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Remote sensing of Wildland Vegetation Fires Using Near-Infrared Spectral Line Emissions from Electronically Excited Potassium Metal
Thesis (PhD)--Stellenbosch University, 2026.
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| Format: | Thesis |
| Language: | English |
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Stellenbosch : Stellenbosch University
2026
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| _version_ | 1867613983819694080 |
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| access_status_str | Open Access |
| author | Magidimisha, Edwin |
| author2 | Steenkamp, Christine |
| author_browse | Magidimisha, Edwin Steenkamp, Christine |
| author_facet | Steenkamp, Christine Magidimisha, Edwin |
| author_sort | Magidimisha, Edwin |
| collection | Thesis |
| dc_rights_str_mv | Stellenbosch University |
| description | Thesis (PhD)--Stellenbosch University, 2026. |
| format | Thesis |
| id | oai:scholar.sun.ac.za:10019.1/136269 |
| institution | Stellenbosch University (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:44:49.127Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from SUNScholar — Stellenbosch University Repository |
| publishDate | 2026 |
| publishDateRange | 2026 |
| publishDateSort | 2026 |
| publisher | Stellenbosch : Stellenbosch University |
| publisherStr | Stellenbosch : Stellenbosch University |
| record_format | dspace |
| source_str | SUNScholar — Stellenbosch University Repository |
| spelling | oai:scholar.sun.ac.za:10019.1/136269 Remote sensing of Wildland Vegetation Fires Using Near-Infrared Spectral Line Emissions from Electronically Excited Potassium Metal Magidimisha, Edwin Steenkamp, Christine Stellenbosch University. Faculty of Science. Dept. of Physics. Thesis (PhD)--Stellenbosch University, 2026. Magidimisha, E. 2026. Remote sensing of Wildland Vegetation Fires Using Near-Infrared Spectral Line Emissions from Electronically Excited Potassium Metal. Unpublished doctoral dissertation. Stellenbosch: Stellenbosch University [online]. Available: https://scholar.sun.ac.za/items/a211e71e-4392-4624-8ea4-fc8ba1d99f7a The thesis investigates the feasibility and performance of a Near-Infrared (NIR)-based fire detection system, which leverages the advances in ultra-narrow band spectral imaging technology to enhance wildfire monitoring and mitigation, and support the long-standing ecological role of fire. The proposed method focuses on detecting spectral line emissions from thermally excited Potassium (K) during biomass combustion, specifically at wavelengths of 766.48 nm (D2) and 769.89 nm (D1). The global rise and severity of wildfire incidents underscore the need for an affordable early warning system capable of detecting small fires before they reach catastrophic levels. While satellite-based thermal infrared sensors provide global coverage and valuable insights into fire dynamics and climate interactions, they are limited by restricted spatial and temporal resolution and the high cost of cooled infrared sensor systems that are used for enhanced detections. This work proposes a high-resolution, compact, cost-effective silicon-based NIR camera technology for detecting small-scale vegetation fires, suitable for both ground and satellite applications. Its affordability opens the possibility for deploying constellations of nanosatellites with improved revisit times, enabling a more responsive fire detection approach. Laboratory experiments were conducted using typical South African vegetation species to characterise their combustion spectra, with a focus on the Potassium doublet at 766.48nm (D2) and 769.89nm (D1). An inductively coupled plasma atomic emission spectroscopy (ICP-AES) process was used to quantify the Potassium concentration in vegetation species. Field measurements with the sensor prototype were performed to assess the sensor's performance under operational environmental conditions. The sensor was also tested for performance under simulated space environmental conditions to evaluate suitability and robustness for operation in outer space. A field experiment was conducted with the sensor integrated as payload into an unmanned aerial vehicle (UAV), the DJI M600 hexacopter, which was flown 200 m above the fire while capturing imagery remotely. In 2018, the experimental sensor prototype was successfully deployed aboard the ZACUBE-2 satellite to low Earth orbit (LEO) at an altitude of 500 km. This study presents a potential sensing technique that offers a route to high-resolution, highly cost-effective, and scalable fire detection systems for widespread deployment. Doctoral 2026-04-30T09:29:17Z 2026-04-30T09:29:17Z 2026-03 Thesis https://scholar.sun.ac.za/handle/10019.1/136269 en Stellenbosch University 158 pages application/pdf Stellenbosch : Stellenbosch University |
| spellingShingle | Magidimisha, Edwin Remote sensing of Wildland Vegetation Fires Using Near-Infrared Spectral Line Emissions from Electronically Excited Potassium Metal |
| title | Remote sensing of Wildland Vegetation Fires Using Near-Infrared Spectral Line Emissions from Electronically Excited Potassium Metal |
| title_full | Remote sensing of Wildland Vegetation Fires Using Near-Infrared Spectral Line Emissions from Electronically Excited Potassium Metal |
| title_fullStr | Remote sensing of Wildland Vegetation Fires Using Near-Infrared Spectral Line Emissions from Electronically Excited Potassium Metal |
| title_full_unstemmed | Remote sensing of Wildland Vegetation Fires Using Near-Infrared Spectral Line Emissions from Electronically Excited Potassium Metal |
| title_short | Remote sensing of Wildland Vegetation Fires Using Near-Infrared Spectral Line Emissions from Electronically Excited Potassium Metal |
| title_sort | remote sensing of wildland vegetation fires using near infrared spectral line emissions from electronically excited potassium metal |
| url | https://scholar.sun.ac.za/handle/10019.1/136269 |
| work_keys_str_mv | AT magidimishaedwin remotesensingofwildlandvegetationfiresusingnearinfraredspectrallineemissionsfromelectronicallyexcitedpotassiummetal |