Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 135-139, 2015
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XL-1-W5/135/2015/
doi:10.5194/isprsarchives-XL-1-W5-135-2015
© Author(s) 2015. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
10 Dec 2015
TARGETED SATELLITE IMAGE CLASSIFICATION FOR URBAN MAP UPDATING USING GEOSPATIAL INFORMATION SYSTEM PLATFORM
M. Davoodianidaliki and A. Abedini Dept. of Geomatics Engineering, Faculty of engineering, University of Tehran N. Kargar St. Jalale al e Ahmad St., Tehran: 14395515, Iran
Keywords: Change Detection, Updating, Urban Maps, High Resolution, Satellite Image, Image Processing, SVM, Targeted Classification Abstract. Traditional map production and updating methods which usually involve field surveying and/or photogrammetry, while established and used for a long time, are time consuming and costly. Whereas satellite imagery have provided great amounts of data with high resolutions suitable for different geospatial applications. This paper focuses on taking advantage of geospatial information systems for enabling automated supervised classification of satellite images in urban areas. Such ability is provided through some attributes that determine whether features in current map have changed or not. The overall process consists of three stages: i: Geo database upgrade for addition of some attributes; ii: Classification by Support Vector Machine (SVM) and iii: Change analysis. The proposed method is applied on a sample data of Worldview 3 image of Hormozgan, Iran. The obtained results show that using such method not only can automate supervised classification but also can decrease misclassification errors through local training. Also its independent of classification method provides the ability to deploy other classification methods.
Conference paper (PDF, 971 KB)


Citation: Davoodianidaliki, M. and Abedini, A.: TARGETED SATELLITE IMAGE CLASSIFICATION FOR URBAN MAP UPDATING USING GEOSPATIAL INFORMATION SYSTEM PLATFORM, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-1/W5, 135-139, doi:10.5194/isprsarchives-XL-1-W5-135-2015, 2015.

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