先进的农业干旱监测网络基础设施

Ziheng Sun, L. Di, Hui Fang, Liying Guo, E. Yu, Junmei Tang, Haoteng Zhao, Juozas Gaigalas, Chen Zhang, Li Lin, Zhiqi Yu, Shaobo Zhong, Xiaoping Wang, Xicheng Tan, Lili Jiang, Zhongxin Chen, Zhanya Xu, Jie Sun
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引用次数: 6

摘要

网络基础设施在农业活动中干旱信息的收集、管理和传播方面发挥着重要作用,特别是当这些活动涉及各种设施、数据源和社区时。协调大量数据和系统的挑战变得至关重要。如果在大的社会环境背景下分析农业干旱,则需要额外关注一些关键问题:将观测数据预处理为可供分析的格式,跨平台整合植被/土壤观测数据,并评估作物产量和环境的潜在风险。为了实现这些目标,必须建立能够接受来自研究和监测网络或农业活动专业人员的数据的网络基础设施。网络基础设施设计一般由数据源、标准化web服务、应用服务和客户端接口四个部分组成。本研究介绍了一个基于云的全球农业干旱监测和预报系统(GADMFS),该系统提供基于卫星和基于模型的植被状况数据集的可扩展的基于植被的干旱指标。所提供的数据集包括来自监测组件的全球历史干旱严重程度数据。该系统是对目前全球干旱评估和预警能力和数据集的重要扩展。实验结果表明,GADMFS成功地捕获了历史上重大干旱事件,并反映了高分辨率的空间分布,可以有针对性地帮助农业利益相关者做出信息决策,采取主动的干旱管理行动。
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Advanced Cyberinfrastructure for Agricultural Drought Monitoring
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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