Daily soil moisture mapping at 1 km resolution based on SMAP data for desertification areas in northern China
Pinzeng Rao,Yicheng Wang,Fang Wang,Yang Liu,Xiaoya Wang,and Zhu Wang
Pinzeng Rao
State Key Laboratory of Hydroscience and Engineering, Department of
Hydraulic Engineering, Tsinghua University, Beijing 100084, China
State Key Laboratory of Simulation and Regulation of Water Cycle in
River Basin, China Institute of Water Resources and Hydropower Research,
Beijing 100038, China
Yicheng Wang
State Key Laboratory of Simulation and Regulation of Water Cycle in
River Basin, China Institute of Water Resources and Hydropower Research,
Beijing 100038, China
State Key Laboratory of Simulation and Regulation of Water Cycle in
River Basin, China Institute of Water Resources and Hydropower Research,
Beijing 100038, China
Yang Liu
State Key Laboratory of Simulation and Regulation of Water Cycle in
River Basin, China Institute of Water Resources and Hydropower Research,
Beijing 100038, China
Xiaoya Wang
State Key Laboratory of Remote Sensing Science, Faculty of
Geographical Science, Beijing Normal University, Beijing 100875, China
Zhu Wang
State Key Laboratory of Simulation and Regulation of Water Cycle in
River Basin, China Institute of Water Resources and Hydropower Research,
Beijing 100038, China
Viewed
Total article views: 5,297 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
3,496
1,646
155
5,297
375
114
156
HTML: 3,496
PDF: 1,646
XML: 155
Total: 5,297
Supplement: 375
BibTeX: 114
EndNote: 156
Views and downloads (calculated since 07 Dec 2021)
Cumulative views and downloads
(calculated since 07 Dec 2021)
Total article views: 3,937 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
2,672
1,157
108
3,937
195
99
136
HTML: 2,672
PDF: 1,157
XML: 108
Total: 3,937
Supplement: 195
BibTeX: 99
EndNote: 136
Views and downloads (calculated since 06 Jul 2022)
Cumulative views and downloads
(calculated since 06 Jul 2022)
Total article views: 1,360 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
Supplement
BibTeX
EndNote
824
489
47
1,360
180
15
20
HTML: 824
PDF: 489
XML: 47
Total: 1,360
Supplement: 180
BibTeX: 15
EndNote: 20
Views and downloads (calculated since 07 Dec 2021)
Cumulative views and downloads
(calculated since 07 Dec 2021)
Viewed (geographical distribution)
Total article views: 5,297 (including HTML, PDF, and XML)
Thereof 5,141 with geography defined
and 156 with unknown origin.
Total article views: 3,937 (including HTML, PDF, and XML)
Thereof 3,852 with geography defined
and 85 with unknown origin.
Total article views: 1,360 (including HTML, PDF, and XML)
Thereof 1,289 with geography defined
and 71 with unknown origin.
It is urgent to obtain accurate soil moisture (SM) with high temporal and spatial resolution for areas affected by desertification in northern China. A combination of multiple machine learning methods, including multiple linear regression, support vector regression, artificial neural networks, random forest and extreme gradient boosting, has been applied to downscale the 36 km SMAP SM products and produce higher-spatial-resolution SM data based on related surface variables.
It is urgent to obtain accurate soil moisture (SM) with high temporal and spatial resolution for...