The Application of Remote Sensing Technology to the Interpretation of Land Use for Rainfall-Induced Landslides Based on Genetic Algorithms and Artificial Neural Networks

被引：40

作者：

Chen, Yie-Ruey ^{[1
]}

Chen, Jing-Wen ^{[2
]}

Hsieh, Shun-Chieh ^{[1
]}

Ni, Po-Ning ^{[1
]}

机构：

[1] Chang Jung Christian Univ, Dept Land Management & Dev, Tainan 71101, Taiwan

[2] Natl Cheng Kung Univ, Dept Civil Engn, Tainan 70101, Taiwan

来源：

IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING | 2009年 / 2卷 / 02期

关键词：

Artificial neural networks; genetic algorithms; geographic information system; image classification; landslides; CLASSIFICATION; MODELS; DAMAGE;

D O I：

10.1109/JSTARS.2009.2023802

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：87 / 95

页数：9

共 32 条

[1] Remote sensing-based neural network mapping of tsunami damage in Aceh, Indonesia [J].