Detecting Fire-Caused Forest Loss in a Moroccan Protected Area

Abstract

Fire is a concern for the sustainability of dry forests such as those of the Mediterranean region, especially under warming climate and high human use. We used data derived from Landsat and MODIS sensors to assess forest changes in the Talassemtane National Park (TNP) in North Africa from 2003–2018. The Talassemtane National Park is a protected area in northern Morocco, a biodiverse, mountainous region with endemic species of concern such as the Moroccan fir (Abies marocana) and Barbary macaque (Macaca sylvanus). To help the managers of the TNP better understand how the forest has been impacted by fire vs. other disturbances, we combined information from remotely derived datasets. The Hansen Global Forest Change (GFC) data are a global resource providing annual forest change, but without specifying the causes of change. We compared the GFC data to MODIS wildfire data from Andela’s Global Fire Atlas (GFA), a new global tool to identify fire locations and progression. We also analyzed surface reflectance-corrected Landsat imagery to calculate fire severity and vegetation death using Relative Differenced Normalized Burn Ratio analysis (RdNBR). In the park, GFC data showed a net loss of 1695 ha over 16 years, corresponding to an approximately 0.3% annual loss of forest. The GFA identified nine large fires that covered 4440 ha in the study period, coinciding with 833 ha of forest loss in the same period. Within these fires, detailed image analysis showed that GFA fire boundaries were approximately correct, providing the first quantitative test of GFA accuracy outside North America. High-severity fire, as determined by RdNBR analysis, made up about 32% of burned area. Overall, the GFA was validated as a useful management tool with only one non-detected wildfire in the study period; wildfires were linked to approximately 49% of the forest loss. This information helps managers develop conservation strategies based on reliable data about forest threats.

Keywords

• Landsat
• MODIS
• Global Fire Atlas
• Hansen Global Forest Change
• forest loss
• fire severity