Combination of multi-sensor remote sensing data for drought monitoring over Southwest China

Author(s):  
Cui Hao ◽  
Jiahua Zhang ◽  
Fengmei Yao
2009 ◽  
Author(s):  
Bingfeng Yang ◽  
Qiao Wang ◽  
Changzuo Wang ◽  
Huawei Wan ◽  
Yipeng Yang ◽  
...  

2021 ◽  
pp. 413-422
Author(s):  
Shao Li ◽  
Xia Xu

Using remote sensing data to monitor large area drought is one of the important methods of drought monitoring at present. However, the traditional remote sensing drought monitoring methods mainly focus on monitoring single drought response factors such as soil moisture or vegetation status, and the research on comprehensive multi-factor drought monitoring is limited. In order to improve the ability to resist drought events, this paper takes Henan Province of China as an example, takes multi-source remote sensing data as data sources, considers various disaster-causing factors, adopts random forest method to model, and explores the method of regional remote sensing comprehensive drought monitoring using various remote sensing data sources. Compared with neural network, classification regression tree and linear regression, the performance of random forest is more stable and tolerant to noise and outliers. In order to provide a new method for comprehensive assessment of regional drought, a comprehensive drought monitoring model was established based on multi-source remote sensing data, which comprehensively considered the drought factors such as soil water stress, vegetation growth status and meteorological precipitation profit and loss in the process of drought occurrence and development.


2014 ◽  
Vol 12 (3) ◽  
pp. 659-666
Author(s):  
He Huang ◽  
Yida Fan ◽  
Siquan Yang ◽  
Wenbo Li ◽  
Haixia He ◽  
...  

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