Mapping Forest Fire Impact with Geospatial Tools in Mountain Forests

Jim Crocker
8th June, 2025

Mapping Forest Fire Impact with Geospatial Tools in Mountain Forests

Based on the Normalized Difference Vegetation Index (NDVI), the generated burn severity maps visualize the spatial distribution of vegetation health and fire impact across the Shagayu (a), Magamba (b), and Mkusu (c) forest reserves.

Image adapted from: Mkiwa et al. / CC BY (Source)

Key Findings

  • In West Usambara Mountain Forests, Tanzania, researchers used satellite images and local community input to map wildfire impact and understand its causes
  • They found that everyday activities like farming and charcoal production trigger most fires, leading to significant vegetation loss over more than 3,300 hectares
[1] A recent study by researchers at Sokoine University of Agriculture and Universiti Kebangsaan Malaysia tackles the lasting challenge of tropical forest fires in Tanzania by using a mix of satellite remote sensing and community-based data to better understand and manage these fires. In West Usambara Mountain Forests, the study focused on mapping fire severity over a ten‐year period and uncovering the underlying human-related causes of these fires. The innovative approach combines geospatial analysis, which uses satellite imagery to track changes in vegetation, with socio-economic methods such as Participatory Rural Appraisal (PRA) and direct on-ground observations. This study addresses a critical problem: while tropical forest fires are known to have severe environmental and economic impacts, their precise sources and effects have not been fully documented. In the context of increasing incidences of forest fires worldwide, understanding the specific circumstances and resulting damage in a local setting becomes essential to protect biodiversity, support sustainable livelihoods, and inform policy decisions. The researchers approached the problem by integrating three main methods. First, Participatory Rural Appraisal (PRA) involved local community members in sharing traditional knowledge and firsthand observations about fire occurrences. This method identified that nearly 38.2% of the forest fires resulted from farm preparation activities, and 21.2% were linked to charcoal production. These activities indicate that routine agricultural practices and energy needs can inadvertently lead to forest fires. By directly engaging local communities, the researchers were able to collect detailed information about the timing, location, and human activities associated with the fires. Second, satellite image analysis provided an objective, detailed view of the forest landscape over time. The study used the differenced Normalized Difference Vegetation Index (dNDVI) to evaluate changes in vegetation health before and after fires. The NDVI is a common measurement in remote sensing that shows how green an area is, reflecting the amount of living plant matter. By comparing NDVI values over time, the research demonstrated significant vegetation loss, with changes in NDVI values ranging from 0.21 to 0.36. This decline indicates a dramatic decrease in plant health post-fire and helps quantify the impact of the fires across the landscape. Third, direct observation complemented these data-driven approaches, giving the study a solid grounding in reality. By verifying satellite imagery results and incorporating firsthand accounts from local residents, the researchers ensured that their mapping of fire severity was both accurate and contextually relevant. Their burn severity maps revealed that high and low severity fire areas together covered between 20.31% and 32.12% of the affected regions, totalling approximately 3,296.96 hectares, which means that roughly 15.86% of the forest reserves experienced significant damage from fires. These integrated methods provide detailed insights into both the causes and effects of the tropical forest fires. The inclusion of socio-economic data helps bridge the gap between remote sensing—a tool that has been used effectively in various forest fire studies—and ground reality, echoing evidence from earlier research. For instance, studies conducted in the Mediterranean region of Türkiye[2] and in Çanakkale province[3] utilized satellite images from Sentinel-2 and Landsat-8/9, respectively, to generate burn severity maps and calculate affected areas. Both those studies employed indices like the difference Normalized Burn Ratio (dNBR) and dNDVI to assess fire impact, showing significant decreases in vegetation density and changes in pollutant levels after fires. The current study not only confirms the value of these remote sensing techniques but also demonstrates the added strength of integrating community knowledge and socio-economic data to create a more comprehensive picture. The combination of these approaches offers several advantages. The satellite-based methods allow for a consistent and broad examination of changes over time, crucial for tracking trends over a decade. This long-term view is key for developing policies that mitigate the risk and impact of future fires. Meanwhile, the socio-economic insights point directly to the human behaviors—including farm and charcoal production practices—that can be addressed through targeted education and alternative livelihood programs. By understanding that nearly 60% of the fires have roots in daily human activities, community awareness campaigns and the enforcement of sustainable practices become clear priorities. Furthermore, the study underscores the potential for upscaling this integrated model to other forested areas. The methods used here can be adapted to regions facing similar challenges, benefiting fire management policies across various ecosystems. The collaboration between academic institutions, local communities, and remote sensing technologies points to a future where environmental management is both scientifically rigorous and socially inclusive. In summary, this study presents a practical framework for addressing the complex issue of tropical forest fires. By merging geospatial analysis with socio-economic data, it offers a detailed look into both the intensity of fire impacts and the human factors that drive them. The findings support and extend earlier remote sensing studies, demonstrating that while satellite imagery is invaluable for detecting changes in vegetation and mapping fire severity, the inclusion of direct community input is essential for fully understanding and managing the causes of these fires. This integrated approach not only enhances forest fire management and conservation efforts in West Usambara Mountain Forests but also provides a replicable model that can bolster environmental policies in other vulnerable regions.

EnvironmentEcology

References

Main Study

1) Integrating geospatial tools in mapping forest fire severity and burned areas in the Western Usambara Mountain Forests, Lushoto, Tanzania

Published 6th June, 2025

https://doi.org/10.1371/journal.pone.0311865

Related Studies

2) Mapping burn severity and monitoring CO content in Türkiye's 2021 Wildfires, using Sentinel-2 and Sentinel-5P satellite data on the GEE platform.

https://doi.org/10.1007/s12145-023-00933-9

3) Spatial and statistical analysis of burned areas with Landsat-8/9 and Sentinel-2 satellites: 2023 Çanakkale forest fires.

https://doi.org/10.1007/s10661-024-13474-5


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