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Title: SMOKE AND FOG CLASSIFICATION IN FOREST MONITORING USING HIGH SPATIAL RESOLUTION IMAGES
SMOKE AND FOG CLASSIFICATION IN FOREST MONITORING USING HIGH SPATIAL RESOLUTION IMAGES

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Julia Ahlen
10.5593/sgem2022/2.1/s08.16
10.5593/sgem2022/2.1
1314-2704
978-619-7603-40-8
English
22
2.1
•    Prof. DSc. Oleksandr Trofymchuk, UKRAINE 
•    Prof. Dr. hab. oec. Baiba Rivza, LATVIA
Geoinformatics
Forest fires cause major damage to human habitats and forest ecosystems. Early detection may prevent serious consequences of fast fire spread. Although there are many smoke detection algorithms employed by various optical remote sensing systems, there is still a major misdetection of images containing fog. Fog exhibits similar visual characteristics to smoke. Furthermore, when monitoring dense forests many smoke detection algorithms would fail in robust recognition due to fog covering the trees at dawn. There have been more or less successful attempts to separate smoke from a fog in optical imagery however, these algorithms are strongly connected to a specific application area or use a semiautomatic approach. This work aims to propose a novel smoke and fog separation algorithm based on color space model calculation followed by rule-based shape analysis. In addition, the internal properties of the smoke candidate areas are examined for linear attenuation towards higher energy wavelength. Those areas are then investigated for internal shape properties such as convex hull and eccentricity. Several tests conducted on various high-resolution aerial images suggest that the system is effective in differentiating smoke and fog and thus considered to be robust in early fire detection in forest areas.
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This work is funded by Geospatial Information Science Group at the University of Gavle, Sweden.
conference
https://doi.org/10.5593/sgem2022/2.1/s08.16
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Proceedings of 22nd International Multidisciplinary Scientific GeoConference SGEM 2022
22nd International Multidisciplinary Scientific GeoConference SGEM 2022, 04 - 10 July, 2022
Proceedings Paper
STEF92 Technology
International Multidisciplinary Scientific GeoConference SGEM
SWS Scholarly Society; Acad Sci Czech Republ; Latvian Acad Sci; Polish Acad Sci; Serbian Acad Sci and Arts; Natl Acad Sci Ukraine; Natl Acad Sci Armenia; Sci Council Japan; European Acad Sci, Arts and Letters; Acad Fine Arts Zagreb Croatia; Croatian Acad Sci and Arts; Acad Sci Moldova; Montenegrin Acad Sci and Arts; Georgian Acad Sci; Acad Fine Arts and Design Bratislava; Turkish Acad Sci.
131-138
04 - 10 July, 2022
website
8483
smoke, fog, detection, image, rule-based