Derivation of Wildfire Ignition Index using GIS-MCDA from High-Resolution UAV Imagery Data and Perception Analysis in Settlement Sali, Dugi Otok Island (Croatia)

Ivan Marić; Ante Šiljeg; Fran Domazetović

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Paper

Derivation of Wildfire Ignition Index using GIS-MCDA from High-Resolution UAV Imagery Data and Perception Analysis in Settlement Sali, Dugi Otok Island (Croatia)

Topics: Decision Support Systems; Disaster Management; Geospatial Information and Technologies; Photogrammetry

In Proceedings of the 7th International Conference on Geographical Information Systems Theory, Applications and Management GISTAM - Volume 1, 90-97, 2021

Authors: Ivan Marić ; Ante Šiljeg and Fran Domazetović

Affiliation: University of Zadar, Department of Geography, Trg kneza Višeslava 9, 23 000 Zadar, Croatia

Keyword(s): Wildfire Risk Ignition Index, GIS-MCDA, High-Resolution UAV Imagery, Perception.

Abstract: In recent years, wildfires have become one of the most hazardous natural disasters because of their overall impact on the natural and urban environment. In this paper, we have generated a wildfire risk ignition index for the Sali settlement (Dugi Otok, Croatia). This model was generated within the INTERREG PEPSEA (Protecting the Enclosed Parts of the Sea in Adriatic from pollution) project. Wildfire ignition index is based on the GIS-MCDA (Multi-Criteria Decision Analysis). The process was performed using 13 criteria grouped in five clusters. Criteria were derived from high-resolution multispectral (5 bands) orthomosaic and digital terrain model (DTM) produced from imagery acquired with Matrice 600 Pro and Matrice 210 RTK V2 UAV. The criteria weights were determined using the AHP (Analytic Hierarchy Process). The model of wildfire ignition risk was classified into five classes, from very low (1) to very high (5). The model indicates that 14.14 % of the study area falls in a very high (5) ignition risk zone. The fire-risk perception was analyzed and the wildfire ignition model was evaluated using a questionnaire. The results indicate that all recent wildfire ignition locations occurred in high (4) and very high (5) risk class. Furthermore, the population recognized wildfires as a moderate threat to the ecosystem of the wider Sali area. A set of specific management measures has been proposed to prevent wildfire ignition. This proposed methodological framework and results can provide valuable information and specific management tools to local government. (More)

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Paper citation in several formats:

Marić, I. ; Šiljeg, A. and Domazetović, F. (2021). Derivation of Wildfire Ignition Index using GIS-MCDA from High-Resolution UAV Imagery Data and Perception Analysis in Settlement Sali, Dugi Otok Island (Croatia). In Proceedings of the 7th International Conference on Geographical Information Systems Theory, Applications and Management - GISTAM; ISBN 978-989-758-503-6; ISSN 2184-500X, SciTePress, pages 90-97. DOI: 10.5220/0010465000900097

@conference{gistam21,
author={Ivan Marić and Ante Šiljeg and Fran Domazetović},
title={Derivation of Wildfire Ignition Index using GIS-MCDA from High-Resolution UAV Imagery Data and Perception Analysis in Settlement Sali, Dugi Otok Island (Croatia)},
booktitle={Proceedings of the 7th International Conference on Geographical Information Systems Theory, Applications and Management - GISTAM},
year={2021},
pages={90-97},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010465000900097},
isbn={978-989-758-503-6},
issn={2184-500X},
}

TY - CONF

JO - Proceedings of the 7th International Conference on Geographical Information Systems Theory, Applications and Management - GISTAM
TI - Derivation of Wildfire Ignition Index using GIS-MCDA from High-Resolution UAV Imagery Data and Perception Analysis in Settlement Sali, Dugi Otok Island (Croatia)
SN - 978-989-758-503-6
IS - 2184-500X
AU - Marić, I.
AU - Šiljeg, A.
AU - Domazetović, F.
PY - 2021
SP - 90
EP - 97
DO - 10.5220/0010465000900097
PB - SciTePress