Landslide detection with multi-dimensional histogram equalization for multispectral remotely sensed imagery

Cheng Feng Lin, Hsuan Ren

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Landslides are serious natural hazards. They usually cause significant properties damage and sometimes also fatalities. For reconstruction and rescue purposes, landslide detection is very important. Normalized Difference Vegetation Index (NDVI) is widely used for this purpose. If NDVI significantly decreases within a short period, that area will be considered as landslide candidate. However, remote sensing images always contain atmospheric effects which affect the NDVI estimation. In this study, we propose a multi-dimensional histogram equalization algorithm as a pre-process step. It modifies multispectral images collected under different atmospheric conditions to have similar spectrum for the same land cover. A set of SPOT images is adopted for experiments and preliminary results show the proposed method can reduce the misclassification rate.

Original languageEnglish
Title of host publication33rd Asian Conference on Remote Sensing 2012, ACRS 2012
Pages1583-1589
Number of pages7
StatePublished - 2012
Event33rd Asian Conference on Remote Sensing 2012, ACRS 2012 - Pattaya, Thailand
Duration: 26 Nov 201230 Nov 2012

Publication series

Name33rd Asian Conference on Remote Sensing 2012, ACRS 2012
Volume2

Conference

Conference33rd Asian Conference on Remote Sensing 2012, ACRS 2012
Country/TerritoryThailand
CityPattaya
Period26/11/1230/11/12

Keywords

  • Landslides
  • Multi-dimensional histogram equalization
  • Multispectral
  • NDVI
  • Remote sensing

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