{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,17]],"date-time":"2026-06-17T17:08:31Z","timestamp":1781716111811,"version":"3.54.5"},"reference-count":48,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,5,4]],"date-time":"2021-05-04T00:00:00Z","timestamp":1620086400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"GDAS' Project of Science and Technology Development","award":["2020GDASYL-20200103011"],"award-info":[{"award-number":["2020GDASYL-20200103011"]}]},{"name":"Guangdong Province Agricultural Science and Technology Innovation and Promotion Projec","award":["No.2020KJ102"],"award-info":[{"award-number":["No.2020KJ102"]}]},{"name":"Guangzhou Basic Research Project","award":["202002020076"],"award-info":[{"award-number":["202002020076"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Radiation transform models such as PROSAIL are widely used for crop canopy reflectance simulation and biophysical parameter inversion. The PROSAIL model basically assumes that the canopy is turbid homogenous media with a bare soil background. However, the canopy structure changes when crop growth stages develop, which is more or less a departure from this assumption. In addition, a paddy rice field is inundated most of the time with flooded soil background. In this study, field-scale paddy rice leaf area index (LAI), leaf cholorphyll content (LCC), and canopy chlorophyll content (CCC) were retrieved from unmanned-aerial-vehicle-based hyperspectral images by the PROSAIL radiation transform model using a lookup table (LUT) strategy, with a special focus on the effects of growth-stage development and soil-background signature selection. Results show that involving flooded soil reflectance as background reflectance for PROSAIL could improve estimation accuracy. When using a LUT with the flooded soil reflectance signature (LUTflooded) the coefficients of determination (R2) between observed and estimation variables are 0.70, 0.11, and 0.79 for LAI, LCC, and CCC, respectively, for the entire growing season (from tillering to heading growth stages), and the corresponding mean absolute errors (MAEs) are 21.87%, 16.27%, and 12.52%. For LAI and LCC, high model bias mainly occurred in tillering growth stages. There is an obvious overestimation of LAI and underestimation of LCC for in the tillering growth stage. The estimation accuracy of CCC is relatively consistent from tillering to heading growth stages.<\/jats:p>","DOI":"10.3390\/rs13091792","type":"journal-article","created":{"date-parts":[[2021,5,5]],"date-time":"2021-05-05T22:51:42Z","timestamp":1620255102000},"page":"1792","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["Phenology Effects on Physically Based Estimation of Paddy Rice Canopy Traits from UAV Hyperspectral Imagery"],"prefix":"10.3390","volume":"13","author":[{"given":"Li","family":"Wang","sequence":"first","affiliation":[{"name":"Research Center of Guangdong Province for Engineering Technology Application of Remote Sensing Big Data, Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1204-9624","authenticated-orcid":false,"given":"Shuisen","family":"Chen","sequence":"additional","affiliation":[{"name":"Research Center of Guangdong Province for Engineering Technology Application of Remote Sensing Big Data, Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiping","family":"Peng","sequence":"additional","affiliation":[{"name":"Institute of Agricultural Resources and Environment, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jichuan","family":"Huang","sequence":"additional","affiliation":[{"name":"Institute of Agricultural Resources and Environment, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8495-1262","authenticated-orcid":false,"given":"Chongyang","family":"Wang","sequence":"additional","affiliation":[{"name":"Research Center of Guangdong Province for Engineering Technology Application of Remote Sensing Big Data, Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5122-0412","authenticated-orcid":false,"given":"Hao","family":"Jiang","sequence":"additional","affiliation":[{"name":"Research Center of Guangdong Province for Engineering Technology Application of Remote Sensing Big Data, Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qiong","family":"Zheng","sequence":"additional","affiliation":[{"name":"Research Center of Guangdong Province for Engineering Technology Application of Remote Sensing Big Data, Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Li","sequence":"additional","affiliation":[{"name":"Research Center of Guangdong Province for Engineering Technology Application of Remote Sensing Big Data, Key Lab of Guangdong for Utilization of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"111402","DOI":"10.1016\/j.rse.2019.111402","article-title":"Remote sensing for agricultural applications: A meta-review","volume":"236","author":"Weiss","year":"2020","journal-title":"Remote Sens. 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