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National-scale spatiotemporal patterns of vegetation fire occurrences using MODIS satellite data
As the risk of climate change increases, robust fire monitoring methods become critical for fire management purposes. National-scale spatiotemporal patterns of the fires and how they relate to vegetation and environmental conditions are not well understood in Zimbabwe. This paper presents a spatiall...
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Published in: | PloS one 2024-03, Vol.19 (3), p.e0297309-e0297309 |
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description | As the risk of climate change increases, robust fire monitoring methods become critical for fire management purposes. National-scale spatiotemporal patterns of the fires and how they relate to vegetation and environmental conditions are not well understood in Zimbabwe. This paper presents a spatially explicit method combining satellite data and spatial statistics in detecting spatiotemporal patterns of fires in Zimbabwe. The Emerging Hot Spot Analysis method was utilized to detect statistically significant spatiotemporal patterns of fire occurrence between the years 2002 and 2021. Statistical analysis was done to determine the association between the spatiotemporal patterns and some environmental variables such as topography, land cover, land use, ecoregions and precipitation. The highest number of fires occurred in September, coinciding with Zimbabwe's observed fire season. The number of fires significantly varied among seasons, with the hot and dry season (August to October) recording the highest fire counts. Additionally, although June, July and November are not part of the official fire season in Zimbabwe, the fire counts recorded for these months were relatively high. This new information has therefore shown the need for revision of the fire season in Zimbabwe. The northern regions were characterized by persistent, oscillating, diminishing and historical spatiotemporal fire hotspots. Agroecological regions IIa and IIb and the Southern Miombo bushveld ecoregion were the most fire-prone areas. The research findings also revealed new critical information about the spatiotemporal fire patterns in various terrestrial ecoregions, land cover, land use, precipitation and topography and highlighted potential areas for effective fire management strategies. |
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National-scale spatiotemporal patterns of the fires and how they relate to vegetation and environmental conditions are not well understood in Zimbabwe. This paper presents a spatially explicit method combining satellite data and spatial statistics in detecting spatiotemporal patterns of fires in Zimbabwe. The Emerging Hot Spot Analysis method was utilized to detect statistically significant spatiotemporal patterns of fire occurrence between the years 2002 and 2021. Statistical analysis was done to determine the association between the spatiotemporal patterns and some environmental variables such as topography, land cover, land use, ecoregions and precipitation. The highest number of fires occurred in September, coinciding with Zimbabwe's observed fire season. The number of fires significantly varied among seasons, with the hot and dry season (August to October) recording the highest fire counts. Additionally, although June, July and November are not part of the official fire season in Zimbabwe, the fire counts recorded for these months were relatively high. This new information has therefore shown the need for revision of the fire season in Zimbabwe. The northern regions were characterized by persistent, oscillating, diminishing and historical spatiotemporal fire hotspots. Agroecological regions IIa and IIb and the Southern Miombo bushveld ecoregion were the most fire-prone areas. The research findings also revealed new critical information about the spatiotemporal fire patterns in various terrestrial ecoregions, land cover, land use, precipitation and topography and highlighted potential areas for effective fire management strategies.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0297309</identifier><identifier>PMID: 38547131</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Biology and Life Sciences ; Climate Change ; Climatic changes ; Computer and Information Sciences ; Earth Sciences ; Ecology and Environmental Sciences ; Ecosystem ; Engineering and Technology ; Environmental aspects ; Fires ; Forecasts and trends ; Forest fires ; Global temperature changes ; Influence ; People and Places ; Seasons ; Social Sciences ; Strategic planning (Business) ; Zimbabwe</subject><ispartof>PloS one, 2024-03, Vol.19 (3), p.e0297309-e0297309</ispartof><rights>Copyright: © 2024 Mupfiga et al. 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National-scale spatiotemporal patterns of the fires and how they relate to vegetation and environmental conditions are not well understood in Zimbabwe. This paper presents a spatially explicit method combining satellite data and spatial statistics in detecting spatiotemporal patterns of fires in Zimbabwe. The Emerging Hot Spot Analysis method was utilized to detect statistically significant spatiotemporal patterns of fire occurrence between the years 2002 and 2021. Statistical analysis was done to determine the association between the spatiotemporal patterns and some environmental variables such as topography, land cover, land use, ecoregions and precipitation. The highest number of fires occurred in September, coinciding with Zimbabwe's observed fire season. The number of fires significantly varied among seasons, with the hot and dry season (August to October) recording the highest fire counts. Additionally, although June, July and November are not part of the official fire season in Zimbabwe, the fire counts recorded for these months were relatively high. This new information has therefore shown the need for revision of the fire season in Zimbabwe. The northern regions were characterized by persistent, oscillating, diminishing and historical spatiotemporal fire hotspots. Agroecological regions IIa and IIb and the Southern Miombo bushveld ecoregion were the most fire-prone areas. 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Mutanga, Onisimo ; Dube, Timothy</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c641t-bb96e2302d4947d85eedc23dbf7cad248c2f4b7cce59236482a1f24355eb34083</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Analysis</topic><topic>Biology and Life Sciences</topic><topic>Climate Change</topic><topic>Climatic changes</topic><topic>Computer and Information Sciences</topic><topic>Earth Sciences</topic><topic>Ecology and Environmental Sciences</topic><topic>Ecosystem</topic><topic>Engineering and Technology</topic><topic>Environmental aspects</topic><topic>Fires</topic><topic>Forecasts and trends</topic><topic>Forest fires</topic><topic>Global temperature changes</topic><topic>Influence</topic><topic>People and Places</topic><topic>Seasons</topic><topic>Social Sciences</topic><topic>Strategic planning (Business)</topic><topic>Zimbabwe</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mupfiga, Upenyu Naume</creatorcontrib><creatorcontrib>Mutanga, Onisimo</creatorcontrib><creatorcontrib>Dube, Timothy</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Opposing Viewpoints Resource Center</collection><collection>Science (Gale in Context)</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mupfiga, Upenyu Naume</au><au>Mutanga, Onisimo</au><au>Dube, Timothy</au><au>Mishra, Bhogendra</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>National-scale spatiotemporal patterns of vegetation fire occurrences using MODIS satellite data</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2024-03-28</date><risdate>2024</risdate><volume>19</volume><issue>3</issue><spage>e0297309</spage><epage>e0297309</epage><pages>e0297309-e0297309</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>As the risk of climate change increases, robust fire monitoring methods become critical for fire management purposes. 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Additionally, although June, July and November are not part of the official fire season in Zimbabwe, the fire counts recorded for these months were relatively high. This new information has therefore shown the need for revision of the fire season in Zimbabwe. The northern regions were characterized by persistent, oscillating, diminishing and historical spatiotemporal fire hotspots. Agroecological regions IIa and IIb and the Southern Miombo bushveld ecoregion were the most fire-prone areas. 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subjects | Analysis Biology and Life Sciences Climate Change Climatic changes Computer and Information Sciences Earth Sciences Ecology and Environmental Sciences Ecosystem Engineering and Technology Environmental aspects Fires Forecasts and trends Forest fires Global temperature changes Influence People and Places Seasons Social Sciences Strategic planning (Business) Zimbabwe |
title | National-scale spatiotemporal patterns of vegetation fire occurrences using MODIS satellite data |
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