Monitoring growth of the wildland-urban interface in 2000 and 2020 in Mediterranean ecosystems with Landsat satellite imagery

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Authors: Kira A. Pfoch, Franz Schug, Heather Cox, Vu-Dong Pham, Sebastian van der Linden, Volker Christian Radeloff
Cited by: 0
References: 102

Abstract

The wildland-urban interface (WUI) is the area where buildings meet or intermingle with wildland vegetation causing high wildfire risk, especially in fire-prone Mediterranean ecosystems. Mapping WUI growth can help to manage that risk but requires consistent information on building density and vegetation cover over time. Unfortunately, most WUI mapping methods cannot be applied to map long-term WUI growth due to the lack of historical data on building locations or density. We developed a novel method to map the WUI and its growth by comparing WUI extents in 2000 and 2020 using Landsat satellite data. Our goal was to: (a) accurately map the 2020 WUI with Landsat data, (b) distinguish WUI types by vegetation composition, and (c) map 2000 to 2020 WUI growth in five Mediterranean ecosystems: Adelaide, Cape Town, Lisbon, San Diego, and Santiago. We used spectral-temporal metrics and neural network regression to calculate impervious, woody, and non-woody vegetation fractions, and mapped the WUI from those. Our maps were accurate for both 2020 WUI (area-adjusted overall accuracies 72.3 to 90.2%), and WUI changes (56.2 to 68.8%). WUI was most prevalent in San Diego (30.9%), and grew rapidly in four sites, especially near cities and coasts. Woody WUI was dominant in all sites except Adelaide, where herbaceous WUI dominated. More broadly, we showed that fractions derived from Landsat data can consistently map WUI growth. That is important given predicted increases in wildfires due to climate change and more human ignitions, and may help to mitigate severe wildfires in fire-prone Mediterranean ecosystems.

Fields of Study & Subjects

Fire effects on ecosystems Remote Sensing and Land Use Land Use and Ecosystem Services

Publication details

Journal / source
Science of Remote Sensing
Volume
13
Pages
100387–100387
Publication date
3 February 2026
Language
EN