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作 者:何凌君 龙海[1] 李莉婕[1] 赵泽英[1] HE LingJun;LONG Hai;LI LiJie;ZHAO ZeYing(Guizhou Agricultural Science and Technology Information Institute,Guiyang,Guizhou 550006,China)
出 处:《农业大数据学报》2024年第4期532-545,共14页Journal of Agricultural Big Data
基 金:贵州省科研机构创新能力建设专项(黔科合服企[2021]15);贵州省科技计划项目(黔科合支撑[2022]113);贵州省农业科学院科技创新项目(黔农科院科技创新[2022]14)。
摘 要:对于当下强烈的农业干旱监测需求,一套可靠、高效的时空变化监测及评估方案是非常必要的。本研究基于1990-2022年的土壤湿度网格数据,选取经典的农业干旱指数SMCI(Soil Moisture Condition Index)和SSI(Standardized Soil Moisture Index),设计了一套多视图协同、交互式的可视化分析方案,为多维的干旱数据分析提供了一种更加全面的、易于感知的新视角。结果表明:1)通过对贵州省干旱在年、季、月不同时间尺度下干旱的强度和空间变化进行分析,详细把握了贵州省这32年间的干旱时空变化,证明了本研究在干旱时空演化特征分析上的有效性;2)通过对SMCI和SSI在不同场景下的适用效果进行比较,评估了不同监测手段的干旱分析优势,证明了本研究可以用于干旱指数的比较。在当前的农业干旱监测中,协同可视化的分析手段可以有效提升监测效果。Nowadays,a set of reliable and efficient monitoring and assessment scheme for spatiotemporal changes is very necessary for the high demand of agricultural drought monitoring.In this study,based on the soil moisture grid data from 1990 to 2022 and the classical agricultural drought indexes SMCI(Soil Moisture Condition Index)and SSI(Standardized Soil Moisture Index),we designed a set of multi-view collaborative and interactive visualization and analysis scheme,which is able to give a new perspective,more comprehensive and more easily adapted to sense on multi-dimensional drought data analysis.The results show that:(1)by analyzing the spatiotemporal changes of drought in Guizhou at different time scales such as year,season and month,we could get a good grasp of the spatiotemporal evolution of drought in Guizhou during these 32 years,and this proves the validity of this study in analyzing the characterization of the spatiotemporal evolution of drought;(2)by comparing the applicable effects of SMCI and SSI in different scenarios,we evaluated the advantages of different monitoring methods in drought analysis,which proves that this study can be used to compare drought indexes.In current agricultural drought monitoring,collaborative visualization analysis can effectively enhance monitoring effect.
关 键 词:时空演化 农业干旱 协同可视化 SMCI SSI
分 类 号:TP3[自动化与计算机技术—计算机科学与技术]
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