文献类型：期刊文献

英文题名：Estimating wheat biomass from GF-3 data and a polarized water cloud model

作者：Han, Dong[1,2] Yang, Hao[2] Qiu, Chunxia[1] Yang, Guijun[2] Chen, Erxue[3] Du, Ying[2] Yang, Wenpan[2] Zhou, Chengquan[2]

第一作者：Han, Dong

通信作者：Yang, H[1]|[a0005392d041eabde44eb]杨浩;

机构：[1]Xian Univ Sci & Technol, Coll Geomat, Xian, Shaanxi, Peoples R China;[2]Minist Agr China, Beijing Res Ctr Informat Technol Agr, Key Lab Quantitat Remote Sensing Agr, Beijing, Peoples R China;[3]Chinese Acad Forestry, Inst Forest Resources Informat Tech, Beijing, Peoples R China

年份：2019

卷号：10

期号：3

起止页码：234-243

外文期刊名：REMOTE SENSING LETTERS

收录：;EI(收录号：20192507061060);Scopus(收录号：2-s2.0-85067225906);WOS:【SCI-EXPANDED(收录号:WOS:000451514500001)】；

基金：This research was funded by National Natural Science Foundation of China (61661136003), National Key Research and Development Program of China (2016YFD0300602), and 03-Y20A11-9001-15/16.

语种：英文

外文关键词：Agricultural robots - Biomass - Cloud computing - Mean square error - Remote sensing - Soil moisture - Synthetic aperture radar

摘要：Wheat is one of the staple crops of the world. With the wide application of remote-sensing methods in agriculture, the use of data from synthetic aperture radar has attracted increasing attention for monitoring wheat growth. Most of previous studies estimated wheat biomass based on a water cloud model (WCM). However, when no data are available on soil moisture content, the applicability of such models is greatly reduced because of insufficient parameters. Thus, this study proposed a new polarized water cloud model (PWCM) called APWCM, which is a physical model and no auxiliary ground data was needed including soil moisture data. APWCM and WCM model was compared to estimate the above ground biomass of wheat in two different study areas. The results revealed that the WCM has a slightly lower root mean squared error (RMSE = 131.63 g m(-2), and 645.17 g m(-2)) in two different study areas. However, the APWCM has lower relative error (RE = 17.91%, and 13.53%) for wheat biomass estimation in areas with higher biomsass. The final result indicates that the APWCM can replace the WCM for estimating wheat biomass based on Gaofen-3 (GF-3) data when soil-moisture data are not available.