Investigation on automatic change detection using pixel-changes and DSM-changes with ALOS-PRISM triplet images

A new algorithm for automatic change detection is presented. It detects a pixel-change and DSM-change from two orthoimages and two DSMs, then it extracts the polygons in elevation-changed areas. Pixel-change is detected by using least squares fitting technique. This method can extract the visible ch...

Full description

Saved in:
Bibliographic Details
Published inInternational archives of the photogrammetry, remote sensing and spatial information sciences. Vol. XL-7/W2; pp. 213 - 217
Main Authors Sasagawa, A., Baltsavias, E., Kocaman Aksakal, S., Wegner, J. D.
Format Journal Article
LanguageEnglish
Published Copernicus Publications 01.01.2013
Online AccessGet full text

Cover

Loading…
More Information
Summary:A new algorithm for automatic change detection is presented. It detects a pixel-change and DSM-change from two orthoimages and two DSMs, then it extracts the polygons in elevation-changed areas. Pixel-change is detected by using least squares fitting technique. This method can extract the visible changed areas between two orthoimages, while DSM-change is detected by difference DSM. From these two changes, polygons in elevation-changed areas are extracted using the longest matched line selection techniques. This method can automatically detect not only visible changed areas such as vegetated areas, new road construction areas and so on, but also elevation-changed areas such as new building construction, land improvement areas and so on with footprint polygon extraction. We have tested our method using the two sets of ALOS-PRISM triplet images observed over a testfield in Tsukuba, Japan. We confirmed that this method has an effect finding changed areas. Also we compared the number of extracted polygons between manual operation and our automatic method.
ISSN:2194-9034
1682-1750
2194-9034
DOI:10.5194/isprsarchives-XL-7-W2-213-2013