{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,31]],"date-time":"2026-01-31T09:35:43Z","timestamp":1769852143402,"version":"3.49.0"},"reference-count":30,"publisher":"MDPI AG","issue":"23","license":[{"start":{"date-parts":[[2023,12,4]],"date-time":"2023-12-04T00:00:00Z","timestamp":1701648000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Science and Technology Program of Qinghai Province of China","award":["2022-NK-136"],"award-info":[{"award-number":["2022-NK-136"]}]},{"name":"Science and Technology Program of Qinghai Province of China","award":["42071303"],"award-info":[{"award-number":["42071303"]}]},{"name":"Science and Technology Program of Qinghai Province of China","award":["41571369"],"award-info":[{"award-number":["41571369"]}]},{"name":"Science and Technology Program of Qinghai Province of China","award":["KZ202110028044"],"award-info":[{"award-number":["KZ202110028044"]}]},{"name":"National Natural Science Foundation of China","award":["2022-NK-136"],"award-info":[{"award-number":["2022-NK-136"]}]},{"name":"National Natural Science Foundation of China","award":["42071303"],"award-info":[{"award-number":["42071303"]}]},{"name":"National Natural Science Foundation of China","award":["41571369"],"award-info":[{"award-number":["41571369"]}]},{"name":"National Natural Science Foundation of China","award":["KZ202110028044"],"award-info":[{"award-number":["KZ202110028044"]}]},{"name":"Joint program of Beijing Municipal Education Commission and Beijing Municipal Natural Science Foundation of China","award":["2022-NK-136"],"award-info":[{"award-number":["2022-NK-136"]}]},{"name":"Joint program of Beijing Municipal Education Commission and Beijing Municipal Natural Science Foundation of China","award":["42071303"],"award-info":[{"award-number":["42071303"]}]},{"name":"Joint program of Beijing Municipal Education Commission and Beijing Municipal Natural Science Foundation of China","award":["41571369"],"award-info":[{"award-number":["41571369"]}]},{"name":"Joint program of Beijing Municipal Education Commission and Beijing Municipal Natural Science Foundation of China","award":["KZ202110028044"],"award-info":[{"award-number":["KZ202110028044"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Chlorophyll plays a critical role in assessing the photosynthetic capacity and health of grasslands. However, existing studies on the hyperspectral inversion of chlorophyll have mainly focused on field crops, leading to limited accuracy when applied to natural grasslands due to their complex canopy structures and species diversity. This study aims to address this challenge by extrapolating the measured leaf chlorophyll to the canopy level using the green vegetation coverage approach. Additionally, fractional-order derivative (FOD) methods are employed to enhance the sensitivity of hyperspectral data to chlorophyll. Several FOD spectral indices are developed to minimize interference from factors such as bare soil and hay, resulting in improved chlorophyll estimation accuracy. The study utilizes partial least squares regression (PLSR) and support vector machine regression (SVR) to construct inversion models based on full-band FOD, two-band FOD spectral indices, and their combination. Through comparative analysis, the optimal model for estimating grassland chlorophyll content is determined, yielding an R2 value of 0.808, RMSE value of 1.720, and RPD value of 2.347.<\/jats:p>","DOI":"10.3390\/rs15235623","type":"journal-article","created":{"date-parts":[[2023,12,4]],"date-time":"2023-12-04T07:59:31Z","timestamp":1701676771000},"page":"5623","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["Grassland Chlorophyll Content Estimation from Drone Hyperspectral Images Combined with Fractional-Order Derivative"],"prefix":"10.3390","volume":"15","author":[{"given":"Aiwu","family":"Zhang","sequence":"first","affiliation":[{"name":"Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing 100048, China"},{"name":"Engineering Research Center of Spatial Information Technology, Ministry of Education, Capital Normal University, Beijing 100048, China"}]},{"given":"Shengnan","family":"Yin","sequence":"additional","affiliation":[{"name":"Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing 100048, China"},{"name":"Engineering Research Center of Spatial Information Technology, Ministry of Education, Capital Normal University, Beijing 100048, China"}]},{"given":"Juan","family":"Wang","sequence":"additional","affiliation":[{"name":"Key Laboratory of 3D Information Acquisition and Application, Ministry of Education, Capital Normal University, Beijing 100048, China"},{"name":"Engineering Research Center of Spatial Information Technology, Ministry of Education, Capital Normal University, Beijing 100048, China"}]},{"given":"Nianpeng","family":"He","sequence":"additional","affiliation":[{"name":"Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Shatuo","family":"Chai","sequence":"additional","affiliation":[{"name":"Academy of Animal Science and Veterinary Medicine, Qinghai University, Xining 810016, China"}]},{"given":"Haiyang","family":"Pang","sequence":"additional","affiliation":[{"name":"School of Ecology, Resources and Environment, Dezhou University, Dezhou 253023, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,12,4]]},"reference":[{"key":"ref_1","first-page":"344","article-title":"Remote estimation of crop and grass chlorophyll and nitrogen content using red-edge bands on Sentinel-2 and -3","volume":"23","author":"Clevers","year":"2013","journal-title":"Int. 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