Monitoring and Predicting Desert Locust Plague Severity in Asia–Africa Using Multisource Remote Sensing Time-Series Data

Monitoring and Predicting Desert Locust Plague Severity in Asia–Africa Using Multisource Remote Sensing Time-Series Data

The outbreak of large-scale desert locust plague in 2020 has attracted wide attention in the world and caused serious damage to food security and livelihood of African and Asian people. Remote sensing techniques can provide indirect feedback on locust plagues, facilitating quick, and real-time monit...

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Bibliographic Details
Main Authors: Zhenfeng Shao, Xiaoxiao Feng, Linze Bai, Haiming Jiao, Ya Zhang, Deren Li, Haisheng Fan, Xiao Huang, Yuqi Ding, Orhan Altan, Nayyer Saleem
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Change detection
Hidden Markov Model (HMM)
hyperspectral imagery
locust plague prediction
moderate-resolution imaging spectroradiometer (MODIS)
semisupervised classification
Online Access:https://ieeexplore.ieee.org/document/9514444/

Internet

https://ieeexplore.ieee.org/document/9514444/

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