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{"work":{"id":9563468,"created_at":"2014-11-30T04:11:58.363-08:00","from_world_paper_id":null,"updated_at":"2024-11-14T22:48:37.745-08:00","_data":{"grobid_abstract":"Remote sensing phenology studies use data gathered by satellite sensors that measure wavelengths of light absorbed and reflected by green plants. Certain pigments in plant leaves strongly absorb wavelengths of visible (red) light. The leaves themselves strongly reflect wavelengths of near-infrared light, which is invisible to human eyes. As a plant canopy changes from early spring growth to late-season maturity and senescence, these reflectance properties also change.","grobid_abstract_attachment_id":"35780480"},"document_type":"paper","pre_hit_view_count_baseline":null,"quality":"low","language":"en","title":"NDVI","broadcastable":true,"draft":null,"has_indexable_attachment":true,"indexable":true}}["work"]; window.loswp.workCoauthors = [5556684]; 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.loswp.appleClientId = 'edu.academia.applesignon';</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 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class="ds-work-card--work-title">NDVI</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="5556684" href="https://juniv.academia.edu/SoniaNazneen"><img alt="Profile image of Sonia Nazneen" class="ds-work-card--author-avatar" src="https://0.academia-photos.com/5556684/2434528/12104241/s65_sonia.nazneen.jpg" />Sonia Nazneen</a></div><div class="ds-work-card--detail"><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">5 pages</p></div><div class="ds-work-card--work-metadata__stat"><span 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With the help of these indices, the difference of vegetational and other land covers can be contrasted and many useful and applicable data can be gathered ranging from vegetation health to growth dynamics among others. In recent decades, starting from the first Landsat satellite, a huge number of VIs were developed in order to be able to effectively monitor vegetation – the reason for the immense number is due to the fact that every sensor, topographic, geographic, vegetative and atmospheric feature is different, and more so are their combinations. This is the reason why there is no unified spectral band mathematical formula. The aim of this short overview is to provide the reader insight of the main vegetation indices (VIs) that have been used in scientific literature and their development over the last 40 years.</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="{"location":"wsj-grid-card-download-pdf-modal","work_title":"The Development of Vegetation Indices: a Short Overview","attachmentId":91746934,"attachmentType":"pdf","work_url":"https://www.academia.edu/87577235/The_Development_of_Vegetation_Indices_a_Short_Overview","alternativeTracking":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/87577235/The_Development_of_Vegetation_Indices_a_Short_Overview"><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="2367141" 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/2367141/Wide_Dynamic_Range_Vegetation_Index_for_Remote_Quantification_of_Biophysical_Characteristics_of_Vegetation">Wide Dynamic Range Vegetation Index for Remote Quantification of Biophysical Characteristics of Vegetation</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="3043244" href="https://independent.academia.edu/AnatolyGitelson">Anatoly Gitelson</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Journal of Plant Physiology, 2004</p><p class="ds-related-work--abstract ds2-5-body-sm">The Normalized Difference Vegetation Index (NDVI) is widely used for monitoring, analyzing, and mapping temporal and spatial distributions of physiological and biophysical characteristics of vegetation. It is well documented that the NDVI approaches saturation asymptotically under conditions of moderate-to-high aboveground biomass. While reflectance in the red region (ρred) exhibits a nearly flat response once the leaf area index (LAI) exceeds 2, the near infrared (NIR) reflectance (ρNIR) continue to respond significantly to changes in moderate-to-high vegetation density (LAI from 2 to 6) in crops. However, this higher sensitivity of the ρNIR has little effect on NDVI values once the ρNIR exceeds 30 %. In this paper a simple modification of the NDVI was proposed. The Wide Dynamic Range Vegetation Index, WDRVI = (a * ρNIR-ρred)/(a * ρNIR+ρred), where the weighting coefficient a has a value of 0.1–0.2, increases correlation with vegetation fraction by linearizing the relationship for typical wheat, soybean, and maize canopies. The sensitivity of the WDRVI to moderate-to-high LAI (between 2 and 6) was at least three times greater than that of the NDVI. By enhancing the dynamic range while using the same bands as the NDVI, the WDRVI enables a more robust characterization of crop physiological and phenological characteristics. Although this index needs further evaluation, the linear relationship with vegetation fraction and much higher sensitivity to change in LAI will be especially valuable for precision agriculture and monitoring vegetation status under conditions of moderate-to-high density. It is anticipated that the new index will complement the NDVI and other vegetation indices that are based on the red and NIR spectral bands.</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="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Wide Dynamic Range Vegetation Index for Remote Quantification of Biophysical Characteristics of Vegetation","attachmentId":50654491,"attachmentType":"pdf","work_url":"https://www.academia.edu/2367141/Wide_Dynamic_Range_Vegetation_Index_for_Remote_Quantification_of_Biophysical_Characteristics_of_Vegetation","alternativeTracking":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/2367141/Wide_Dynamic_Range_Vegetation_Index_for_Remote_Quantification_of_Biophysical_Characteristics_of_Vegetation"><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="122720360" 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/122720360/Vegetation_Index_greenness_global_data_set_White_Paper_for_NASA_ESDR_CDR_April_2006_">Vegetation Index greenness global data set White Paper for NASA ESDR/CDR (April 2006)</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="212358989" href="https://independent.academia.edu/ForrestHall4">Forrest Hall</a></div><p class="ds-related-work--metadata ds2-5-body-xs">2006</p><p class="ds-related-work--abstract ds2-5-body-sm">Vegetation Indices (VI) are optical measures of vegetation canopy ‘greenness’, a direct measure of photosynthetic potential resulting from the composite property of total leaf chlorophyll, leaf area, canopy cover, and structure. VI’s are widely used as proxies in estimating canopy state variables (leaf area index, fraction of absorbed photosynthetically-active radiation, chlorophyll content, vegetation fraction) and canopy biophysical processes (photosynthesis, transpiration, net primary production). 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class="ds-related-work--metadata ds2-5-body-xs">International Journal of Remote Sensing, 2010</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="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Characterizing vegetation indices derived from active and passive sensors","attachmentId":50956545,"attachmentType":"pdf","work_url":"https://www.academia.edu/29600304/Characterizing_vegetation_indices_derived_from_active_and_passive_sensors","alternativeTracking":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-related-work-grid-card-view-pdf" href="https://www.academia.edu/29600304/Characterizing_vegetation_indices_derived_from_active_and_passive_sensors"><span class="ds2-5-text-link__content">View PDF</span><span 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Clevers</a></div><p class="ds-related-work--metadata ds2-5-body-xs">Remote Sensing of Environment, 1989</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="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Application of a weighted infrared-red vegetation index for estimating leaf Area Index by Correcting for Soil Moisture","attachmentId":41914212,"attachmentType":"pdf","work_url":"https://www.academia.edu/21019868/Application_of_a_weighted_infrared_red_vegetation_index_for_estimating_leaf_Area_Index_by_Correcting_for_Soil_Moisture","alternativeTracking":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-related-work-grid-card-view-pdf" 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js-related-work-sidebar-card" data-collection-position="19" data-entity-id="108077509" data-sort-order="default"><a class="ds-related-work--title js-related-work-grid-card-title ds2-5-body-md ds2-5-body-link" href="https://www.academia.edu/108077509/Vegetation_Indices_Combining_the_Red_and_Red_Edge_Spectral_Information_for_Leaf_Area_Index_Retrieval">Vegetation Indices Combining the Red and Red-Edge Spectral Information for Leaf Area Index Retrieval</a><div class="ds-related-work--metadata"><a class="js-related-work-grid-card-author ds2-5-body-sm ds2-5-body-link" data-author-id="38545846" href="https://independent.academia.edu/GiovanniLaneve">Giovanni Laneve</a></div><p class="ds-related-work--metadata ds2-5-body-xs">IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018</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="{"location":"wsj-grid-card-download-pdf-modal","work_title":"Vegetation Indices Combining the Red and Red-Edge Spectral Information for Leaf Area Index Retrieval","attachmentId":106558554,"attachmentType":"pdf","work_url":"https://www.academia.edu/108077509/Vegetation_Indices_Combining_the_Red_and_Red_Edge_Spectral_Information_for_Leaf_Area_Index_Retrieval","alternativeTracking":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-related-work-grid-card-view-pdf" href="https://www.academia.edu/108077509/Vegetation_Indices_Combining_the_Red_and_Red_Edge_Spectral_Information_for_Leaf_Area_Index_Retrieval"><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 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