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Forest fires are a pervasive and serious problem. Besides loss of life and extensive environmental damage, fires also result in substantial economic losses, not to mention property damage, injuries, displacements and hardships experienced by the affected citizens. This project proposes a low-cost in...
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| Format: | Thesis |
| Language: | English |
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Department of Electrical Engineering
2019
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| _version_ | 1867614051064872960 |
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| access_status_str | Open Access |
| author | Estebanez, Camarena Monica |
| author2 | Martinez, Peter |
| author_browse | Estebanez, Camarena Monica Martinez, Peter |
| author_facet | Martinez, Peter Estebanez, Camarena Monica |
| author_sort | Estebanez, Camarena Monica |
| collection | Thesis |
| description | Forest fires are a pervasive and serious problem. Besides loss of life and extensive environmental damage, fires also result in substantial economic losses, not to mention property damage, injuries, displacements and hardships experienced by the affected citizens. This project proposes a low-cost intelligent hyperspectral 3U CubeSat for the production of fire risk and burnt area maps. It applies Machine Learning algorithms to autonomously process images and obtain final data products on-board the satellite for direct transmission to users on the ground. Used in combination with other services such as EFFIS or AFIS, the system could considerably reduce the extent and consequences of forest fires. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/29881 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:45:53.460Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2019 |
| publishDateRange | 2019 |
| publishDateSort | 2019 |
| publisher | Department of Electrical Engineering |
| publisherStr | Department of Electrical Engineering |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/29881 PyrSat - Prevention and response to wild fires with an intelligent Earth observation CubeSat Estebanez, Camarena Monica Martinez, Peter Engineering Forest fires are a pervasive and serious problem. Besides loss of life and extensive environmental damage, fires also result in substantial economic losses, not to mention property damage, injuries, displacements and hardships experienced by the affected citizens. This project proposes a low-cost intelligent hyperspectral 3U CubeSat for the production of fire risk and burnt area maps. It applies Machine Learning algorithms to autonomously process images and obtain final data products on-board the satellite for direct transmission to users on the ground. Used in combination with other services such as EFFIS or AFIS, the system could considerably reduce the extent and consequences of forest fires. 2019-03-01T09:16:24Z 2019-03-01T09:16:24Z 2018 2019-02-25T08:59:55Z Master Thesis Masters MPhil http://hdl.handle.net/11427/29881 eng application/pdf Department of Electrical Engineering Faculty of Engineering and the Built Environment University of Cape Town |
| spellingShingle | Engineering Estebanez, Camarena Monica PyrSat - Prevention and response to wild fires with an intelligent Earth observation CubeSat |
| thesis_degree_str | Master's |
| title | PyrSat - Prevention and response to wild fires with an intelligent Earth observation CubeSat |
| title_full | PyrSat - Prevention and response to wild fires with an intelligent Earth observation CubeSat |
| title_fullStr | PyrSat - Prevention and response to wild fires with an intelligent Earth observation CubeSat |
| title_full_unstemmed | PyrSat - Prevention and response to wild fires with an intelligent Earth observation CubeSat |
| title_short | PyrSat - Prevention and response to wild fires with an intelligent Earth observation CubeSat |
| title_sort | pyrsat prevention and response to wild fires with an intelligent earth observation cubesat |
| topic | Engineering |
| url | http://hdl.handle.net/11427/29881 |
| work_keys_str_mv | AT estebanezcamarenamonica pyrsatpreventionandresponsetowildfireswithanintelligentearthobservationcubesat |