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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Community Detection in Very High-Resolution Meteorological Networks

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Autor(es):
Ceron, Wilson [1] ; Santos, Leonardo B. L. [2] ; Neto, Giovanni Dolif [2] ; Quiles, Marcos G. [1] ; Candido, Onofre A. [1]
Número total de Autores: 5
Afiliação do(s) autor(es):
[1] Univ Fed Sao Paulo, Inst Sci & Technol, BR-12247014 Sao Jose Dos Campos - Brazil
[2] Ctr Monitoring & Early Warning Nat Disasters, BR-12247016 Sao Jose Dos Campos - Brazil
Número total de Afiliações: 2
Tipo de documento: Artigo Científico
Fonte: IEEE Geoscience and Remote Sensing Letters; v. 17, n. 11, p. 2007-2010, NOV 2020.
Citações Web of Science: 0
Resumo

Several complex dynamical systems are embedded in geographical space. Geographical data have proven its importance in several domains. For instance, the formation and scrutiny of climate networks have emerged as a new research topic in environmental literature. However, there is still a lack of investigations of scenarios with very high spatial resolution, such as those considering meteorological data. Recently, a new concept, named (geo)graphs, was proposed. (Geo)graphs are graphs, or networks, in which the nodes have an assigned geographical location. Besides embedding nodes into space, these graphs are readily manipulated with a geographical information system, and, thus, represent a suitable tool for dealing with very high-resolution scenarios, such as meteorological data. In this context, here, we apply a (geo)graph approach to model a radar-derived rainfall data set. We represent the nodes as a point-type shapefile and the edges as a line-type shapefile, which are standard file types in geoinformatics. After, we analyze the topological properties of a family of (geo)graphs considering distinct thresholds. The analysis of these networks reveals a spatially well-defined community structure, which, interestingly, is consistent with topographical/altimetric and land use/land cover data. These results show the relation between geographical properties and the topological structure of the network might be applied to different ecological studies, from sustainable development to urban planning and disaster risk reduction. (AU)

Processo FAPESP: 16/16291-2 - Caracterização de redes dinâmicas: métodos e aplicações
Beneficiário:Marcos Gonçalves Quiles
Linha de fomento: Bolsas no Exterior - Pesquisa
Processo FAPESP: 15/50122-0 - Fenômenos dinâmicos em redes complexas: fundamentos e aplicações
Beneficiário:Elbert Einstein Nehrer Macau
Linha de fomento: Auxílio à Pesquisa - Temático
Processo FAPESP: 18/06205-7 - Vulnerabilidade Estocástica em Redes Complexas
Beneficiário:Leonardo Bacelar Lima Santos
Linha de fomento: Bolsas no Exterior - Pesquisa