Prioritization in wildfire restoration using GIS-based ordered weighted averaging (OWA): A case study in southern California

Abstract

Wildfires are a prevalent natural disaster that can significantly impact human populations and result in considerable losses. With a changing climate, wildfires in many countries have increased in intensity and frequency, making effective restoration efforts in affected areas crucial. This paper aims to evaluate the efficacy of ordered weighted averaging (OWA), a GIS-based multi-criteria decision analysis technique, in identifying priority areas for wildfire restoration. A case study using the 2009 Station Fire in California is presented, using the restoration criteria of slope, erodibility, proximity to forest cover, and proximity to surface water. By applying both importance and order weights, multiple OWA decision strategies with varying risk levels were examined. Different strategies greatly influence the spatial distribution of land considered high and low priority for wildfire restoration, each with varying levels of trade off. In the OWA decision space, placing full emphasis on the highest (best) values (using the risk-taking OR operator) or the lowest values (using the risk-averse AND operator) resulted in composite priority maps that cannot be recommended for practical use. More nuanced scenarios are achieved with the OWA operators representing a range of compromise decision strategies between these extremes. The OWA technique in GIS can thus help to explore the impact of decision-makers' risk attitudes in a wildfire restoration setting.