Methodological Proposal for Automated Detection of the Wildland–Urban Interface: Application to the Metropolitan Regions of Madrid and Barcelona

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Title: Methodological Proposal for Automated Detection of the Wildland–Urban Interface: Application to the Metropolitan Regions of Madrid and Barcelona
Authors: Zambrano-Ballesteros, Andrea | Nanu, Sabina Florina | Navarro Carrión, José Tomás | Ramon-Morte, Alfredo
Research Group/s: Medio, Sociedad y Paisaje (MedSPai) | Planificación y Gestión Sostenible del Turismo
Center, Department or Service: Universidad de Alicante. Departamento de Análisis Geográfico Regional y Geografía Física | Universidad de Alicante. Instituto Interuniversitario de Geografía
Keywords: GIS | LiDAR | PostGIS | Wildland–urban interface (WUI) | Wildfire | SIOSE | Geo open data | Geo small data
Knowledge Area: Análisis Geográfico Regional
Issue Date: 3-Jun-2021
Publisher: MDPI
Citation: Zambrano-Ballesteros A, Nanu SF, Navarro-Carrión JT, Ramón-Morte A. Methodological Proposal for Automated Detection of the Wildland–Urban Interface: Application to the Metropolitan Regions of Madrid and Barcelona. ISPRS International Journal of Geo-Information. 2021; 10(6):381. https://doi.org/10.3390/ijgi10060381
Abstract: Official information on Land Use Land Cover is essential for mapping wildland–urban interface (WUI) zones. However, these resources do not always provide the geometrical or thematic accuracy required to delimit buildings that are easily exposed to risk of wildfire at the appropriate scale. This research shows that the integration of active remote sensing and official Land Use Land Cover (LULC) databases, such as the Spanish Land Use Land Cover information system (SIOSE), creates the synergy capable of achieving this. An automated method was developed to detect WUI zones by the massive geoprocessing of data from official and open repositories of the Spanish national plan for territory observation (PNOT) of the Spanish national geographic institute (IGN), and it was tested in the most important metropolitan zones in Spain: Barcelona and Madrid. The processing of trillions of LiDAR data and their integration with thousands of SIOSE polygons were managed in a Linux environment, with libraries for geographic processing and a PostgreSQL database server. All this allowed the buildings that are exposed to wildfire risk with a high level of accuracy to be obtained with a methodology that can be applied anywhere in the Spanish territory.
Sponsor: This research was funded by and conducted within the SIOSE-INNOVA Project (CSO2016-79420-R AEI/FEDER/UE, Ministry of Science and Innovation, Spain) and funded by the endowment of an award for conducting research with the objectives of sustainable development (SDGs) from the General Directorate for Cooperation and Solidarity of Government of Generalitat Valenciana (Spain).
URI: http://hdl.handle.net/10045/115586
ISSN: 2220-9964
DOI: 10.3390/ijgi10060381
Language: eng
Type: info:eu-repo/semantics/article
Rights: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Peer Review: si
Publisher version: https://doi.org/10.3390/ijgi10060381
Appears in Collections:INV - PGST - Artículos de Revistas
INV - MedSPai - Artículos de Revistas

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