleyRundquist"},"attachments":[{"id":71004374,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71004374/thumbnails/1.jpg","file_name":"10106049.2020.pdf","download_url":"https://www.academia.edu/attachments/71004374/download_file","bulk_download_file_name":"Geocarto_International_s_on_going_long_t.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71004374/10106049.2020-libre.pdf?1633205997=\u0026response-content-disposition=attachment%3B+filename%3DGeocarto_International_s_on_going_long_t.pdf\u0026Expires=1740502953\u0026Signature=hBa4s5fmV582rqmns4N~8EklgLR3EiY7San49k0rfk0M8R6nFRoDqXdvBZ5~e4-4gV~6o3l3ZBVVfKu3Eb9kV4u0nErc6A89djJWq20R12EVruodm95Tp6ECwPA11PuHba1cMxFJfP68RJeOkmJPa1A4reee7l0gsLxQhZ-NtDCrZTNSoWuuliGVqD5udeubBDTJI-7JwsttkGonupaKGKTG3Ecn-gSemziHXQ7qg1uJwzFd8wQnfRqWI2T2VKAsqGDplxQNDSAUNsV5kDWKpipTeSR3~cmJ0eMFR-M6U0dnvMYItZRQZe1qWZJCQBqHpQQgArkwTUn8M3STRwPg3w__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="54833638"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/54833638/An_exploration_of_colorectal_cancer_incidence_rates_in_North_Dakota_USA_via_structural_equation_modeling"><img alt="Research paper thumbnail of An exploration of colorectal cancer incidence rates in North Dakota, USA, via structural equation modeling" class="work-thumbnail" src="https://attachments.academia-assets.com/71004371/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/54833638/An_exploration_of_colorectal_cancer_incidence_rates_in_North_Dakota_USA_via_structural_equation_modeling">An exploration of colorectal cancer incidence rates in North Dakota, USA, via structural equation modeling</a></div><div class="wp-workCard_item"><span>International Journal of Colorectal Disease</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Purpose The state of North Dakota has one of the highest incidence rates for colorectal cancer in...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Purpose The state of North Dakota has one of the highest incidence rates for colorectal cancer in the USA. Its high incidence rate, coupled with a large variation in incidence rates among counties within the state, makes North Dakota a "natural laboratory" in which to investigate environmental clues to colorectal cancer. We conducted a hypothesis-generating study to explore potential determinants of colorectal cancer in North Dakota. Methods We obtained county-specific incidence rates for North Dakota's 53 counties from the statewide cancer registry and corresponding data on county demographic, agricultural, and geophysical features from population-based sources. Candidate demographic/agricultural variables included median household income, population density, colorectal cancer screening rates, average farm size (in acres), and the percent of county fertilized. Geophysical variables included the uranium content of soil, residential radon levels, and source of drinking water (municipal or well water). Statistical analyses were performed via multivariate regression and structural equation modeling. Results Colorectal cancer incidence rates across North Dakota counties varied 3-fold. The structural equation model identified a significant role for well water use (p < 0.05). This finding is consistent with studies that implicate well water in colorectal cancer. Conclusions Well water contains several agents, e.g., bacteria, disinfection by-products, and nitrates that are potent colorectal carcinogens. Studies of well water use and colorectal cancer risk at the individual level in North Dakota are warranted.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="13e130e171fc68c8bac725bcf9ede170" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71004371,"asset_id":54833638,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71004371/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="54833638"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="54833638"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 54833638; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=54833638]").text(description); $(".js-view-count[data-work-id=54833638]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 54833638; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='54833638']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "13e130e171fc68c8bac725bcf9ede170" } } $('.js-work-strip[data-work-id=54833638]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":54833638,"title":"An exploration of colorectal cancer incidence rates in North Dakota, USA, via structural equation modeling","internal_url":"https://www.academia.edu/54833638/An_exploration_of_colorectal_cancer_incidence_rates_in_North_Dakota_USA_via_structural_equation_modeling","owner_id":138386,"coauthors_can_edit":true,"owner":{"id":138386,"first_name":"Bradley","middle_initials":null,"last_name":"Rundquist","page_name":"BradleyRundquist","domain_name":"und","created_at":"2010-02-26T04:13:55.837-08:00","display_name":"Bradley Rundquist","url":"https://und.academia.edu/BradleyRundquist"},"attachments":[{"id":71004371,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71004371/thumbnails/1.jpg","file_name":"s00384-019-03352-9.pdf","download_url":"https://www.academia.edu/attachments/71004371/download_file","bulk_download_file_name":"An_exploration_of_colorectal_cancer_inci.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71004371/s00384-019-03352-9-libre.pdf?1633205998=\u0026response-content-disposition=attachment%3B+filename%3DAn_exploration_of_colorectal_cancer_inci.pdf\u0026Expires=1740502953\u0026Signature=X6bCtL5qLvpvqVd0hUm6TKSgYda0cfUt6hucYt-0d3Ji4wmncXw8bZVSQuueRcgn-yvVwEH4B-qujeoeDkH18dVgtuVlmYIvCIB2Pteg8s-z3nKB6~J9ApZu9yZn~-inr2Ki4ztHQ7z6tefVaoDG-9CK05qRur5ydTD5dlStMtERmCPhuzx2CG4vYiWFK7Ujv4M1jbeCsp77u7SLDda4qReltFcrbyKU9Y3mOqi0aCAzBthLu6GTkOhVI69UfpkSjPhMOGQM8Kp6rahx-W300JmW1yKMQ63-YIVJLbhLvEgGgst2rP-jr2rwH1~0c9~YQSAKPS4980fwlQg7jvBw7g__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":71004372,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71004372/thumbnails/1.jpg","file_name":"s00384-019-03352-9.pdf","download_url":"https://www.academia.edu/attachments/71004372/download_file","bulk_download_file_name":"An_exploration_of_colorectal_cancer_inci.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71004372/s00384-019-03352-9-libre.pdf?1633205998=\u0026response-content-disposition=attachment%3B+filename%3DAn_exploration_of_colorectal_cancer_inci.pdf\u0026Expires=1740502953\u0026Signature=LshAvbM-q1PrsIYtzgge~DJ8imbmEijfRYDJEsy8mDQFU6aN-jE9-Ov2owgIy4b3PaKabVg24IAA6kEjvJ9060~V-ahLk0733MfPI~xWholMF4egtyHr78~uboQSKwwmqBL4gPrVJJj-Z5whDFfBitu1AtYI6CMST5nkpqZ7Uu5pC0J~0ouXGnJvvCcnkT7hhUqYQLbnfroNKIJ55ImAbvPt0I6DgrgMN4mIdZXpMBqqEvmYbP4uQRQd3FiLuBqCkArCRGimp2Km0F-YBCCWFp~edvhof-IPFUpf4JQzYtq8UHvm3yjHsfrMMmSQC45T36VHUF-tpuSa0iJTtL70DQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="54833635"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/54833635/Monitoring_Landscape_Dynamics_in_Central_U_S_Grasslands_with_Harmonized_Landsat_8_and_Sentinel_2_Time_Series_Data"><img alt="Research paper thumbnail of Monitoring Landscape Dynamics in Central U.S. Grasslands with Harmonized Landsat-8 and Sentinel-2 Time Series Data" class="work-thumbnail" src="https://attachments.academia-assets.com/71004376/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/54833635/Monitoring_Landscape_Dynamics_in_Central_U_S_Grasslands_with_Harmonized_Landsat_8_and_Sentinel_2_Time_Series_Data">Monitoring Landscape Dynamics in Central U.S. Grasslands with Harmonized Landsat-8 and Sentinel-2 Time Series Data</a></div><div class="wp-workCard_item"><span>Remote Sensing</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Remotely monitoring changes in central U.S. grasslands is challenging because these landscapes te...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Remotely monitoring changes in central U.S. grasslands is challenging because these landscapes tend to respond quickly to disturbances and changes in weather. Such dynamic responses influence nutrient cycling, greenhouse gas contributions, habitat availability for wildlife, and other ecosystem processes and services. Traditionally, coarse-resolution satellite data acquired at daily intervals have been used for monitoring. Recently, the harmonized Landsat-8 and Sentinel-2 (HLS) data increased the temporal frequency of the data. Here we investigated if the increased data frequency provided adequate observations to characterize highly dynamic grassland processes. We evaluated HLS data available for 2016 to (1) determine if data from Sentinel-2 contributed to an improvement in characterizing landscape processes over Landsat-8 data alone, and (2) quantify how observation frequency impacted results. Specifically, we investigated into estimating annual vegetation phenology, detecting burn ...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="a68d222c489275ebe3e002c08c6c9c2b" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71004376,"asset_id":54833635,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71004376/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="54833635"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="54833635"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 54833635; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=54833635]").text(description); $(".js-view-count[data-work-id=54833635]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 54833635; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='54833635']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "a68d222c489275ebe3e002c08c6c9c2b" } } $('.js-work-strip[data-work-id=54833635]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":54833635,"title":"Monitoring Landscape Dynamics in Central U.S. Grasslands with Harmonized Landsat-8 and Sentinel-2 Time Series Data","internal_url":"https://www.academia.edu/54833635/Monitoring_Landscape_Dynamics_in_Central_U_S_Grasslands_with_Harmonized_Landsat_8_and_Sentinel_2_Time_Series_Data","owner_id":138386,"coauthors_can_edit":true,"owner":{"id":138386,"first_name":"Bradley","middle_initials":null,"last_name":"Rundquist","page_name":"BradleyRundquist","domain_name":"und","created_at":"2010-02-26T04:13:55.837-08:00","display_name":"Bradley Rundquist","url":"https://und.academia.edu/BradleyRundquist"},"attachments":[{"id":71004376,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71004376/thumbnails/1.jpg","file_name":"pdf.pdf","download_url":"https://www.academia.edu/attachments/71004376/download_file","bulk_download_file_name":"Monitoring_Landscape_Dynamics_in_Central.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71004376/pdf-libre.pdf?1633206004=\u0026response-content-disposition=attachment%3B+filename%3DMonitoring_Landscape_Dynamics_in_Central.pdf\u0026Expires=1740502953\u0026Signature=FDLty33-dNAPfGAEoD1at7kzLEFcGZUfHqmOtliWAEHRWQx~FnNQ~AAWvXIWJdJteKhNlWBvkEJZskJ05xWH2tVlhj0o-sszFPN1eqM2zk6bNJt9--oTA~HkqWKWXrKZCHPGJquLRi60YOs1QLvkg1z1PhYkGXuellxGJae58m-Wf6icr4EqrUy~0NfPlRB8BoixcX~8n2qpPTMBM9O~w6u~9kmcVlSHKQhfQ~KckX6O07HMby0~fUtFblwuLKzjp712cpi11PqQYcQycr1FYWVI7DDA9ydwkO~r6i43~f3U~8NUtELuPBrqM3lgMiXLmf6uCuUXDjZAFX6XsnR8hA__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":71004378,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71004378/thumbnails/1.jpg","file_name":"pdf.pdf","download_url":"https://www.academia.edu/attachments/71004378/download_file","bulk_download_file_name":"Monitoring_Landscape_Dynamics_in_Central.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71004378/pdf-libre.pdf?1633206005=\u0026response-content-disposition=attachment%3B+filename%3DMonitoring_Landscape_Dynamics_in_Central.pdf\u0026Expires=1740502953\u0026Signature=BHMQ7fkGnocF--vPAB3GZ1v8tw6qR9hQmUUAUy61xDGBCQXj0lbsBT94GriXGpJM5uL83iqH8o1Pl4Qs5E4Vjh3UtEUq19z0m1pXOaJu8C7jGJeJO0boP6SfmesKFzbU1QGjiPbe3Xcs7qBW1VGCK419VA0Ukb1tppZ8WpnQI3MZJhGY59tnuh9NvY2cycpfB7pa3VAaQY4Q0Lf-fbullsGPRPia2s7I83VTJaV2ez4ORVCA2xvPEbnqPOTxH154yQ9WbalTe8ozDB7Bc16YxB8ivIk0NM6da1MXHnf0t54pdmr8GV~XLrUl62p4zE8LEFupd620rOEtJFf7pn21yw__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="54833634"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/54833634/Seasonal_home_ranges_and_habitat_selection_of_three_elk_Cervus_elaphus_herds_in_North_Dakota"><img alt="Research paper thumbnail of Seasonal home ranges and habitat selection of three elk (Cervus elaphus) herds in North Dakota" class="work-thumbnail" src="https://attachments.academia-assets.com/71004467/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/54833634/Seasonal_home_ranges_and_habitat_selection_of_three_elk_Cervus_elaphus_herds_in_North_Dakota">Seasonal home ranges and habitat selection of three elk (Cervus elaphus) herds in North Dakota</a></div><div class="wp-workCard_item"><span>PLOS ONE</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Changes in land use have resulted in range shifts of many wildlife species, including those enter...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Changes in land use have resulted in range shifts of many wildlife species, including those entering novel environments, resulting in the critical need to understand their spatial ecology to inform ecosystem effects and management decisions. Dispersing elk (Cervus elaphus) were colonizing areas of suitable habitat in the Northern Great Plains, USA, resulting in crop depredation complaints in these areas. Although state resource managers had little information on these elk herds, limited evidence suggested temporal movements into Canada. We collected and analyzed essential information on home range and habitat selection for 3 elk herds residing in North Dakota. We captured 5 adult female elk in each study area, affixed global positioning system collars, and monitored them for 1 year (2016-2017). We estimated diel period, seasonal, and hunting season home ranges using Brownian Bridge Movement Models for each individual. We analyzed habitat selection using multinomial logit models to test for differences in use of land classes, and for departures from proportionate use based on random sampling; our predictor variables included individual elk, diel period, and season. Home ranges differed between the 3 herds, seasons, and diel period; gun and winter season home ranges were both larger than in summer, as was night when compared with day. Female elk generally restricted themselves to cover during the day and entered open areas at night and during winter months. Our results also suggest that elk in our study areas tended to seek more cover, and in the case of our Turtle Mountain study area, some cross into Canada during gun season. Our study provides a better understanding of the spatial ecology of elk in the Northern Great Plains while highlighting the need for enhanced international cooperative management efforts.</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="d7c3999b85bd1f12cf769094ce81f30f" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71004467,"asset_id":54833634,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71004467/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="54833634"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="54833634"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 54833634; window.Academia.workViewCountsFetcher.queue(workId, function (count) { var description = window.$h.commaizeInt(count) + " " + window.$h.pluralize(count, 'View'); $(".js-view-count[data-work-id=54833634]").text(description); $(".js-view-count[data-work-id=54833634]").attr('title', description).tooltip(); }); });</script></span></span><span><span class="percentile-widget hidden"><span class="u-mr2x work-percentile"></span></span><script>$(function () { var workId = 54833634; window.Academia.workPercentilesFetcher.queue(workId, function (percentileText) { var container = $(".js-work-strip[data-work-id='54833634']"); container.find('.work-percentile').text(percentileText.charAt(0).toUpperCase() + percentileText.slice(1)); container.find('.percentile-widget').show(); container.find('.percentile-widget').removeClass('hidden'); }); });</script></span></div><div id="work-strip-premium-row-container"></div></div></div><script> require.config({ waitSeconds: 90 })(["https://a.academia-assets.com/assets/wow_profile-a9bf3a2bc8c89fa2a77156577594264ee8a0f214d74241bc0fcd3f69f8d107ac.js","https://a.academia-assets.com/assets/work_edit-ad038b8c047c1a8d4fa01b402d530ff93c45fee2137a149a4a5398bc8ad67560.js"], function() { // from javascript_helper.rb var dispatcherData = {} if (true){ window.WowProfile.dispatcher = window.WowProfile.dispatcher || _.clone(Backbone.Events); dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "d7c3999b85bd1f12cf769094ce81f30f" } } $('.js-work-strip[data-work-id=54833634]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":54833634,"title":"Seasonal home ranges and habitat selection of three elk (Cervus elaphus) herds in North Dakota","internal_url":"https://www.academia.edu/54833634/Seasonal_home_ranges_and_habitat_selection_of_three_elk_Cervus_elaphus_herds_in_North_Dakota","owner_id":138386,"coauthors_can_edit":true,"owner":{"id":138386,"first_name":"Bradley","middle_initials":null,"last_name":"Rundquist","page_name":"BradleyRundquist","domain_name":"und","created_at":"2010-02-26T04:13:55.837-08:00","display_name":"Bradley Rundquist","url":"https://und.academia.edu/BradleyRundquist"},"attachments":[{"id":71004467,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71004467/thumbnails/1.jpg","file_name":"viewcontent.pdf","download_url":"https://www.academia.edu/attachments/71004467/download_file","bulk_download_file_name":"Seasonal_home_ranges_and_habitat_selecti.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71004467/viewcontent-libre.pdf?1633205993=\u0026response-content-disposition=attachment%3B+filename%3DSeasonal_home_ranges_and_habitat_selecti.pdf\u0026Expires=1740502953\u0026Signature=PJ2II92NMUKwjJaez2epnqgzBqcAyHpzwFVRikOhYZ9vEiiJs7nbS8k8V4Ga-eOv9XfsIcHPMaEyahXGigJo4uDh9eXBE4eDwHRWbyLTo0NPXYTFeUpEKaR86JdO7QkWf5jQ-nGfmDFMpYuF3~yL559Bxn1smQ2TUb8J7p~Lg13tiSsuHd994TnkFPBwftjEAA~eKdzwWiqo1KEU7izeU7wguiNVb3CL3yFPw3Pf79cjit99ULcrNnoh0o45AYGwHRNnBva~9AQvlztMhXXy1iNmmf4qBRbrewgbivPgN9mGvX319Y-oO0gnZN61rNopvgtHurGGniX4BXDmrzxthQ__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); $(this).data('initialized', true); } }); $a.trackClickSource(".js-work-strip-work-link", "profile_work_strip") }); </script> <div class="js-work-strip profile--work_container" data-work-id="54833632"><div class="profile--work_thumbnail hidden-xs"><a class="js-work-strip-work-link" data-click-track="profile-work-strip-thumbnail" href="https://www.academia.edu/54833632/Detection_of_Shelterbelt_Density_Change_Using_Historic_APFO_and_NAIP_Aerial_Imagery"><img alt="Research paper thumbnail of Detection of Shelterbelt Density Change Using Historic APFO and NAIP Aerial Imagery" class="work-thumbnail" src="https://attachments.academia-assets.com/71004379/thumbnails/1.jpg" /></a></div><div class="wp-workCard wp-workCard_itemContainer"><div class="wp-workCard_item wp-workCard--title"><a class="js-work-strip-work-link text-gray-darker" data-click-track="profile-work-strip-title" href="https://www.academia.edu/54833632/Detection_of_Shelterbelt_Density_Change_Using_Historic_APFO_and_NAIP_Aerial_Imagery">Detection of Shelterbelt Density Change Using Historic APFO and NAIP Aerial Imagery</a></div><div class="wp-workCard_item"><span>Remote Sensing</span></div><div class="wp-workCard_item"><span class="js-work-more-abstract-truncated">Grand Forks County, North Dakota, boasts the highest concentration of shelterbelts in the World. ...</span><a class="js-work-more-abstract" data-broccoli-component="work_strip.more_abstract" data-click-track="profile-work-strip-more-abstract" href="javascript:;"><span> more </span><span><i class="fa fa-caret-down"></i></span></a><span class="js-work-more-abstract-untruncated hidden">Grand Forks County, North Dakota, boasts the highest concentration of shelterbelts in the World. As trees age and reach their lifespan limits, renovations should have taken place with new trees being planted. However, in recent years, the rate of tree removal is thought to exceed the rate of replanting, which can result in a net loss of shelterbelts. Through manual digitization and geographic object-based image analysis (GEOBIA), we mapped shelterbelt densities in the Grand Forks County using historical and contemporary aerial photography, and estimated actual changes in density over 54 years. Our results showed a doubling in shelterbelt densities from 1962 to 2014, with an increase of 6402 m2/km2 over the 52 years (or 123 m2/km2/year). From 2014 to 2016, we measured 1,040,178 m2 of shelterbelt areas removed from the county, creating a density loss of −157 m2/km2/year. The total change over two years was relatively small compared with that seen over the previous 52 years. However, t...</span></div><div class="wp-workCard_item wp-workCard--actions"><span class="work-strip-bookmark-button-container"></span><a id="d6520b71f4cb595cd74926a32c5b30d9" class="wp-workCard--action" rel="nofollow" data-click-track="profile-work-strip-download" data-download="{"attachment_id":71004379,"asset_id":54833632,"asset_type":"Work","button_location":"profile"}" href="https://www.academia.edu/attachments/71004379/download_file?s=profile"><span><i class="fa fa-arrow-down"></i></span><span>Download</span></a><span class="wp-workCard--action visible-if-viewed-by-owner inline-block" style="display: none;"><span class="js-profile-work-strip-edit-button-wrapper profile-work-strip-edit-button-wrapper" data-work-id="54833632"><a class="js-profile-work-strip-edit-button" tabindex="0"><span><i class="fa fa-pencil"></i></span><span>Edit</span></a></span></span></div><div class="wp-workCard_item wp-workCard--stats"><span><span><span class="js-view-count view-count u-mr2x" data-work-id="54833632"><i class="fa fa-spinner fa-spin"></i></span><script>$(function () { var workId = 54833632; 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dispatcherData = { dispatcher: window.WowProfile.dispatcher, downloadLinkId: "d6520b71f4cb595cd74926a32c5b30d9" } } $('.js-work-strip[data-work-id=54833632]').each(function() { if (!$(this).data('initialized')) { new WowProfile.WorkStripView({ el: this, workJSON: {"id":54833632,"title":"Detection of Shelterbelt Density Change Using Historic APFO and NAIP Aerial Imagery","internal_url":"https://www.academia.edu/54833632/Detection_of_Shelterbelt_Density_Change_Using_Historic_APFO_and_NAIP_Aerial_Imagery","owner_id":138386,"coauthors_can_edit":true,"owner":{"id":138386,"first_name":"Bradley","middle_initials":null,"last_name":"Rundquist","page_name":"BradleyRundquist","domain_name":"und","created_at":"2010-02-26T04:13:55.837-08:00","display_name":"Bradley Rundquist","url":"https://und.academia.edu/BradleyRundquist"},"attachments":[{"id":71004379,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71004379/thumbnails/1.jpg","file_name":"remotesensing-11-00218-v3.pdf","download_url":"https://www.academia.edu/attachments/71004379/download_file","bulk_download_file_name":"Detection_of_Shelterbelt_Density_Change.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71004379/remotesensing-11-00218-v3-libre.pdf?1633206005=\u0026response-content-disposition=attachment%3B+filename%3DDetection_of_Shelterbelt_Density_Change.pdf\u0026Expires=1740502953\u0026Signature=P~s54FGTLu3TMrALSWHp5yI3deC4q1QQ2ku2fRGprRGbh5LVR56Qj6hGnIcr5cDIXpIXZOmcQYRrsTnrig6NK4M8C0dxM9~nHg9vlN-t9Rs064kG9HSrbFwFZnWJJ4EFLyGxzkmzYcSvpmO946cQBjOq~8jH2XNh~RKD~Ek2GynPrS9vJXqQGRa1fPEpHVPVJ9Bj5MBlzFfu~Qap74cw6~ndP~NNqoMxbfu7TBg-ZLp14DsXiOWnknfSYOo9J1Gug6A7BFjWYMLEFaUuP-ulwq7F-xrwhqI8Jipolu9ydaWsGoaXmJf5g9czS3y8IK6wD2BGP8OgwPxSBCsnGBX-4Q__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"},{"id":71004380,"title":"","file_type":"pdf","scribd_thumbnail_url":"https://attachments.academia-assets.com/71004380/thumbnails/1.jpg","file_name":"remotesensing-11-00218-v3.pdf","download_url":"https://www.academia.edu/attachments/71004380/download_file","bulk_download_file_name":"Detection_of_Shelterbelt_Density_Change.pdf","bulk_download_url":"https://d1wqtxts1xzle7.cloudfront.net/71004380/remotesensing-11-00218-v3-libre.pdf?1633206005=\u0026response-content-disposition=attachment%3B+filename%3DDetection_of_Shelterbelt_Density_Change.pdf\u0026Expires=1740502953\u0026Signature=e7XuYyxUjvcP4MKHaReNPg8EL4dujxcnXP6nC-FXMSeL87kMVpJ9qItpZBY6wP1e7cdGv7KUlv4bf-iSxVyUX8ICV903crvdjTNKzQK6owszRAmnIkMWX199eMCcNYrKM2JIQ4h7FIKrnOxMy5kf8ZKTOSUgRqLvWsqyOFTeC82EUy6LThiIwxhXoVGT2B8Yv2pVtMXtHPY0cHsPz7K9u4~HtNXNHTCo6XtbWoHG4cdB9IfoflsDO29b5pFygLUFFo2Gqw3ii8pmB6cIjBylqhcgqqXSKLjwNCI2WjRXzK-fqCf~NlYgS1--c3BQsCRvZ8J5RcyhcqEJNDVGDaa54A__\u0026Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA"}]}, dispatcherData: dispatcherData }); 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