Advanced Cyberinfrastructure for Agricultural Drought Monitoring

文献类型： 外文期刊

第一作者： Sun, Ziheng

作者： Sun, Ziheng;Di, Liping;Fang, Hui;Guo, Liying;Yu, Eugene;Tang, Junmei;Zhao, Haoteng;Gaigalas, Juozas;Zhang, Chen;Lin, Li;Yu, Zhiqi;Zhong, Shaobo;Wang, Xiaoping;Tan, Xicheng;Jiang, Lili;Chen, Zhongxin;Xu, Zhanya;Sun, Jie

作者机构：

关键词： cyberinfrastructure; agricultural drought; big data; remote sensing; time series

期刊名称：2019 8TH INTERNATIONAL CONFERENCE ON AGRO-GEOINFORMATICS (AGRO-GEOINFORMATICS)

ISSN： 2334-3168

年卷期： 2019 年

页码：

收录情况： SCI

摘要： Cyberinfrastructure plays an important role in the collection, management, and dissemination of drought information in agricultural activities, especially when the activities involve a variety of facilities, data sources, and communities. The challenge of coordinating tremendous sources of data and systems becomes paramount. Some key questions require additional attention if analyzing agricultural drought in a large social-environmental context: preprocessing observation into analysis-ready format, integrate vegetation/soil observations across platforms, and assess potential risks on the crop yield and environment. Cyberinfrastructure capable of accepting data from either research and monitoring networks or professionals in agricultural activities, must be built to achieve these goals. The cyberinfrastructure design generally consists of four components: data source, standardized web service, application service, and client interface. This study introduces a cloud-based global agricultural drought monitoring and forecasting system (GADMFS) which provides scalable vegetation-based drought indicators derived from satellite-, and model-based vegetation condition datasets. The provided datasets include global historical drought severity data from the monitoring component. The system is a significant extension to current capabilities and datasets from global drought assessment and early warning. The experiment results show that GADMFS successfully captured the major drought events in history and reflected the high-resolution spatial distribution which can specifically assist agriculture stakeholders to make informative decisions and take proactive drought management actions.

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