We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Urban Change Analysis with Multi-Sensor Multispectral Imagery.
- Authors
Yuqi Tang; Liangpei Zhang
- Abstract
An object-based method is proposed in this paper for change detection in urban areas with multi-sensor multispectral (MS) images. The co-registered bi-temporal images are resampled to match each other. By mapping the segmentation of one image to the other, a change map is generated by characterizing the change probability of image objects based on the proposed change feature analysis. The map is then used to separate the changes from unchanged areas by two threshold selection methods and k-means clustering (k = 2). In order to consider the multi-scale characteristics of ground objects, multi-scale fusion is implemented. The experimental results obtained with QuickBird and IKONOS images show the superiority of the proposed method in detecting urban changes in multi-sensor MS images.
- Subjects
CHINA; CLIMATE change; MULTISPECTRAL imaging; CITIES &; towns; IMAGE segmentation; K-means clustering
- Publication
Remote Sensing, 2017, Vol 9, Issue 3, p252
- ISSN
2072-4292
- Publication type
Article
- DOI
10.3390/rs9030252