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(PDF) Monitoring and mapping of seasonal vegetation trend in Tamil Nadu using NDVI and NDWI imagery

<!DOCTYPE html> <html > <head> <meta charset="utf-8"> <meta rel="search" type="application/opensearchdescription+xml" href="/open_search.xml" title="Academia.edu"> <meta content="width=device-width, initial-scale=1" name="viewport"> <meta name="google-site-verification" content="bKJMBZA7E43xhDOopFZkssMMkBRjvYERV-NaN4R6mrs"> <meta name="csrf-param" content="authenticity_token" /> <meta name="csrf-token" content="m0xwCuEjZIDyiq6DugiKSk1HHCIf7mEmPrPCNCNh1_3jrf7IfSK3i75R0SQsW9_VYnqu2lTgZ6exf9Lt02j2lA" /> <meta name="citation_title" content="Monitoring and mapping of seasonal vegetation trend in Tamil Nadu using NDVI and NDWI imagery" /> <meta name="citation_publication_date" content="2019/01/01" /> <meta name="citation_journal_title" content="Journal of Applied and Natural Science" /> <meta name="citation_author" content="SHANMUGASUNDARAM K" /> <meta name="twitter:card" content="summary" /> <meta name="twitter:url" content="https://www.academia.edu/81792485/Monitoring_and_mapping_of_seasonal_vegetation_trend_in_Tamil_Nadu_using_NDVI_and_NDWI_imagery" /> <meta name="twitter:title" content="Monitoring and mapping of seasonal vegetation trend in Tamil Nadu using NDVI and NDWI imagery" /> <meta name="twitter:description" content="In order to monitor vegetation growth and development over the districts and land covers of Tamil Nadu, India during the crop growing season viz., Khairf and Rabi of 2017, Moderate Resolution Imaging Spectroradiometer (MODIS) derived surface" /> <meta name="twitter:image" content="http://a.academia-assets.com/images/twitter-card.jpeg" /> <meta property="fb:app_id" content="2369844204" /> <meta property="og:type" content="article" /> <meta property="og:url" content="https://www.academia.edu/81792485/Monitoring_and_mapping_of_seasonal_vegetation_trend_in_Tamil_Nadu_using_NDVI_and_NDWI_imagery" /> <meta property="og:title" content="Monitoring and mapping of seasonal vegetation trend in Tamil Nadu using NDVI and NDWI imagery" /> <meta property="og:image" content="http://a.academia-assets.com/images/open-graph-icons/fb-paper.gif" /> <meta property="og:description" content="In order to monitor vegetation growth and development over the districts and land covers of Tamil Nadu, India during the crop growing season viz., Khairf and Rabi of 2017, Moderate Resolution Imaging Spectroradiometer (MODIS) derived surface" /> <meta property="article:author" content="https://tnau.academia.edu/SHANMUGASUNDARAMK" /> <meta name="description" content="In order to monitor vegetation growth and development over the districts and land covers of Tamil Nadu, India during the crop growing season viz., Khairf and Rabi of 2017, Moderate Resolution Imaging Spectroradiometer (MODIS) derived surface" /> <title>(PDF) Monitoring and mapping of seasonal vegetation trend in Tamil Nadu using NDVI and NDWI imagery</title> <link rel="canonical" href="https://www.academia.edu/81792485/Monitoring_and_mapping_of_seasonal_vegetation_trend_in_Tamil_Nadu_using_NDVI_and_NDWI_imagery" /> <script async src="https://www.googletagmanager.com/gtag/js?id=G-5VKX33P2DS"></script> <script> window.dataLayer = window.dataLayer || []; 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The regression slope values derived from the trend analysis was utilized and the NDVI and NDWI seasonal trend showed majority of area in Tamil Nadu falling under positive trend during the Kharif season (86.52 per cent for NDVI and 90.29 per cent for NDWI). While irrespective of land cover classes, NDVI and NDWI during Kharif season showed a greater positive trend (greening) wit...","author":[{"@context":"https://schema.org","@type":"Person","name":"SHANMUGASUNDARAM K","url":"https://tnau.academia.edu/SHANMUGASUNDARAMK"}],"contributor":[],"dateCreated":"2022-06-18","datePublished":"2019-01-01","headline":"Monitoring and mapping of seasonal vegetation trend in Tamil Nadu using NDVI and NDWI imagery","image":"https://attachments.academia-assets.com/87713922/thumbnails/1.jpg","inLanguage":"en","keywords":["Environmental Science","Normalized Difference Vegetation Index"],"publication":"Journal of Applied and Natural Science","publisher":{"@context":"https://schema.org","@type":"Organization","name":"ANSF Publications"},"sourceOrganization":[{"@context":"https://schema.org","@type":"EducationalOrganization","name":"tnau"}],"thumbnailUrl":"https://attachments.academia-assets.com/87713922/thumbnails/1.jpg","url":"https://www.academia.edu/81792485/Monitoring_and_mapping_of_seasonal_vegetation_trend_in_Tamil_Nadu_using_NDVI_and_NDWI_imagery"}</script><style type="text/css">@media(max-width: 567px){:root{--token-mode: Rebrand;--dropshadow: 0 2px 4px 0 #22223340;--primary-brand: #0645b1;--error-dark: #b60000;--success-dark: #05b01c;--inactive-fill: #ebebee;--hover: #0c3b8d;--pressed: #082f75;--button-primary-fill-inactive: #ebebee;--button-primary-fill: #0645b1;--button-primary-text: #ffffff;--button-primary-fill-hover: #0c3b8d;--button-primary-fill-press: #082f75;--button-primary-icon: #ffffff;--button-primary-fill-inverse: #ffffff;--button-primary-text-inverse: #082f75;--button-primary-icon-inverse: #0645b1;--button-primary-fill-inverse-hover: 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window.loswp.shouldDetectTimezone = true; window.loswp.shouldShowBulkDownload = true; window.loswp.showSignupCaptcha = false window.loswp.willEdgeCache = false; window.loswp.work = {"work":{"id":81792485,"created_at":"2022-06-18T20:01:42.369-07:00","from_world_paper_id":208740111,"updated_at":"2022-06-24T20:31:02.815-07:00","_data":{"abstract":"In order to monitor vegetation growth and development over the districts and land covers of Tamil Nadu, India during the crop growing season viz., Khairf and Rabi of 2017, Moderate Resolution Imaging Spectroradiometer (MODIS) derived surface reflectance product (MOD09A1) which is available at 500 m resolution and 8-day temporal period was used to derive a time series based Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) for monitoring and mapping terrestrial vegetation trend analysis which showed areas in Tamil Nadu having vegetation greening and vegetation browning. The regression slope values derived from the trend analysis was utilized and the NDVI and NDWI seasonal trend showed majority of area in Tamil Nadu falling under positive trend during the Kharif season (86.52 per cent for NDVI and 90.29 per cent for NDWI). While irrespective of land cover classes, NDVI and NDWI during Kharif season showed a greater positive trend (greening) wit...","publisher":"ANSF Publications","publication_date":"2019,,","publication_name":"Journal of Applied and Natural Science"},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"high","language":"en","title":"Monitoring and mapping of seasonal vegetation trend in Tamil Nadu using NDVI and NDWI imagery","broadcastable":true,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [2296939]; window.loswp.locale = "en"; window.loswp.countryCode = "SG"; window.loswp.cwvAbTestBucket = ""; window.loswp.designVariant = "ds_vanilla"; window.loswp.fullPageMobileSutdModalVariant = "full_page_mobile_sutd_modal"; window.loswp.useOptimizedScribd4genScript = false; window.loginModal = {}; window.loginModal.appleClientId = 'edu.academia.applesignon'; window.userInChina = "false";</script><script defer="" src="https://accounts.google.com/gsi/client"></script><div class="ds-loswp-container"><div class="ds-work-card--grid-container"><div class="ds-work-card--container js-loswp-work-card"><div class="ds-work-card--cover"><div class="ds-work-cover--wrapper"><div class="ds-work-cover--container"><button class="ds-work-cover--clickable js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;swp-splash-paper-cover&quot;,&quot;attachmentId&quot;:87713922,&quot;attachmentType&quot;:&quot;pdf&quot;}"><img alt="First page of “Monitoring and mapping of seasonal vegetation trend in Tamil Nadu using NDVI and NDWI imagery”" class="ds-work-cover--cover-thumbnail" src="https://0.academia-photos.com/attachment_thumbnails/87713922/mini_magick20220618-15992-ydv791.png?1655607779" /><img alt="PDF Icon" class="ds-work-cover--file-icon" src="//a.academia-assets.com/images/single_work_splash/adobe_icon.svg" /><div class="ds-work-cover--hover-container"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span><p>Download Free PDF</p></div><div class="ds-work-cover--ribbon-container">Download Free PDF</div><div class="ds-work-cover--ribbon-triangle"></div></button></div></div></div><div class="ds-work-card--work-information"><h1 class="ds-work-card--work-title">Monitoring and mapping of seasonal vegetation trend in Tamil Nadu using NDVI and NDWI imagery</h1><div class="ds-work-card--work-authors ds-work-card--detail"><a class="ds-work-card--author js-wsj-grid-card-author ds2-5-body-md ds2-5-body-link" data-author-id="2296939" href="https://tnau.academia.edu/SHANMUGASUNDARAMK"><img alt="Profile image of SHANMUGASUNDARAM K" class="ds-work-card--author-avatar" src="//a.academia-assets.com/images/s65_no_pic.png" />SHANMUGASUNDARAM K</a></div><div class="ds-work-card--detail"><p class="ds-work-card--detail ds2-5-body-sm">2019, Journal of Applied and Natural Science</p><div class="ds-work-card--work-metadata"><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">visibility</span><p class="ds2-5-body-sm" id="work-metadata-view-count">…</p></div><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">description</span><p class="ds2-5-body-sm">8 pages</p></div><div class="ds-work-card--work-metadata__stat"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">link</span><p class="ds2-5-body-sm">1 file</p></div></div><script>(async () => { const workId = 81792485; 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if (!viewCountBody) { throw new Error('Failed to find work views element'); } viewCountBody.textContent = `${commaizedViewCount} views`; } catch (error) { // Remove the whole views element if there was some issue parsing. document.getElementById('work-metadata-view-count')?.parentNode?.remove(); throw new Error(`Failed to parse view count: ${viewCount}`, error); } }; // If the DOM is still loading, wait for it to be ready before updating the view count. if (document.readyState === "loading") { document.addEventListener('DOMContentLoaded', () => { updateViewCount(viewCount); }); // Otherwise, just update it immediately. } else { updateViewCount(viewCount); } })();</script></div><p class="ds-work-card--work-abstract ds-work-card--detail ds2-5-body-md">In order to monitor vegetation growth and development over the districts and land covers of Tamil Nadu, India during the crop growing season viz., Khairf and Rabi of 2017, Moderate Resolution Imaging Spectroradiometer (MODIS) derived surface reflectance product (MOD09A1) which is available at 500 m resolution and 8-day temporal period was used to derive a time series based Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) for monitoring and mapping terrestrial vegetation trend analysis which showed areas in Tamil Nadu having vegetation greening and vegetation browning. The regression slope values derived from the trend analysis was utilized and the NDVI and NDWI seasonal trend showed majority of area in Tamil Nadu falling under positive trend during the Kharif season (86.52 per cent for NDVI and 90.29 per cent for NDWI). While irrespective of land cover classes, NDVI and NDWI during Kharif season showed a greater positive trend (greening) wit...</p><div class="ds-work-card--button-container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;continue-reading-button--work-card&quot;,&quot;attachmentId&quot;:87713922,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;workUrl&quot;:&quot;https://www.academia.edu/81792485/Monitoring_and_mapping_of_seasonal_vegetation_trend_in_Tamil_Nadu_using_NDVI_and_NDWI_imagery&quot;}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;download-pdf-button--work-card&quot;,&quot;attachmentId&quot;:87713922,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;workUrl&quot;:&quot;https://www.academia.edu/81792485/Monitoring_and_mapping_of_seasonal_vegetation_trend_in_Tamil_Nadu_using_NDVI_and_NDWI_imagery&quot;}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div><div class="ds-signup-banner-trigger-container"><div class="ds-signup-banner-trigger ds-signup-banner-trigger-premium-marketing"></div></div><div class="ds-signup-banner ds-signup-banner-premium-marketing"><div id="ds-signup-banner-close-button"><button class="ds2-5-button ds2-5-button--secondary ds2-5-button--inverse"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">close</span></button></div><div class="premium-banner-content"><div class="left"><img src="//a.academia-assets.com/images/academia-logo-capital-white.svg" /><span>Get access to the world's latest research</span></div><div class="right"><div class="card free"><div class="header">Free</div><div class="feature-list"><div class="feature"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">check</span><span>Download one paper at a time</span></div><div class="feature"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">check</span><span>Save papers to bookmarks</span></div><div class="feature"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">check</span><span>Basic search</span></div></div><button class="ds2-5-button ds2-5-button--secondary ds2-5-button--small ds2-5-button--inverse ds2-5-button--full-width js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;premium-banner-desktop-free&quot;}">Sign up for free</button></div><div class="card premium"><div class="pill">Recommended</div><div class="header premium">Premium</div><div class="feature-list"><div class="feature"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">check</span><span>Get highly curated PDF packages</span></div><div class="feature"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">check</span><span>Track your impact with Mentions</span></div><div class="feature"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">check</span><span>Access advanced search filters</span></div><div class="feature"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">check</span><span>Support Academia’s mission</span></div><div class="feature"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">check</span><span>Create your personal website</span></div></div><button class="ds2-5-button ds2-5-button--small ds2-5-button--inverse ds2-5-button--full-width js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;premium-banner-desktop-upgrade&quot;,&quot;submitText&quot;:&quot;Try Premium for $1&quot;}">Try Premium for $1</button></div></div></div></div><script>(() => { // Set up signup banner show/hide behavior: // 1. 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Borana</a></div><p class="ds-related-work--metadata ds2-5-body-xs">ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</p><p class="ds-related-work--abstract ds2-5-body-sm">Arid region of India shows vast variation in climate and vegetation during last two decades. In order to analysis impact of monsoonal patterns on the vegetation indices of the arid zone, a three years (2015-2017) temporal series Moderate Resolution Image Spectrometer (MODIS) data for Pre &amp; Post Monsoon was used for computing Normalized Difference Vegetation Index (NDVI). The cloud-free NDVI time series data are used to study the relationship between the rainfall pattern and the vegetation changes in Jodhpur District. ENVI and ArcGIS image processing software are used to evaluate and monitor the vegetation for the pre-monsoon and postmonsoon seasons for three years. Enormous changes were observed during pre and post monsoon temporal analysis. This study shows that MODIS NDVI data is best suited for quick vegetation assessment in arid region.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;Modis Derived Ndvi Based Time Series Analysis of Vegetation in the Jodhpur Area&quot;,&quot;attachmentId&quot;:83162452,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/75365004/Modis_Derived_Ndvi_Based_Time_Series_Analysis_of_Vegetation_in_the_Jodhpur_Area&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/75365004/Modis_Derived_Ndvi_Based_Time_Series_Analysis_of_Vegetation_in_the_Jodhpur_Area"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="1" data-entity-id="109346549" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/109346549/Long_term_trend_analysis_of_vegetation_dynamics_over_Rajasthan_using_satellite_derived_enhanced_vegetation_index">Long term trend analysis of vegetation dynamics over Rajasthan using satellite derived enhanced vegetation index</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="11954383" href="https://independent.academia.edu/AmritaDaripa">Amrita Daripa</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Journal of Agrometeorology, 2023</p><p class="ds-related-work--abstract ds2-5-body-sm">Vegetation is considered as an important part of the terrestrial ecosystem and biosphere. It is a crucial component of soil-water-plant-atmospheric system, having a significant influence on hydrological and biogeochemical cycles, global energy budget and terrestrial carbon storage (Liu and Lei, 2015; Srivastava et al., 2021). It has a clear relationship with climate change so can be used as a proxy for environment, climate and hydrological studies (Zoran et al., 2016; Wu et al., 2017). Long term vegetation condition assessment is important to understand the ecosystem and its functions. Long term satellite derived remote sensing products provide valuable inputs for precise monitoring of vegetation dynamics and its relation with climate change (Chakraborty et al. 2018; Pan et al., 2018). Globally, various satellite time series products such as NOAA (AVHRR), SPOT (Vegetation), and TERRA/AQUA (MODIS) have been used for the detection of land cover change, natural resource monitoring, and assessment of vegetation condition for a region (Lunetta et al., 2006; Priyadarshi et al., 2018). Remote sensing-based vegetation indices precisely estimate crop phenology, vegetation condition, and net and gross primary productivity from red and near-infrared band reflectance (Piao et al., 2020). MODIS-derived vegetation indices with multiple spatial resolutions (250 m, 500 m, 1 km, and 0.05 Deg), are very useful in monitoring of vegetation dynamics and provide scope to understand the vegetation cover changes at regional and global scales. The enhanced vegetation index (EVI), one of the most significant vegetation index used for growth assessment of surface vegetation and is also one of the most important basic data in ecosystems research. The change in EVI is a crucial indicator of changes in the local environment and ecosystems (Sarkar and Kafatos, 2004; Cao et al., 2015). It can estimate biomass effectively under saturated conditions (Huete et al., 2002; Fraga et al., 2014). In addition, the EVI range is broader and more dynamic, allowing for the collection of more fluctuations than the NDVI because it takes into account the coefficient of resistance components that rectify the impact of aerosols.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;Long term trend analysis of vegetation dynamics over Rajasthan using satellite derived enhanced vegetation index&quot;,&quot;attachmentId&quot;:107499851,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/109346549/Long_term_trend_analysis_of_vegetation_dynamics_over_Rajasthan_using_satellite_derived_enhanced_vegetation_index&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/109346549/Long_term_trend_analysis_of_vegetation_dynamics_over_Rajasthan_using_satellite_derived_enhanced_vegetation_index"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="2" data-entity-id="47643947" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/47643947/10_Nilay_Nishant_and_Jeganathan_C_2012_Reliability_of_MODIS_and_GIMMS_vegetation_indices_for_extracting_phenological_information_of_natural_vegetation_in_India_National_Symposium_on_Space_Technology_for_Food_and_Environmental_Security_and_Annual_Conventions_of_Indian_Society_of_Remote_Sensin_">10. Nilay Nishant and Jeganathan, C.,(2012). Reliability of MODIS and GIMMS vegetation indices for extracting phenological information of natural vegetation in India. National Symposium on Space Technology for Food &amp; Environmental Security and Annual Conventions of Indian Society of Remote Sensin...</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="1298241" href="https://bitmesra.academia.edu/Jeganathanc">Jeganathan CHOCKALINGAM</a></div><p class="ds-related-work--abstract ds2-5-body-sm">Since 1972 satellite derived vegetation vigour has been successfully used for various environmental modeling. However, extraction of reliable annual growth information about natural vegetation (i.e., phenology) has been of recent interest due to the free availability of time-series satellite data and its usability for many global models. Interestingly, for extracting phenology information of natural vegetation in India only Medium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) data was used, so far. The authors were curious to use Moderate Resolution Imaging Spectroradiometer (MODIS) and Global Inventory Modelling and Mapping Studies (GIMMS) based products in extracting this phenology information about evergreen, semievergreen, moist deciduous and dry deciduous vegetation in India. For this study the cloud corrected time-series MODIS NDVI &amp; EVI from product MOD13C1 with 5.6 km spatial resolution with 16 day temporal resolution were used for the 12 year period (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011). GIMMS NDVI with 8km spatial resolution having 15 day temporal resolution were used for 6 year period (2000)(2001)(2002)(2003)(2004)(2005)(2006). These three differently derived vegetation indices were analysed at each year so as to extract and understand the reliable growth rhythm. It was found that for Evergreen vegetation type the annual growth rhythm derived using MODIS based NDVI and EVI showed a different pattern at inter and intra year level. The variation in NDVI from GIMMS was too oscillatory for most of the vegetation types. This study has revealed that GIMMS NDVI data is not at all usable for Phenological study especially in India. MODIS EVI is suitable than NDVI. Hence, care is needed before using these data sets for understanding atmospheric and vegetative interaction, biomass calculation or carbon studies, (</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;10. Nilay Nishant and Jeganathan, C.,(2012). Reliability of MODIS and GIMMS vegetation indices for extracting phenological information of natural vegetation in India. National Symposium on Space Technology for Food \u0026 Environmental Security and Annual Conventions of Indian Society of Remote Sensin...&quot;,&quot;attachmentId&quot;:66630535,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/47643947/10_Nilay_Nishant_and_Jeganathan_C_2012_Reliability_of_MODIS_and_GIMMS_vegetation_indices_for_extracting_phenological_information_of_natural_vegetation_in_India_National_Symposium_on_Space_Technology_for_Food_and_Environmental_Security_and_Annual_Conventions_of_Indian_Society_of_Remote_Sensin_&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/47643947/10_Nilay_Nishant_and_Jeganathan_C_2012_Reliability_of_MODIS_and_GIMMS_vegetation_indices_for_extracting_phenological_information_of_natural_vegetation_in_India_National_Symposium_on_Space_Technology_for_Food_and_Environmental_Security_and_Annual_Conventions_of_Indian_Society_of_Remote_Sensin_"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="3" data-entity-id="46897205" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/46897205/Spatio_Temporal_Changes_of_Vegetation_Cover_through_NDVI_a_case_study_of_Kolkata_Municipal_Corporation_KMC_West_Bengal">Spatio-Temporal Changes of Vegetation Cover through NDVI – a case study of Kolkata Municipal Corporation (KMC), West Bengal</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="15766973" href="https://chandernagorecollege.academia.edu/AshisSarkar">Ashis Sarkar</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Indian Journal of Spatial Science, Spring Issue, 12(1), 2021</p><p class="ds-related-work--abstract ds2-5-body-sm">On account of rapid urbanization, vegetation cover of the earth&#39;s surface has been declining day by day. To study the spatial and temporal changes of vegetation cover we can use remote sensing and geographic information system. The present study aims to analyze and detect the spatial and temporal changes of NDVI of Kolkata Municipal Corporation (KMC). The researcher used the Normalized Difference Vegetation Index (NDVI) to detect the spatio-temporal changes of the vegetation cover of the KMC from 1991 to 2011. It is computed by using the visible and near-infrared bands of the electromagnetic spectrum (EMS). For this, multi-spectral remote sensing data have been used. The results show that the city of Kolkata is experiencing a declining trend of green cover; it is more prevalent in the added area of the KMC, i.e. the area covered by Wards No.101 to 141.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;Spatio-Temporal Changes of Vegetation Cover through NDVI – a case study of Kolkata Municipal Corporation (KMC), West Bengal&quot;,&quot;attachmentId&quot;:66278108,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/46897205/Spatio_Temporal_Changes_of_Vegetation_Cover_through_NDVI_a_case_study_of_Kolkata_Municipal_Corporation_KMC_West_Bengal&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/46897205/Spatio_Temporal_Changes_of_Vegetation_Cover_through_NDVI_a_case_study_of_Kolkata_Municipal_Corporation_KMC_West_Bengal"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="4" data-entity-id="85323508" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/85323508/Assessing_seasonal_trends_and_variability_of_vegetation_growth_from_NDVI3g_MODIS_NDVI_and_EVI_over_South_Asia">Assessing seasonal trends and variability of vegetation growth from NDVI3g, MODIS NDVI and EVI over South Asia</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="216406841" href="https://iihs.academia.edu/MrinalSingha">Mrinal Singha</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Remote Sensing Letters, 2018</p><p class="ds-related-work--abstract ds2-5-body-sm">The characterization of vegetation dynamics over South Asia (SA) has been primarily conducted using satellite time series of Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (NDVI). However, various vegetation indices may show diverse trend patterns over the same area. This study analysed the consistency of the vegetation spatiotemporal trends from AVHRR version 3 NDVI (NDVI3g) with the Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI and Enhanced Vegetation Index (EVI) over SA during various seasons, assuming that MODIS products are of higher quality. Results showed that the spatiotemporal vegetation trends derived from the NDVI3g were analogous to both MODIS NDVI and EVI indicating greening over semi-arid regions where croplands dominate and browning over tropical/subtropical forest areas. Correlations among them were better during winter monsoon. Discrepancies occurred in tropical/subtropical densely vegetated (humid) and complex topographic areas specifically during summer monsoon (SM). This study improved the understanding of the heterogeneous vegetation trends over the vast complicated terrain of SA. It was revealed that NDVI3g is reliable to quantify vegetation trends over SA, however, calibration errors still could introduce biases during SM season.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;Assessing seasonal trends and variability of vegetation growth from NDVI3g, MODIS NDVI and EVI over South Asia&quot;,&quot;attachmentId&quot;:90054875,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/85323508/Assessing_seasonal_trends_and_variability_of_vegetation_growth_from_NDVI3g_MODIS_NDVI_and_EVI_over_South_Asia&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/85323508/Assessing_seasonal_trends_and_variability_of_vegetation_growth_from_NDVI3g_MODIS_NDVI_and_EVI_over_South_Asia"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="5" data-entity-id="18785273" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/18785273/EVALUATING_THE_NORMALIZED_DIFFERENCE_VEGETATION_INDEX_USING_LANDSAT_DATA_BY_ENVI_IN_SALEM_DISTRICT_TAMILNADU_INDIA">EVALUATING THE NORMALIZED DIFFERENCE VEGETATION INDEX USING LANDSAT DATA BY ENVI IN SALEM DISTRICT, TAMILNADU, INDIA</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="38863272" href="https://independent.academia.edu/AppliedGeologyGandhigram">Applied Geology Gandhigram</a></div><p class="ds-related-work--abstract ds2-5-body-sm">The present study provides the Normalized Difference Vegetation Index of the study area. The main aim of this study is to evaluate the vegetation index using Lands at image. NDVI map prepared by using ENVI Image processing software. The study area NDVI map gives the Maximum value of 0.7 and Minimum Value of-0.06. The result depicts following types of vegetation index like Water bodies, Barren and Rocks, Shrub and Grass land, Moderate Green, Very green area, dense forests, Temperature and Tropical Rainforests. The NDVI cover type of water bodies are very less at the same time the Barren areas, Rock surface, shrub and Grass land are mostly occupying the Eastern part of the study area. Remaining cover types are occupying the highly elevated areas.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;EVALUATING THE NORMALIZED DIFFERENCE VEGETATION INDEX USING LANDSAT DATA BY ENVI IN SALEM DISTRICT, TAMILNADU, INDIA&quot;,&quot;attachmentId&quot;:40253831,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/18785273/EVALUATING_THE_NORMALIZED_DIFFERENCE_VEGETATION_INDEX_USING_LANDSAT_DATA_BY_ENVI_IN_SALEM_DISTRICT_TAMILNADU_INDIA&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/18785273/EVALUATING_THE_NORMALIZED_DIFFERENCE_VEGETATION_INDEX_USING_LANDSAT_DATA_BY_ENVI_IN_SALEM_DISTRICT_TAMILNADU_INDIA"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="6" data-entity-id="35610185" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/35610185/Long_Term_Trend_of_Vegetation_in_Bundelkhand_Region_India_An_Assessment_Through_SPOT_VGT_NDVI_Datasets">Long-Term Trend of Vegetation in Bundelkhand Region (India): An Assessment Through SPOT-VGT NDVI Datasets</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="706685" href="https://bankurauniv.academia.edu/Kundu">Arnab Kundu</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Climate Change, Extreme Events and Disaster Risk Reduction, 2018</p><p class="ds-related-work--abstract ds2-5-body-sm">Vegetation cover is an important natural resource of the terrestrial ecosystem, and it has significant role in preserving the ecological balance in an area. Analyzing the dynamic pattern of vegetation cover and its trend can be a key to explain any unusual condition of the environment. Bundelkhand, located at the central part of India, has experienced recurrent drought events in last decade, and considering the devastating effects of drought in that region, the present study aims to explore the long-term trend of vegetation using geo-spatial technology. The remote sensing-based SPOT-VGT NDVI data were used to identify the changes in vegetation with time. The normalized difference vegetation index (NDVI) has proven to be a very powerful indicator of global vegetation productivity. In this study, we used linear regression model for evaluating the long-term trend of vegetation considering NDVI as dependable and time as independent variable. Our results showed that there is a varying pattern of vegetation trend and its response to rainfall.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;Long-Term Trend of Vegetation in Bundelkhand Region (India): An Assessment Through SPOT-VGT NDVI Datasets&quot;,&quot;attachmentId&quot;:55477932,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/35610185/Long_Term_Trend_of_Vegetation_in_Bundelkhand_Region_India_An_Assessment_Through_SPOT_VGT_NDVI_Datasets&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/35610185/Long_Term_Trend_of_Vegetation_in_Bundelkhand_Region_India_An_Assessment_Through_SPOT_VGT_NDVI_Datasets"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="7" data-entity-id="28613838" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/28613838/NORMALISED_DIFFERENCIATIVE_VEGETATION_INDEX_NDVI_ANALYSIS_IN_SOUTH_EAST_DRY_AGRO_CLIMATIC_ZONES_OF_KARNATAKA_USING_RS_AND_GIS_TECHNIQUES">NORMALISED DIFFERENCIATIVE VEGETATION INDEX (NDVI) ANALYSIS IN SOUTH-EAST DRY AGRO-CLIMATIC ZONES OF KARNATAKA USING RS AND GIS TECHNIQUES</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="39246530" href="https://independent.academia.edu/JournalIJAR">IJAR Indexing</a></div><p class="ds-related-work--abstract ds2-5-body-sm">NDVI shows normal range of -1 to 1, water, clouds and snow have negative values they reflect more red than IR radiation. Rocks and soils are shows values “Zero” values some reflecting the colour Red and IR radiation only green vegetation has positive and high NDVI values. NDVI change values were extracted for the same pixels that were used for calibration. NDVI Values ranges between -0.33 to 0.03 Water Bodies, 0.03 to 0.19 Non Vegetation, 0.19 to 0.27 Low vegetation , 0.27 to 0.38 Medium Vegetation and 0.38 to 0.77 Dense Vegetation.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;NORMALISED DIFFERENCIATIVE VEGETATION INDEX (NDVI) ANALYSIS IN SOUTH-EAST DRY AGRO-CLIMATIC ZONES OF KARNATAKA USING RS AND GIS TECHNIQUES&quot;,&quot;attachmentId&quot;:48977988,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/28613838/NORMALISED_DIFFERENCIATIVE_VEGETATION_INDEX_NDVI_ANALYSIS_IN_SOUTH_EAST_DRY_AGRO_CLIMATIC_ZONES_OF_KARNATAKA_USING_RS_AND_GIS_TECHNIQUES&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/28613838/NORMALISED_DIFFERENCIATIVE_VEGETATION_INDEX_NDVI_ANALYSIS_IN_SOUTH_EAST_DRY_AGRO_CLIMATIC_ZONES_OF_KARNATAKA_USING_RS_AND_GIS_TECHNIQUES"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="8" data-entity-id="1472455" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/1472455/Mapping_the_phenology_of_natural_vegetation_in_India_using_remote_sensing_derived_chlorophyll_index">Mapping the phenology of natural vegetation in India using remote sensing derived chlorophyll index</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="1298241" href="https://bitmesra.academia.edu/Jeganathanc">Jeganathan CHOCKALINGAM</a></div><p class="ds-related-work--abstract ds2-5-body-sm">Time series of MEdium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) level-3 data product, with a spatial resolution of ∼4.6 km composited at 8-day intervals for the years 2003 to 2007, were used to map the phenology of natural vegetation in India. Initial dropouts and noise in the MTCI data were corrected using a temporal moving window filter, Fourier-based smoothing using the first four harmonics was applied and then the phenological variables were extracted through a temporal iterative search of peaks and valleys in the time series for each pixel. The approach was fine-tuned to extract reliable phenological variables from the complex and multiple phenology cycles. A global land cover map (GLC2000) was used as a reference to extract the spatial locations of the vegetation types to infer their phenology. The median of each phenological variable was derived and a spatial majority filter was applied to the 1° 1° grids (representing 1:250 000 Survey of India toposheet) covering the whole of India. This study presents the results derived for the evergreen, semi-evergreen, moist deciduous and dry deciduous vegetation types of India. A general trend of earlier onset of greenness at lower latitudes than at higher latitudes was observed for the natural vegetation in India.</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;Mapping the phenology of natural vegetation in India using remote sensing derived chlorophyll index&quot;,&quot;attachmentId&quot;:31383168,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/1472455/Mapping_the_phenology_of_natural_vegetation_in_India_using_remote_sensing_derived_chlorophyll_index&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/1472455/Mapping_the_phenology_of_natural_vegetation_in_India_using_remote_sensing_derived_chlorophyll_index"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div><div class="ds-related-work--container js-wsj-grid-card" data-collection-position="9" data-entity-id="65497735" data-sort-order="default"><a class="ds-related-work--title js-wsj-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/65497735/Evaluation_of_Vegetation_Indices_and_Phenological_Metrics_Using_Time_Series_MODIS_Data_for_Monitoring_Vegetation_Change_in_Punjab_Pakistan">Evaluation of Vegetation Indices and Phenological Metrics Using Time-Series MODIS Data for Monitoring Vegetation Change in Punjab, Pakistan</a><div class="ds-related-work--metadata"><a class="js-wsj-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="27280392" href="https://msstate.academia.edu/DrAqilTariq">Dr. Aqil Tariq</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Water</p><p class="ds-related-work--abstract ds2-5-body-sm">In arid and semi-arid regions, it is essential to monitor the spatiotemporal variability and dynamics of vegetation. Among other provinces of Pakistan, Punjab has produced a significant number of crops. Recently, Punjab, Pakistan, has been described as a global hotspot for extremes of climate change. In this study, the soil adjusted vegetation index (SAVI), normalized vegetation difference index (NDVI), and enhanced vegetation index (EVI) were comprehensively evaluated to monitor vegetation change in Punjab, Pakistan. The time-series MODIS (Moderate Resolution Imaging Spectroradiometer) data of different periods were used. The mean annual variability of the above vegetation indices (VIs) from 2000 to 2019 was evaluated and analyzed. For each type of vegetation, two phenological metrics (i.e., for the start of the season and end of the season) were calculated and compared. The spatio-temporal image analysis of the mean annual vegetation indices revealed similar patterns and varying v...</p><div class="ds-related-work--ctas"><button class="ds2-5-text-link ds2-5-text-link--inline js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;wsj-grid-card-download-pdf-modal&quot;,&quot;work_title&quot;:&quot;Evaluation of Vegetation Indices and Phenological Metrics Using Time-Series MODIS Data for Monitoring Vegetation Change in Punjab, Pakistan&quot;,&quot;attachmentId&quot;:77067743,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;work_url&quot;:&quot;https://www.academia.edu/65497735/Evaluation_of_Vegetation_Indices_and_Phenological_Metrics_Using_Time_Series_MODIS_Data_for_Monitoring_Vegetation_Change_in_Punjab_Pakistan&quot;,&quot;alternativeTracking&quot;:true}"><span class="material-symbols-outlined" style="font-size: 18px" translate="no">download</span><span class="ds2-5-text-link__content">Download free PDF</span></button><a class="ds2-5-text-link ds2-5-text-link--inline js-wsj-grid-card-view-pdf" href="https://www.academia.edu/65497735/Evaluation_of_Vegetation_Indices_and_Phenological_Metrics_Using_Time_Series_MODIS_Data_for_Monitoring_Vegetation_Change_in_Punjab_Pakistan"><span class="ds2-5-text-link__content">View PDF</span><span class="material-symbols-outlined" style="font-size: 18px" translate="no">chevron_right</span></a></div></div></div></div><div class="ds-sticky-ctas--wrapper js-loswp-sticky-ctas hidden"><div class="ds-sticky-ctas--grid-container"><div class="ds-sticky-ctas--container"><button class="ds2-5-button js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;continue-reading-button--sticky-ctas&quot;,&quot;attachmentId&quot;:87713922,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;workUrl&quot;:null}">See full PDF</button><button class="ds2-5-button ds2-5-button--secondary js-swp-download-button" data-signup-modal="{&quot;location&quot;:&quot;download-pdf-button--sticky-ctas&quot;,&quot;attachmentId&quot;:87713922,&quot;attachmentType&quot;:&quot;pdf&quot;,&quot;workUrl&quot;:null}"><span class="material-symbols-outlined" style="font-size: 20px" translate="no">download</span>Download PDF</button></div></div></div><div class="ds-below-fold--grid-container"><div class="ds-work--container js-loswp-embedded-document"><div class="attachment_preview" data-attachment="Attachment_87713922" style="display: none"><div class="js-scribd-document-container"><div class="scribd--document-loading js-scribd-document-loader" style="display: block;"><img alt="Loading..." src="//a.academia-assets.com/images/loaders/paper-load.gif" /><p>Loading Preview</p></div></div><div style="text-align: center;"><div class="scribd--no-preview-alert js-preview-unavailable"><p>Sorry, preview is currently unavailable. 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