Drought Monitoring in Sub-Sahara Africa

被引：0
|
作者：
Mou, Fan [1 ]
Akwasi, Twum-Antwi [1 ]
Li, Mujie [1 ]
Zhu, Mingcang [2 ]
He, Yong [3 ]
He, Zhanyong [3 ]
Xiao, Yang [3 ]
Ren, Juan [3 ]
Xia, Jun [1 ,4 ,5 ]
Zhang, Xiang [4 ,5 ]
Zheng, Zezhong [1 ,5 ,6 ]
Zhou, Guoqing [6 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Resources & Environm, Chengdu 611731, Sichuan, Peoples R China
[2] Dept Nat Resources Sichuan Prov, Chengdu 610072, Sichuan, Peoples R China
[3] Sichuan Res Inst Ecosyst Restorat & Geodisaster P, Chengdu 610081, Sichuan, Peoples R China
[4] Wuhan Univ, Hubei Prov Key Lab Water Syst Sci Sponge City Con, Wuhan 430072, Hubei, Peoples R China
[5] Wuhan Univ, State Key Lab Water Resources & Hydropower Engn S, Wuhan 430072, Hubei, Peoples R China
[6] Guilin Univ Technol, Guangxi Key Lab Spatial Informat & Geomat, Guilin 541004, Guangxi, Peoples R China
来源：
IGARSS 2020 - 2020 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM | 2020年
关键词：
Drought monitoring; NDVI; rainfall; LST; DYNAMICS;
D O I：
10.1109/IGARSS39084.2020.9323809
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Drought is one of the main natural hazards affecting the environment and economy of countries all over the world. Fusing weather data with satellite images therefore becomes a superior method of identifying and monitoring drought in a given region. We established the relationship between land surface temperature (LST), the normalized differential vegetation index (NDVI) and rainfall data to derive areas of drought. Then, we obtained the indexes from the rainfall anomaly and NDVI anomaly as indicators which confirm the drought indicative claims of the maps produced. Our further examination of the NDVI, LST and rainfall maps indicate that the western, central and Volta Regions of the study area are the least prone to drought, with Axim (one of the most southern towns) in Ghana recording the highest rainfall in the country each year.
引用
收藏
页码：6902 / 6905
页数：4
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