RESEARCH ON DROUTHT MONITORING IN SHANDONG PROVIENCE BASED ON MULTI-SOURCE REMOTE SENSING DATA

被引：0
作者：
Wan, Hong [1 ,2 ,3 ]
Guo, Peng [1 ]
Wang, Zhengdong [1 ,2 ]
Zhao, Tianjie [2 ]
Meng, Chunhong [1 ]
Yang, Gang [1 ]
机构：
[1] Shandong Agr Univ, Coll Informat Sci & Engn, Tai An 271000, Shandong, Peoples R China
[2] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Beijing 100094, Peoples R China
[3] Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
来源：
2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019) | 2019年
基金：
中国国家自然科学基金;
关键词：
drought monitoring; remote sensing; FY-3B; MODIS;
D O I：
10.1109/igarss.2019.8897998
中图分类号：
P [天文学、地球科学];
学科分类号：
07 ;
摘要：
Drought is one of the major natural disasters which not only causes great damage to ecosystems and the environment, but also seriously affects social and economic activities and residents' lives. In this study, the MODIS- Albedo, LST and NDVI data was used to downscale the FY-3B soil moisture product at 25km to 1km by multivariate statistical regression method. Then the drought of Shandong Province was monitored using the downscaling results in 2016. The results indicate that drought monitoring using multi-source remote sensing data is very useful for drought monitoring.
引用
收藏
页码：9428 / 9430
页数：3
相关论文
共 4 条
[1]  
[曹永攀 Cao Yongpan], 2011, [遥感技术与应用, Remote Sensing Technology and Application], V26, P590
[2]   Spaceborne soil moisture estimation at high resolution: a microwave-optical/IR synergistic approach [J].
Chauhan, NS ;
Miller, S ;
Ardanuy, P .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2003, 24 (22) :4599-4622
[3]  
De Jeu R., 2014, J HYDROL, P284
[4]   Downscaling SMOS-Derived Soil Moisture Using MODIS Visible/Infrared Data [J].
Piles, Maria ;
Camps, Adriano ;
Vall-Llossera, Merce ;
Corbella, Ignasi ;
Panciera, Rocco ;
Ruediger, Christoph ;
Kerr, Yann H. ;
Walker, Jeffrey .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2011, 49 (09) :3156-3166
1