{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T03:51:29Z","timestamp":1769917889493,"version":"3.49.0"},"reference-count":47,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T00:00:00Z","timestamp":1685318400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Zhejiang Provincial Key Science and Technology Project","award":["2018C02013"],"award-info":[{"award-number":["2018C02013"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Forest growing stock volume (GSV, m3\/ha) is an indispensable variable for forest resources supervision. Precise measurement of GSV is conducive to monitoring forest dynamics. Nevertheless, little research has explored the pattern pixel values and the function of texture features derived from a vegetation index (VI) for GSV prediction. In this study, we investigated combining linear regression or Random Forest with Sentinel-2 spectral predictors and image textures derived from spectral bands and vegetation indices, which were based on standard deviation values or mean values at the plot level, for predicting GSV of Masson pine, theropencedrymion and all the survey plots in Anji County, China. Specifically, ten groups of experiments encompassing combinations of spectral parameters and texture measures were established for detecting the potential of image textures based on two different image pixel statistics. The results showed that texture measures derived from VI were superior to spectral parameters or texture measures derived from spectral bands for estimating the GSV of single tree species. Moreover, texture features based on shortwave infrared bands or their related VI and the standard deviation at pixel level for spectral bands\/indices were emphasized. Finally, the mean value at the plot level exhibited slightly stronger potential than the standard deviation in general.<\/jats:p>","DOI":"10.3390\/rs15112821","type":"journal-article","created":{"date-parts":[[2023,5,30]],"date-time":"2023-05-30T02:04:21Z","timestamp":1685412261000},"page":"2821","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Texture Features Derived from Sentinel-2 Vegetation Indices for Estimating and Mapping Forest Growing Stock Volume"],"prefix":"10.3390","volume":"15","author":[{"given":"Gengsheng","family":"Fang","sequence":"first","affiliation":[{"name":"College of Mathematics and Computer Science, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Key Laboratory of Forestry Intelligent Monitoring and Information Technology Research of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China"}]},{"given":"Xiaobing","family":"He","sequence":"additional","affiliation":[{"name":"Baishanzu Scientific Research Monitoring Center, Qianjiangyuan-Baishanzu National Park, Lishui 323000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2554-1028","authenticated-orcid":false,"given":"Yuhui","family":"Weng","sequence":"additional","affiliation":[{"name":"College of Forestry and Agriculture, Stephen F. Austin State University, Nacogdoches, TX 75962, USA"}]},{"given":"Luming","family":"Fang","sequence":"additional","affiliation":[{"name":"College of Mathematics and Computer Science, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Key Laboratory of Forestry Intelligent Monitoring and Information Technology Research of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,29]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1016\/j.rse.2010.09.018","article-title":"Retrieval of growing stock volume in boreal forest using hyper-temporal series of Envisat ASAR ScanSAR backscatter measurements","volume":"115","author":"Santoro","year":"2011","journal-title":"Remote Sens. 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