A Random Forest Model for Drought: Monitoring and Validation for Grassland Drought Based on Multi-Source Remote Sensing Data

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成果类型：

期刊论文

作者：

Wang, Qian;Zhao, Lin;Wang, Mali;Wu, Jinjia;Zhou, Wei;...

通讯作者：

Qipeng Zhang

作者机构：

[Wang, Qian; Zhao, Lin; Wang, Mali; Zhang, Qipeng] Liaocheng Univ, Sch Geog & Environm, Dept Geog Informat Sci, Liaocheng 252059, Shandong, Peoples R China.

[Wu, Jinjia] Liaocheng Univ, Grand Canal Res Ctr, Grand Canal Res Inst, Liaocheng 252000, Shandong, Peoples R China.

[Zhou, Wei] Southwest Univ, Sch Geog Sci, Chongqing Jinfo Mt Karst Ecosyst Natl Observat &, Chongqing 400715, Peoples R China.

[Deng, Meie] Wuhan Polytech Univ, Sch Management, Wuhan 430048, Peoples R China.

通讯机构：

[Qipeng Zhang] D

Department of Geographic Information Science, School of Geography and Environment, Liaocheng University, Liaocheng 252059, China<&wdkj&>Author to whom correspondence should be addressed.

语种：

英文

关键词：

random forest;grassland drought monitoring;SPEI;drought

期刊：

Remote Sensing

ISSN：

2072-4292

年：

2022

卷：

期：

页码：

4981-

DOI：

10.3390/rs14194981

基金类别：

This study was supported by the Natural Science Foundation of China (32060279), Natural Science Foundation of Shandong Province (ZR2022MD063), and the Doctoral Startup Foundation of Liaocheng University (318052036, 318052116).

机构署名：

本校为其他机构

院系归属：

管理学院

摘要：

The accuracy of drought monitoring models is crucial for drought monitoring and early warning. Random forest (RF) is being used widely in the field of artificial intelligence. Nonetheless, the application of a random forest model in grassland drought monitoring research is yet to be further explored. In this study, various drought hazard factors were integrated based on remote sensing data, including from the Moderate Resolution Imaging Spectroradiometer (MODIS) and Global Precipitation Measurement (GPM), as multisource remote sensing data. Based on the RF, a comprehensive grassland drought mo...

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A Random Forest Model for Drought: Monitoring and Validation for Grassland Drought Based on Multi-Source Remote Sensing Data

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