{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T08:58:21Z","timestamp":1776329901121,"version":"3.50.1"},"reference-count":56,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2022,6,24]],"date-time":"2022-06-24T00:00:00Z","timestamp":1656028800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41971328"],"award-info":[{"award-number":["41971328"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2022YFS0490"],"award-info":[{"award-number":["2022YFS0490"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["TD-XYDXX-006"],"award-info":[{"award-number":["TD-XYDXX-006"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Science and Technology Program Project Funds of Sichuan Province","award":["41971328"],"award-info":[{"award-number":["41971328"]}]},{"name":"the Science and Technology Program Project Funds of Sichuan Province","award":["2022YFS0490"],"award-info":[{"award-number":["2022YFS0490"]}]},{"name":"the Science and Technology Program Project Funds of Sichuan Province","award":["TD-XYDXX-006"],"award-info":[{"award-number":["TD-XYDXX-006"]}]},{"name":"the Six Talent Peaks Program of Jiangsu Province","award":["41971328"],"award-info":[{"award-number":["41971328"]}]},{"name":"the Six Talent Peaks Program of Jiangsu Province","award":["2022YFS0490"],"award-info":[{"award-number":["2022YFS0490"]}]},{"name":"the Six Talent Peaks Program of Jiangsu Province","award":["TD-XYDXX-006"],"award-info":[{"award-number":["TD-XYDXX-006"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Even though research has shown that the spectral parameters of yellow-edge, red-edge and NIR (near-infrared) shoulder wavelength regions are able to estimate green cover and leaf area index (LAI), a large amount of dead materials in grasslands challenges the accuracy of their estimation using hyperspectral remote sensing. However, the exact impact of dead vegetation cover on these spectral parameters remains unclear. Therefore, we evaluated the influences of dead materials on the spectral parameters in the wavelength regions of yellow-edge, red-edge and NIR shoulder by comparing normalized difference vegetation indices (NDVI) including the common red valley at 670 nm and NDVI using the red valley extracted by a new statistical method. This method, based on the concept of segmented linear regression, was developed to extract the spectral parameters and calculate NDVI automatically from the hyper-spectra. To fully understand the impact of dead cover on the spectral parameters (i.e., consider full coverage combinations of green vegetation, dead materials and bare soil), both in situ measured and simulated hyper-spectra were analyzed. The impact of dead cover on LAI estimation by those spectral parameters and NDVI were also evaluated. The results show that: (i) without considering the influence of bare soil, dead materials decreases the slope of red-edge, the slope of NIR shoulder and NDVI, while dead materials increases the slope of yellow-edge; (ii) the spectral characteristics of red valley disappear when dead cover exceeds 67%; (iii) large amount of dead materials also result in a blue shift of the red-edge position; (iv) accurate extraction of the red valley position enhances LAI estimation and reduces the influences of dead materials using hyperspectral NDVI; (v) the accuracy of LAI estimation using the slope of yellow-edge, the slope of red-edge, red-edge position and NDVI significantly drops when dead cover exceeds 72.3\u201374.5% (variation among indices).<\/jats:p>","DOI":"10.3390\/rs14133031","type":"journal-article","created":{"date-parts":[[2022,6,26]],"date-time":"2022-06-26T22:50:23Z","timestamp":1656283823000},"page":"3031","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["The Impact of NPV on the Spectral Parameters in the Yellow-Edge, Red-Edge and NIR Shoulder Wavelength Regions in Grasslands"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0033-2262","authenticated-orcid":false,"given":"Dandan","family":"Xu","sequence":"first","affiliation":[{"name":"Department of Ecology, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China"}]},{"given":"Yanqing","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Ecology, College of Biology and the Environment, Nanjing Forestry University, Nanjing 210037, China"}]},{"given":"Weixin","family":"Xu","sequence":"additional","affiliation":[{"name":"College of Resource and Environment, Chengdu University of Information and Technology, Chengdu 610225, China"}]},{"given":"Xulin","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Geography and Planning, University of Saskatchewan, 117 Science Place, Saskatoon, SK S7N 5C8, Canada"}]}],"member":"1968","published-online":{"date-parts":[[2022,6,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.rse.2013.11.017","article-title":"Measuring the dead component of mixed grassland with Landsat imagery","volume":"142","author":"Xu","year":"2014","journal-title":"Remote Sens. 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