Title :
The Application of Remote Sensing Technology to the Interpretation of Land Use for Rainfall-Induced Landslides Based on Genetic Algorithms and Artificial Neural Networks
Author :
Chen, Yie-Ruey ; Ni, Po-Ning ; Jing-Wen Chen ; Hsieh, Shun-Chieh
Author_Institution :
Dept. of Land Manage. & Dev., Chang Jung Christian Univ., Tainan, Taiwan
fDate :
6/1/2009 12:00:00 AM
Abstract :
In this paper, we explore the relationship between land use practices and landslides triggered by rainfall in eastern Taiwan. Before-and-after satellite images, combined with an artificial neural network method, enable the classification of land use and landslide zones. Genetic algorithms are used to evaluate the land use factors causing landslides. Using the geographic information system ArcGIS to support spatial reasoning, predictive maps are produced. The results suggest that the proposed method and procedures can be an effective tool for landslide monitoring and would be easily transferred to other similar applications.
Keywords :
genetic algorithms; geographic information systems; geomorphology; geophysical techniques; geophysics computing; image classification; neural nets; remote sensing; ArcGIS; artificial neural network method; eastern Taiwan; genetic algorithms; geographic information system; land use classification; land use factors; landslide zones classification; predictive maps; rainfall-induced landslides; remote sensing technology; spatial reasoning; Algorithm design and analysis; Artificial neural networks; Artificial satellites; Earth; Genetic algorithms; Geographic Information Systems; Intelligent networks; Monitoring; Remote sensing; Terrain factors; Artificial neural networks; genetic algorithms; geographic information system; image classification; landslides;
Journal_Title :
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
DOI :
10.1109/JSTARS.2009.2023802
