Mapping socio-spatial segregation in the city of Marília/SP (Brazil)

Araujo, Agnes Silva de; Filho, Alfredo Pereira de Queiroz

doi:10.26848/rbgf.v11.2.p431-441

Cited by 1 publication

(1 citation statement)

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“…To calculate the susceptibility of a given area to occurrences, the informative value method was adopted. That method is usually used for analyzing the susceptibility of a territory to landslides [45,46] but also to fire [47] and other types of risk, including nonenvironmental [48]. The raster layer zonal statistics tool, used in the analysis mentioned in the previous paragraph, creates a table that relates the different classes of the reclassified variable (returned as "zone") to statistics regarding the area with occurrences within such class, namely "count" (number of pixels belonging to the class) and "sum" (sum of the pixel values in the class).…”

Section: Main Scriptmentioning

confidence: 99%

A GIS Plugin for Susceptibility Modeling: Case Study of Wildfires in Vila Nova de Foz Côa

Padrão¹,

Duarte

Teodoro

2022

Land

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Risk mapping is a crucial part of spatial planning, as it optimizes the allocation of resources in its management. It is, therefore, of great interest to build tools that enhance its production. This work focuses on the implementation of a susceptibility model for different types of spatially distributed risk in a geographic information systems (GIS) Python plugin. As an example, the susceptibility model was applied to study the occurrence of wildfires in the municipality of Vila Nova de Foz Côa, Portugal. The plugin was developed to simplify the production and evaluation of susceptibility maps regarding the available geographical information. Regarding our case study, the data used corresponds to three training areas, ten years of burned areas and nine environmental variables. The model is applied to different combinations of these factors. The validation, performed with receiver operating characteristic (ROC) curves, resulted in an area under the curve (AUC) of 74% for a fire susceptibility model, calculated with the same environmental factors used in official Portuguese cartography (land use and slope) and with the optimal training area, years of information on burned area and level of land use classification. After experimenting with four variable combinations, a maximum AUC of 77% was achieved. This study confirms the suitability of the variables chosen for the production of official fire susceptibility models but leaves out the comparison between the official methodology and the methodology proposed in this work.

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Section: Main Scriptmentioning

confidence: 99%