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<p>Wildfires represent a major environmental and socio-economic challenge in savanna ecosystems, particularly in sub-Saharan Africa, where fire regimes are driven by climatic variability and human activities. In northern Ghana, recurrent wildfires affect vegetation dynamics, soil systems, carbon cycling, and rural livelihoods, yet their integration into disaster risk management (DRM) frameworks remains limited. This study presents a systematic review of wildfire research in northern Ghana and synthesizes existing evidence to propose a conceptual remote sensing (RS) time-series framework for wildfire impact assessment and risk analysis. A total of 37 studies were selected following PRISMA-based screening and evaluated in terms of data sources, analytical methods, and thematic focus. The review highlights the use of multi-source satellite datasets (Landsat, Sentinel-2, MODIS) and key spectral indices, including NDVI, NBR/dNBR, land surface temperature, and net primary productivity. Time-series approaches such as BFAST and LandTrendr are identified as critical tools for detecting wildfire dynamics. The synthesis reveals persistent wildfire activity characterized by spatial heterogeneity, strong dry-season concentration, and non-linear temporal trends. Post-fire recovery is influenced more by soil moisture and ecological conditions than by fire frequency alone. Key limitations include reliance on proxy indicators, coarse-resolution climate data, and limited field validation. To address these gaps, a conceptual RS time-series framework integrating multi-indicator analysis, change detection, and socio-economic vulnerability through multi-criteria decision analysis is proposed. The framework provides a structured basis for future research and policy development, contributing to improved wildfire management and climate adaptation in savanna ecosystems.</p>

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A systematic review of wildfire dynamics in northern Ghana: toward an integrative remote sensing time-series framework for disaster risk management

  • 期刊论文

  • 发表日期：

    2026年4月8日

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  • Michael Stanley Peprah,
  • Cynthia Awewura Abavare

摘要

Wildfires represent a major environmental and socio-economic challenge in savanna ecosystems, particularly in sub-Saharan Africa, where fire regimes are driven by climatic variability and human activities. In northern Ghana, recurrent wildfires affect vegetation dynamics, soil systems, carbon cycling, and rural livelihoods, yet their integration into disaster risk management (DRM) frameworks remains limited. This study presents a systematic review of wildfire research in northern Ghana and synthesizes existing evidence to propose a conceptual remote sensing (RS) time-series framework for wildfire impact assessment and risk analysis. A total of 37 studies were selected following PRISMA-based screening and evaluated in terms of data sources, analytical methods, and thematic focus. The review highlights the use of multi-source satellite datasets (Landsat, Sentinel-2, MODIS) and key spectral indices, including NDVI, NBR/dNBR, land surface temperature, and net primary productivity. Time-series approaches such as BFAST and LandTrendr are identified as critical tools for detecting wildfire dynamics. The synthesis reveals persistent wildfire activity characterized by spatial heterogeneity, strong dry-season concentration, and non-linear temporal trends. Post-fire recovery is influenced more by soil moisture and ecological conditions than by fire frequency alone. Key limitations include reliance on proxy indicators, coarse-resolution climate data, and limited field validation. To address these gaps, a conceptual RS time-series framework integrating multi-indicator analysis, change detection, and socio-economic vulnerability through multi-criteria decision analysis is proposed. The framework provides a structured basis for future research and policy development, contributing to improved wildfire management and climate adaptation in savanna ecosystems.