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Mapping paddy rice by the object-based random forest method using time series Sentinel-1/Sentinel-2 data

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成果类型:
期刊论文
作者:
Cai, Yaotong;Lin, Hui;Zhang, Meng*
通讯作者:
Zhang, Meng
作者机构:
[Zhang, Meng] Cent South Univ Forestry & Technol, Res Ctr Forestry Remote Sensing & Informat Engn, Changsha 410004, Hunan, Peoples R China.
Key Lab Forestry Remote Sensing Based Big Data &, Changsha 410004, Hunan, Peoples R China.
State Forestry Adm Forest Resources Management &, Key Lab, Changsha 410004, Hunan, Peoples R China.
通讯机构:
[Zhang, Meng] C
Cent South Univ Forestry & Technol, Res Ctr Forestry Remote Sensing & Informat Engn, Changsha 410004, Hunan, Peoples R China.
语种:
英文
关键词:
Object-based;Paddy rice;RASTFM;Sentinel-1;Sentinel-2;Time series
期刊:
Advances in Space Research
ISSN:
0273-1177
年:
2019
卷:
64
期:
11
页码:
2233-2244
基金类别:
The authors would like to thank the editors and anonymous reviewers for the valuable comments, which are significant for improving this manuscript. This Work was supported in part by the National Natural Science Foundation of China ( 41901385 ), and in part by the China Postdoctoral Science Foundation ( 2019M652815 ).
机构署名:
本校为第一且通讯机构
院系归属:
林学院
摘要:
Rice is one of the world's major staple foods, especially in China. In this study, we proposed an object-based random forest (RF) method for paddy rice mapping using time series Sentinel-1 and Sentinel-2 data. Firstly, the Robust Adaptive Spatial Temporal Fusion Model (RASTFM) was used to blend MODIS and Sentinel-2 data for achieving multi-temporal Sentinel-2 data. Subsequently, the Savitzky-Golay filter (S-G) was applied to smooth the time series Sentinel-2 NDVI data. And the phenological parameters were derived from the filtered time series N...

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