Graph4GIS: Geographical graphs for GIS platforms based on weather radar dataset

被引：0

作者：

Jorge, Aurelienne ^{[1
]}

Freitas, Vander L. S. ^{[2
]}

Costa, Izabelly C. ^{[1
]}

Santos, Leonardo B. L. ^{[3
]}

机构：

[1] Natl Inst Space Res OE, Cachoeira Paulista, SP, Brazil

[2] Fed Univ Ouro Preto UFOP, Ouro Preto, MG, Brazil

[3] Natl Ctr Monitoring & Early Warnings Nat Disasters, Sao Jose Dos Campos, SP, Brazil

来源：

SOFTWARE IMPACTS | 2023年 / 17卷

基金：

巴西圣保罗研究基金会;

关键词：

Complex networks; Weather radar; Nowcasting; Precipitation forecast; Geographical graphs; TOOL;

D O I：

10.1016/j.simpa.2023.100530

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Complex networks have diverse applications in studying natural systems, such as weather and climate. Graph-based networks enable the identification of inherent relationships and structural patterns in these systems. This paper introduces Graph4GIS, a novel tool for constructing geographical graphs using spatial gridded data, with a particular focus on weather radar datasets. Time series are represented as nodes, and links are established between nodes based on predefined similarity criteria. The tool offers various similarity measures and criteria for network construction. As a proof of concept, the paper presents results of different network structures applied to a watershed.

引用

页数：3

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