Final published version
Licence: CC BY: Creative Commons Attribution 4.0 International License
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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TY - JOUR
T1 - Analysis and Exploitation of Landforms for Improved Optimisation of Camera-Based Wildfire Detection Systems
AU - Heyns, A.M.
AU - du Plessis, W.
AU - Curtin, K.M.
AU - Kosch, M.
AU - Hough, G.
PY - 2021/9/30
Y1 - 2021/9/30
N2 - Tower-mounted camera-based wildfire detection systems provide an effective means of early forest fire detection. Historically, tower sites have been identified by foresters and locals with intimate knowledge of the terrain and without the aid of computational optimisation tools. When moving into vast new territories and without the aid of local knowledge, this process becomes cumbersome and daunting. In such instances, the optimisation of final site layouts may be streamlined if a suitable strategy is employed to limit the candidate sites to landforms which offer superior system visibility. A framework for the exploitation of landforms for these purposes is proposed. The landform classifications at 165 existing tower sites from wildfire detection systems in South Africa, Canada and the USA are analysed using the geomorphon technique, and it is noted that towers are located at or near certain landform types. A metaheuristic and integer linear programming approach is then employed to search for optimal tower sites in a large area currently monitored by the ForestWatch wildfire detection system, and these sites are then classified according to landforms. The results support the observations made for the existing towers in terms of noteworthy landforms, and the optimisation process is repeated by limiting the candidate sites to selected landforms. This leads to solutions with improved system coverage, achieved within reduced computation times. The presented framework may be replicated for use in similar applications, such as site-selection for military equipment, cellular transmitters, and weather radar. © 2021, The Author(s).
AB - Tower-mounted camera-based wildfire detection systems provide an effective means of early forest fire detection. Historically, tower sites have been identified by foresters and locals with intimate knowledge of the terrain and without the aid of computational optimisation tools. When moving into vast new territories and without the aid of local knowledge, this process becomes cumbersome and daunting. In such instances, the optimisation of final site layouts may be streamlined if a suitable strategy is employed to limit the candidate sites to landforms which offer superior system visibility. A framework for the exploitation of landforms for these purposes is proposed. The landform classifications at 165 existing tower sites from wildfire detection systems in South Africa, Canada and the USA are analysed using the geomorphon technique, and it is noted that towers are located at or near certain landform types. A metaheuristic and integer linear programming approach is then employed to search for optimal tower sites in a large area currently monitored by the ForestWatch wildfire detection system, and these sites are then classified according to landforms. The results support the observations made for the existing towers in terms of noteworthy landforms, and the optimisation process is repeated by limiting the candidate sites to selected landforms. This leads to solutions with improved system coverage, achieved within reduced computation times. The presented framework may be replicated for use in similar applications, such as site-selection for military equipment, cellular transmitters, and weather radar. © 2021, The Author(s).
KW - Facility location
KW - Fire detection
KW - Integer linear programming
KW - Landforms
KW - Maximal cover
KW - NSGA-II
KW - Cameras
KW - Deforestation
KW - Fires
KW - Geomorphology
KW - Integer programming
KW - Meteorological radar
KW - Military applications
KW - Site selection
KW - Towers
KW - Computation time
KW - Forest fire detection
KW - Integer Linear Programming
KW - Landform classification
KW - Local knowledge
KW - Optimisations
KW - System coverage
KW - Wildfire detection
U2 - 10.1007/s10694-021-01120-2
DO - 10.1007/s10694-021-01120-2
M3 - Journal article
VL - 57
SP - 2269
EP - 2303
JO - Fire Technology
JF - Fire Technology
SN - 0015-2684
ER -