Title
Multiscale remote sensing data segmentation and post-segmentation change detection based on logical modeling: Theoretical exposition and experimental results for forestland cover change analysis
Abstract
Quantification of forestland cover extents, changes and causes thereof are currently of regional and global research priority. Remote sensing data (RSD) play a significant role in this exercise. However, supervised classification-based forest mapping from RSD are limited by lack of ground-truth- and spectral-only-based methods. In this paper, first results of a methodology to detect change/no change based on unsupervised multiresolution image transformation are presented. The technique combines directional wavelet transformation texture and multispectral imagery in an anisotropic diffusion aggregation or segmentation algorithm. The segmentation algorithm was implemented in unsupervised self-organizing feature map neural network. Using Landsat TM (1986) and ETM+ (2001), logical-operations-based change detection results for part of Mau forest in Kenya are presented. An overall accuracy for change detection of 88.4%, corresponding to kappa of 0.8265, was obtained. The methodology is able to predict the change information a-posteriori as opposed to the conventional methods that require land cover classes a priori for change detection. Most importantly, the approach can be used to predict the existence, location and extent of disturbances within natural environmental systems.
Year
DOI
Venue
2008
10.1016/j.cageo.2007.05.021
Computers & Geosciences
Keywords
Field
DocType
data segmentation,change detection,change information a-posteriori,forestland cover extent,segmentation algorithm,directional wavelet transformation texture,logical-operations-based change detection result,post-segmentation change detection,forestland cover change analysis,mau forest,supervised classification-based forest mapping,unsupervised multiresolution image transformation,logical modeling,land cover class,ground truth,wavelet transform,anisotropic diffusion,neural network,multispectral imagery,object oriented
Data mining,Thematic Mapper,Data segment,Change detection,Segmentation,Computer science,Multispectral image,Remote sensing,Artificial neural network,Land cover,Wavelet
Journal
Volume
Issue
ISSN
34
7
Computers and Geosciences
Citations 
PageRank 
References 
10
0.89
14
Authors
3
Name
Order
Citations
PageRank
Yashon Ouma1152.39
S. S. Josaphat2100.89
Ryutaro Tateishi37813.21