TY - GEN
T1 - Advanced cyberinfrastructure for agricultural drought monitoring
AU - Sun, Ziheng
AU - Di, Liping
AU - Fang, Hui
AU - Guo, Liying
AU - Yu, Eugene
AU - Tang, Junmei
AU - Zhao, Haoteng
AU - Gaigalas, Juozas
AU - Zhang, Chen
AU - Lin, Li
AU - Yu, Zhiqi
AU - Zhong, Shaobo
AU - Wang, Xiaoping
AU - Tan, Xicheng
AU - Jiang, Lili
AU - Chen, Zhongxin
AU - Xu, Zhanya
AU - Sun, Jie
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - 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.
AB - 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.
KW - Agricultural drought
KW - Big data
KW - Cyberinfrastructure
KW - Remote sensing
KW - Time series.
UR - http://www.scopus.com/inward/record.url?scp=85072917994&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85072917994&partnerID=8YFLogxK
U2 - 10.1109/Agro-Geoinformatics.2019.8820694
DO - 10.1109/Agro-Geoinformatics.2019.8820694
M3 - Conference contribution
AN - SCOPUS:85072917994
T3 - 2019 8th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2019
BT - 2019 8th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2019
Y2 - 16 July 2019 through 19 July 2019
ER -