Title
Object-oriented classification and application in land use classification using SPOT-5 PAN imagery
Abstract
High-resolution remotely sensed data have been actively employed in urban land use/cover. Object-oriented classification techniques based on image segmentation are being actively studied in the high-resolution image process and interpretation to extract a variety of thematic information. Different from the pixel-based image analysis, the processing of the object-oriented method is based on image object or segment, not single pixel. The object-oriented classification includes two consecutive processes. An image is subdivided into separated regions according to the spectral and spatial heterogeneity in the image segmentation process. Then the objects are assigned to a specific class according to the class's detailed description in the image classification process. As a case study, the study area is a pail of the planning Beijing Olympic Games Cottage, which has changed greatly with the advent of the year of 2008. The panchromatic SPOT-5 image in August of 2002 is segmented and these segments then are classified to hierarchically linked objects by the eCognition software. The overall classification accuracy is up to 87%
Year
DOI
Venue
2004
10.1109/IGARSS.2004.1370370
IGARSS
Keywords
Field
DocType
geophysical techniques,remote sensing,beijing olympic games cottage,urban land use/cover,object-oriented classification,land use,spot-5 pan imagery,ecognition software,image resolution,land use classification,image segmentation,thematic information,pixel-based image analysis,high-resolution image process,image classification,spot-5 imagery,panchromatic spot-5 image,geophysical signal processing,high-resolution remotely sensed data,ad 2002 08,ad 2008,high resolution,spatial heterogeneity,image analysis
Computer vision,Image texture,Computer science,Panchromatic film,Remote sensing,Image segmentation,Software,Thematic map,Artificial intelligence,Pixel,Contextual image classification,Image resolution
Conference
Volume
Issue
ISSN
5
null
2153-6996
ISBN
Citations 
PageRank 
0-7803-8742-2
6
0.65
References 
Authors
3
4
Name
Order
Citations
PageRank
Ziyu Wang13420.68
Wenxia Wei260.99
Shuhe Zhao3263.66
Xiuwan Chen43318.04