Spatio-temporal dynamics, drivers of wildfire occurrence and distribution in the northern savannah ecological zone of Ghana

Nawaa, Aline M., Folega, Fousseni, Kobo-bah, Amos, Walz, Yvonne, Wala, Kperkouma and Amponsah, Amos, (2025). Spatio-temporal dynamics, drivers of wildfire occurrence and distribution in the northern savannah ecological zone of Ghana. Scientific African, 27(E02580), 1-13

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  • Sub-type Journal article
    Author Nawaa, Aline M.
    Folega, Fousseni
    Kobo-bah, Amos
    Walz, Yvonne
    Wala, Kperkouma
    Amponsah, Amos
    Title Spatio-temporal dynamics, drivers of wildfire occurrence and distribution in the northern savannah ecological zone of Ghana
    Appearing in Scientific African
    Volume 27
    Issue No. E02580
    Publication Date 2025-03
    Place of Publication Amesterdam
    Publisher Elsevier
    Start page 1
    End page 13
    Language eng
    Abstract This study rigorously investigates the spatio-temporal dynamics and determinants of wildfire occurrences in the Northern Savannah Ecological Zone of Ghana from 2000 to 2021, leveraging remote sensing data and advanced statistical analyses. The study utilized Collection 6 MODIS datasets, including MCD64A1 for burned area mapping and MCD14DL for active fire locations. Temporal trends were analyzed using the Mann-Kendall test and Sen’s slope estimator to detect significant changes. Over the 21 years, 432,153 active fires were recorded, resulting in a total burn area of 515,822.7 km². The peak wildfire occurrences were noted in 2011, with 28,943 fires, and in 2002, with a burn area of 33,883.4 km². Spatial analysis revealed concentrated wildfire hotspots in the northwest-central regions, while cold spots were primarily located in the Upper East region. Temporal trend analysis using the Mann-Kendall test indicated a significant decreasing trend in burn area over time (p = 0.015). Key drivers of wildfire occurrence and distribution were identified through Geographically Weighted Regression (GWR), which high lighted distance to settlements, slope, distance to roads, maximum temperature, and elevation as significant factors. The GWR model exhibited an improved fit over the global Ordinary Least Squares (OLS) model, as evidenced by a lower Akaike Information Criterion corrected (AICc) value, indicating enhanced model performance. The observed spatial heterogeneity in wildfire patterns underscores the necessity for localized modeling approaches and targeted management strategies. This study offers critical insights for the formulation of effective wildfire management policies in Ghana’s Savannah zone, emphasizing the need to consider both environmental and anthropogenic factors in wildfire prevention and mitigation efforts.
    UNBIS Thesaurus CLIMATE CHANGE
    REMOTE SENSING
    Keyword Wildfires
    Savannah zone
    Spatio-temporal dynamics
    Geographically weighted regression (GWR)
    Copyright Holder The Author(s)
    Copyright Year 2025
    Copyright type Creative commons
    DOI 10.1016/j.sciaf.2025.e02580
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    Created: Thu, 01 May 2025, 17:26:50 JST by Aarti Basnyat on behalf of UNU EHS