Characterization of forest canopy gaps caused by landslides using high density airborne laser scanning

High density airborne laser scanning (HDALS) data has revolutionized the characterization of tree growth anomalies and complex vegetation attributes including forest canopy gaps (FCG). They pose significant impact to forest eco-logical and monitoring activities. This paper presents a new approach ba...

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主要な著者: Gode, Ameya, Razak, Khamarrul Azahari
フォーマット: Conference or Workshop Item
出版事項: 2013
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オンライン・アクセス:http://eprints.utm.my/id/eprint/37499/
http://www.voronoi.com/isg2013/Programme%20schedule.html
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要約:High density airborne laser scanning (HDALS) data has revolutionized the characterization of tree growth anomalies and complex vegetation attributes including forest canopy gaps (FCG). They pose significant impact to forest eco-logical and monitoring activities. This paper presents a new approach based on object oriented technique to extract FCG characteristics caused by complex landslides in the French Alps. With a substantial point density across the forested landslides (170 points m-2), the method had an overall detection rate of 81% and over-predicted the reference FCG. The statistical tests revealed significant differences of FCG in landslide and non-landslide zones at the 95% confidence level and supported the field evidences. The results are promising given the complex interaction between landslide processes and forest ecosystem in the area. This study highlights the potential contribution of HDALS data to a regional ecological hazard assessment and can be alternative tool to analyze disrupted vegetation induced by geomorphic processes in a complex environment.