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

## TL;DR

This study combines geospatial tools and local knowledge to map and analyze forest fire severity in Tanzania's Western Usambara Mountains over 10 years.

## Contribution

The study introduces an integrated method combining remote sensing and socio-economic data to assess forest fire sources and severity in tropical forests.

## Key findings

- Farm preparation and charcoal production are the main causes of forest fires in the region.
- Burn severity maps showed 15.86% of the reserves were burned over 10 years.
- Vegetation loss was significant, with dNDVI and NBR/NDVI time series showing declines of 0.21 to 0.36.

## Abstract

Despite the numerous negative effects of tropical forest fires in Tanzania, the sources and effects remain insufficiently documented. This study aimed to develop an integrated approach that combines geospatial tools and socio-economic data to assess the sources and effects of forest fires and map burn severity and its trends over 10 years in West Usambara Mountain Forests. Three approaches including Participatory Rural Appraisal (PRA), satellite image analysis, and direct observation were used to generate information on spatial and temporal forest fire severity. Findings revealed that farm preparation (38.2%) and charcoal preparation (21.2%) are the primary source of these forest fires. Burn severity maps showed 32.12% to 20.31% of combined high and low severity areas, with a total burned area of 3,296.96 hectares, accounting for 15.86% of the reserves. The differenced Normalized Difference Vegetation Index (dNDVI) maps revealed 36.30% to 21.10 of high and low severity areas, while post-fire NBR and NDVI time series indicated a significant vegetation loss (0.21 to 0.36). This study demonstrates the integration of remote sensing and socio-economic approaches to enhance forest fire management, conservation, policy enforcement, and community awareness that can be upscaled to other forest areas for effective management.