Automatic landslide recognition through Optimum-Path Forest
计算机科学
路径(计算)
随机森林
计算机视觉
作者
Rodrigo José Pisani,Paulina Setti Riedel,Kelton A. P. Costa,Rodrigo Y. M. Nakamura,Clayton R. Pereira,Gustavo Henrique de Rosa,João Paulo Papa
出处
期刊:International Geoscience and Remote Sensing Symposium日期:2012-07-22卷期号:: 6228-6231被引量:3
标识
DOI:10.1109/igarss.2012.6352681
摘要
In this paper we shed light over the problem of landslide automatic recognition using supervised classification, and we also introduced the OPF classifier in this context. We employed two images acquired from Geoeye-MS satellite at March-2010 in the northwest (high steep areas) and north sides (pipeline area) covering the area of Duque de Caxias city, Rio de Janeiro State, Brazil. The landslide recognition rate has been assessed through a cross-validation with 10 runnings. In regard to the classifiers, we have used OPF against SVM with Radial Basis Function for kernel mapping and a Bayesian classifier. We can conclude that OPF, Bayes and SVM achieved high recognition rates, being OPF the fastest approach.