Spatial Clustering of Vegetation Fire Intensity Using MODIS Satellite Data
This work analyses the spatial clustering of fire intensity in Zimbabwe, using remotely sensed Moderate Resolution Imaging Spectroradiometer (MODIS) active fire occurrence data. In order to investigate the spatial pattern of fire intensity, MODIS-derived fire radiative power (FRP) was utilized. A l...
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| Format: | research article |
| Language: | English |
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Multidisciplinary Digital Publishing Institute
2023
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| Online Access: | https://cris.library.msu.ac.zw//handle/11408/5621 https://doi.org/10.3390/atmos13121972 |
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| author | Pedzisai Kowe Upenyu Naume Mupfiga Onisimo Mutanga Timothy Dube |
| author2 | Department of Geography, Environmental Sustainability and Resilience Building, Midlands State University, Gweru 9055, Zimbabwe |
| author_facet | Department of Geography, Environmental Sustainability and Resilience Building, Midlands State University, Gweru 9055, Zimbabwe Pedzisai Kowe Upenyu Naume Mupfiga Onisimo Mutanga Timothy Dube |
| author_sort | Pedzisai Kowe |
| collection | DSpace |
| description | This work analyses the spatial clustering of fire intensity in Zimbabwe, using remotely
sensed Moderate Resolution Imaging Spectroradiometer (MODIS) active fire occurrence data. In order to investigate the spatial pattern of fire intensity, MODIS-derived fire radiative power (FRP) was utilized. A local indicator of spatial autocorrelation method, the Getis-Ord (Gi*) spatial statistic, was applied to show the spatial distribution of high and low fire intensity clusters. Analysis of the
relationship between topographic variables, vegetation type, agroecological zones and fire intensity was done. According to the study’s findings, the majority (44%) of active fires detected in the study area in 2019 were of low-intensity (cold spots), and the majority (49.3%) of them occurred in shrubland. High-intensity fires (22%) primarily occurred in the study area’s eastern and western regions. The study findings demonstrate the utility of spatial statistics methods in conjunction with satellite fire
data in detecting clusters of high and low-intensity fires (hot spots and cold spots). |
| format | research article |
| id | ir-11408-5621 |
| institution | My University |
| language | English |
| publishDate | 2023 |
| publisher | Multidisciplinary Digital Publishing Institute |
| record_format | dspace |
| spelling | ir-11408-56212023-05-05T07:09:25Z Spatial Clustering of Vegetation Fire Intensity Using MODIS Satellite Data Pedzisai Kowe Upenyu Naume Mupfiga Onisimo Mutanga Timothy Dube Department of Geography, Environmental Sustainability and Resilience Building, Midlands State University, Gweru 9055, Zimbabwe Discipline of Geography and Environmental Science, School of Agricultural Earth and Environmental Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville, Pietermaritzburg 3209, South Africa Discipline of Geography and Environmental Science, School of Agricultural Earth and Environmental Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville, Pietermaritzburg 3209, South Africa nstitute of Water Studies, Department of Earth Sciences, The University of the Western Cape, Private Bag X17, Bellville 7535, South Africa active fire occurrence fire intensity fire radiative power spatial clustering hot spots cold spots spatial data climate change This work analyses the spatial clustering of fire intensity in Zimbabwe, using remotely sensed Moderate Resolution Imaging Spectroradiometer (MODIS) active fire occurrence data. In order to investigate the spatial pattern of fire intensity, MODIS-derived fire radiative power (FRP) was utilized. A local indicator of spatial autocorrelation method, the Getis-Ord (Gi*) spatial statistic, was applied to show the spatial distribution of high and low fire intensity clusters. Analysis of the relationship between topographic variables, vegetation type, agroecological zones and fire intensity was done. According to the study’s findings, the majority (44%) of active fires detected in the study area in 2019 were of low-intensity (cold spots), and the majority (49.3%) of them occurred in shrubland. High-intensity fires (22%) primarily occurred in the study area’s eastern and western regions. The study findings demonstrate the utility of spatial statistics methods in conjunction with satellite fire data in detecting clusters of high and low-intensity fires (hot spots and cold spots). 13 12 1 19 2023-05-05T07:09:24Z 2023-05-05T07:09:24Z 2022-11-25 research article https://cris.library.msu.ac.zw//handle/11408/5621 https://doi.org/10.3390/atmos13121972 en Atmosphere 2073-4433 open Multidisciplinary Digital Publishing Institute |
| spellingShingle | active fire occurrence fire intensity fire radiative power spatial clustering hot spots cold spots spatial data climate change Pedzisai Kowe Upenyu Naume Mupfiga Onisimo Mutanga Timothy Dube Spatial Clustering of Vegetation Fire Intensity Using MODIS Satellite Data |
| title | Spatial Clustering of Vegetation Fire Intensity Using MODIS Satellite Data |
| title_full | Spatial Clustering of Vegetation Fire Intensity Using MODIS Satellite Data |
| title_fullStr | Spatial Clustering of Vegetation Fire Intensity Using MODIS Satellite Data |
| title_full_unstemmed | Spatial Clustering of Vegetation Fire Intensity Using MODIS Satellite Data |
| title_short | Spatial Clustering of Vegetation Fire Intensity Using MODIS Satellite Data |
| title_sort | spatial clustering of vegetation fire intensity using modis satellite data |
| topic | active fire occurrence fire intensity fire radiative power spatial clustering hot spots cold spots spatial data climate change |
| url | https://cris.library.msu.ac.zw//handle/11408/5621 https://doi.org/10.3390/atmos13121972 |
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