MODELLING OF NATURAL FIRE OCCURRENCES: A CASE OF SOUTH AFRICA
In contemporary literature there have been growing concerns regarding preservations of natural ecosystems. Given the global growth in awareness of global warming, the need for natural fire prediction models has grown rapidly. Using South Africa as a case study, we evaluate the potential of integrati...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2020-08-01
|
| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/1477/2020/isprs-archives-XLIII-B3-2020-1477-2020.pdf |
| _version_ | 1819226569109929984 |
|---|---|
| author | T. Moyo W. Musakwa N. A. Nyathi E. Mpofu T. Gumbo |
| author_facet | T. Moyo W. Musakwa N. A. Nyathi E. Mpofu T. Gumbo |
| author_sort | T. Moyo |
| collection | DOAJ |
| description | In contemporary literature there have been growing concerns regarding preservations of natural ecosystems. Given the global growth in awareness of global warming, the need for natural fire prediction models has grown rapidly. Using South Africa as a case study, we evaluate the potential of integrating several natural fire prediction models and geographical information system (GIS) platforms. Initially, natural fire prone regions in South Africa were spatially demarcated basing on municipal historical data records. Thereafter, the natural fire prediction models were applied/tested in parallel to identify the best prediction models that give optimum results in predicting natural fires. The models were assessed for accuracy using historical data. Preliminary results reveal locations in the North West, Mpumalanga and Limpopo province had the highest recorded potential for natural fires. In conclusion, the work demonstrates huge potential of prediction models in informing the likelihood of natural fire outbreaks. Lastly, the work recommends the adoption of natural fire prediction models and the subsequent formulation and use of relevant future natural fire mitigation policies and techniques to avert disasters in time. |
| first_indexed | 2024-12-23T10:27:34Z |
| format | Article |
| id | doaj.art-ded89c6086364755a00b6af13500bcc2 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-23T10:27:34Z |
| publishDate | 2020-08-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-ded89c6086364755a00b6af13500bcc22022-12-21T17:50:32ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342020-08-01XLIII-B3-20201477148210.5194/isprs-archives-XLIII-B3-2020-1477-2020MODELLING OF NATURAL FIRE OCCURRENCES: A CASE OF SOUTH AFRICAT. Moyo0W. Musakwa1N. A. Nyathi2E. Mpofu3T. Gumbo4Department of Operations and Quality Management, University of Johannesburg. Corner Siemert & Beit Streets, Doornfontein 0184 Johannesburg, South AfricaFuture Earth and Ecosystem Services Research Group, Department of Urban and Regional Planning, University of Johannesburg, Corner Siemert & Beit Streets, Doornfontein 0184 Johannesburg, South AfricaDepartment of Geography, Environmental Management and Energy Studies, University of Johannesburg, University Road, Auckland Park, Johannesburg, Sout South AfricaFuture Earth and Ecosystem Services Research Group, Department of Urban and Regional Planning, University of Johannesburg, Corner Siemert & Beit Streets, Doornfontein 0184 Johannesburg, South AfricaDepartment of Urban and Regional Planning, University of Johannesburg, Corner Siemert & Beit Streets, Doornfontein 0184 Johannesburg, South AfricaIn contemporary literature there have been growing concerns regarding preservations of natural ecosystems. Given the global growth in awareness of global warming, the need for natural fire prediction models has grown rapidly. Using South Africa as a case study, we evaluate the potential of integrating several natural fire prediction models and geographical information system (GIS) platforms. Initially, natural fire prone regions in South Africa were spatially demarcated basing on municipal historical data records. Thereafter, the natural fire prediction models were applied/tested in parallel to identify the best prediction models that give optimum results in predicting natural fires. The models were assessed for accuracy using historical data. Preliminary results reveal locations in the North West, Mpumalanga and Limpopo province had the highest recorded potential for natural fires. In conclusion, the work demonstrates huge potential of prediction models in informing the likelihood of natural fire outbreaks. Lastly, the work recommends the adoption of natural fire prediction models and the subsequent formulation and use of relevant future natural fire mitigation policies and techniques to avert disasters in time.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/1477/2020/isprs-archives-XLIII-B3-2020-1477-2020.pdf |
| spellingShingle | T. Moyo W. Musakwa N. A. Nyathi E. Mpofu T. Gumbo MODELLING OF NATURAL FIRE OCCURRENCES: A CASE OF SOUTH AFRICA The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | MODELLING OF NATURAL FIRE OCCURRENCES: A CASE OF SOUTH AFRICA |
| title_full | MODELLING OF NATURAL FIRE OCCURRENCES: A CASE OF SOUTH AFRICA |
| title_fullStr | MODELLING OF NATURAL FIRE OCCURRENCES: A CASE OF SOUTH AFRICA |
| title_full_unstemmed | MODELLING OF NATURAL FIRE OCCURRENCES: A CASE OF SOUTH AFRICA |
| title_short | MODELLING OF NATURAL FIRE OCCURRENCES: A CASE OF SOUTH AFRICA |
| title_sort | modelling of natural fire occurrences a case of south africa |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B3-2020/1477/2020/isprs-archives-XLIII-B3-2020-1477-2020.pdf |
| work_keys_str_mv | AT tmoyo modellingofnaturalfireoccurrencesacaseofsouthafrica AT wmusakwa modellingofnaturalfireoccurrencesacaseofsouthafrica AT nanyathi modellingofnaturalfireoccurrencesacaseofsouthafrica AT empofu modellingofnaturalfireoccurrencesacaseofsouthafrica AT tgumbo modellingofnaturalfireoccurrencesacaseofsouthafrica |