Journal of Agricultural Big Data >
Analysis of Spatiotemporal Evolution of Guizhou Agricultural Drought Index Based on Collaborative Visualization
Received date: 2024-03-19
Accepted date: 2024-05-21
Online published: 2024-12-02
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.
HE LingJun, LONG Hai, LI LiJie, ZHAO ZeYing . Analysis of Spatiotemporal Evolution of Guizhou Agricultural Drought Index Based on Collaborative Visualization[J]. Journal of Agricultural Big Data, 2024 , 6(4) : 532 -545 . DOI: 10.19788/j.issn.2096-6369.000042
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