数字农科院2.0

Advanced Cyberinfrastructure For Agricultural Drought Monitoring

文献类型： 外文期刊

作者： Sun, ZH; Di, LP; Fang, H; Guo, LY; Yu, EGN; Tang, JM; Zhao, HT; Gaigalas, J; Zhang, C; Lin, L; Yu, ZQ; Zhong, SB; Wang, XP; Tan, XC; Jiang, LL; Chen, ZX; Xu, ZY; Sun, J

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：

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.

分类号：

  • 相关文献

[1]Establish Cyberinfrastructure To Facilitate Agricultural D.rought Monitoring. Sun, ZH, Di, LP, Zhang, C, Fang, H, Yu, E, Lin, L, Tan, XC, Guo, LY, Chen, ZX, Yue, P, Jiang, LL, Liu, Z. 2017

[2]Distributed Correlation Model Mining From R.emote Sensing Big Data B ased On Gene Expression Programming. Yang, LC, Qin, ZH. 2018

[3]Net Surface Shortwave Radiation Retrieval Using Random Forest Method With Modis/Aqua Data. Li, Zhao-Liang,Wu, Hua,Wu, Hua,Wu, Hua,Ying, Wangmin,Ying, Wangmin,Li, Zhao-Liang. 2019

[4]Estimation of evapotranspiration using all-weather land surface temperature and variational trends with warming temperatures for the River Source Region in Southwest China. Ma Y., Zhou J., Liu S., Zhang W., Zhang Y., Xu Z., Song L., Zhao H.. 2022

[5]A Robust Method for Filling the Gaps in MODIS and VIIRS Land Surface Temperature Data. Rui Yao,Lunche Wang,Xin Huang,Liang Sun,Ruiqing Chen,Xiaojun Wu,Wei Zhang,Zigeng Niu. 2021

[6]Global Disparity In Public Awareness O.f The Biological Control P otential Of Invertebrates. Reynolds, O. L.,Wyckhuys, K. A. G.,Reynolds, O. L.,Wratten, S. D.,Wyckhuys, K. A. G.,Vasseur, L.,Goettel, O.,Gurr, G. M.,Gurr, G. M.,Vasseur, L.,Goettel, O.,Lovei, G. L.,Wyckhuys, K. A. G.,Lovei, G. L.,Wyckhuys, K. A. G.,Pozsgai, G.,Wyckhuys, K. A. G.,Wyckhuys, K. A. G.,Wratten, S. D.,Reynolds, O. L.,Wyckhuys, K. A. G.,Wyckhuys, K. A. G.. 2019

[7]Research on intelligent supervision and visualization of big data on the flow and direction of veterinary drug. Kong Fantao, Cao Shanshan, Sun Wei, Liu Jifang.. 2022

[8]Research On Monitoring Platform Of A.gricultural Product Circulation Efficiency S upported By Cloud Computing. Chen, JB, Zhong, Y, Lam, A. 2018

[9]Valid Historical Data For Probabilistic R.isk Analysis In Natural D isasters. Huang, Chongfu,Huang, Chongfu,Zhao, Sijian,Huang, Chongfu,Guo, Jun,Guo, Jun,Guo, Jun. 2017

[10]High resolution crop intensity mapping using harmonized Landsat-8 and Sentinel-2 data. HAO P.-Y., TANG H.-J., CHEN Z.-X., YU L., WU M.-Q.. 2019

[11]Retrieval Of Surface Temperature And Emissivity From Ground-Based Time-Series Thermal Infrared Data. Qian, YG, Wang, N, Li, K, Wu, H, Duan, SB, Liu, YK, Ma, LL, Gao, CX, Qiu, S, Tang, LL, Li, CR. 2020

[12]Air-drying and long time preservation of soil do not significantly impact microbial community composition and structure. Wang F.,Che R.,Deng Y.,Wu Y.,Tang L.,Xu Z.,Wang W.,Liu H.,Cui X.. 2021

[13]Development Of A Low-Cost Quadrotor U.av Based On Adrc F or Agricultural Remote Sensing. Xue, Xinyu,Zhang, Songchao,Zhang, Songchao,Sun, Tao,Chen, Chen,Sun, Zhu. 2019

[14]Rapid Detection Of Chlorophyll Content A.nd Distribution In Citrus O rchards Based On Low-Altitude Remote Sensing And Bio-Sensors. Deng, Lie,He, Shaolan,Li, Wentao,Lyu, Qiang,Zheng, Yongqiang,Yi, Shilai,Xie, Rangjin,Wang, Kejian,Ma, Yanyan. 2018

[15]Evaluation Of Machine Learning Algorithms In Spatial Downscaling Of Modis Land Surface Temperature. Wu, Hua,Duan, Si-Bo,Li, Zhao-Liang,Wu, Hua,Li, Zhao-Liang,Li, Wan,Li, Wan,Ni, Li,Wu, Hua. 2019

[16]Water quality related to Conservation Reserve Program (CRP) and cropland areas: Evidence from multi-temporal remote sensing. Yin, Dameng,Wang, Le,Zhu, Zhenduo,Clark, Susan Spierre,Cao, Ying,Besek, Jordan,Dai, Ning. 2021

[17]A Framework For Assessing The E.ffects Of Afforestation And S outh-To-North Water Transfer On Nitrogen And Phosphorus Uptake By Plants In A Critical Riparian Zone. Zhao, HG, Huang, YC, You, SC, Wu, YF, Zheng, FX. 2019

[18]Estimation Of Daily Evapotranspiration Using M.odis Data To Calculate I nstantaneous Decoupling Coefficient And Resistances. Jiang, YZ, Jiang, XG, Tang, RL, Li, ZL, Zhang, YZ, Huang, C, Ru, C. 2017

[19]The Influences Of The South-To-North Water Transfer Project On Nitrogen Removal By Soil In A Terminal Reservoir In A Critical State In China. Xue, WL, Li, FH, Zhao, HG. 2019

[20]Estimating Grassland Lai Using The R.andom Forests Approach And L andsat Imagery In The Meadow Steppe Of Hulunber, China. Li, ZW, Xin, XP, Tang, H, Yang, F, Chen, BR, Zhang, BH. 2017

作者其他论文 更多>>