Landslide identification based on FORMOSAT-2 multispectral imagery by wavelet-based texture feature extraction

Li Wei Chang, Pi Fuei Hsieh, Ching Weei Lin

研究成果: Conference contribution

5 引文 斯高帕斯(Scopus)

摘要

To identify landslides for disaster monitoring, FORMOSAT-2 imagery has the advantages of low cost and frequent revisit over any other satellite imagery currently available in Taiwan. However, its four spectral bands are not capable enough to distinguish landslides from other ground cover types, for example, thin rivers. In this study, we attempt to overcome the spectral incapability of FORMOSAT-2 imagery from the standpoint of classification. First, we explore more discriminative features, such as texture and topographical features, in order to improve class separability. Texture features are extracted from the FORMOSAT-2 imagery itself using the log-polar wavelet packet transformation whereas a topographical feature slope is derived from an auxiliary Digital Elevation Model (DEM) dataset. Second, a contextual classifier that combines spectral and spatial information is used since this type of classifier is appropriate for our case of homogeneous object identification. Our results have been validated partially by field investigation on several sites. Experiments show that our approach has given a significant improvement over the spectral approach.

原文English
主出版物標題2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS
發行者Institute of Electrical and Electronics Engineers Inc.
頁面3300-3303
頁數4
ISBN(列印)0780395107, 9780780395107
DOIs
出版狀態Published - 2006
事件2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS - Denver, CO, United States
持續時間: 2006 七月 312006 八月 4

出版系列

名字International Geoscience and Remote Sensing Symposium (IGARSS)

Other

Other2006 IEEE International Geoscience and Remote Sensing Symposium, IGARSS
國家/地區United States
城市Denver, CO
期間06-07-3106-08-04

All Science Journal Classification (ASJC) codes

  • 電腦科學應用
  • 地球與行星科學(全部)

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