Please use this identifier to cite or link to this item:
|Title:||Land Cover Change Detection Thresholds for Landsat Data Samples|
|Authors:||RASI Rastislav; KISSIYAR Ouns; VOLLMAR MICHAEL|
|Citation:||2011 6th International Workshop on the Analysis of Multi-temporal Remote Sensing Images (Multi-Temp) Proceedings p. 205-208|
|Publisher:||Institute of Electrical and Electronics Engineers (IEEE)|
|Type:||Articles in periodicals and books|
|Abstract:||This paper presents the results of research on common change detection techniques. More specifically it looks into the optimization of reshold values for these investigated change detection techniques: image differencing, normalized image differencing, image ratioing, normalized variance differencing, normalized spectral Euclidean distance and Tasseled Cap parameters difference. The threshold values were optimized for the detection of land cover change/nochange based on the comparison with an existing validated classification of five broad land cover classes. For this study a sample set of 104 image pairs was selected, each of 20 x 20 km, cut from Landsat TM/ETM+ imagery series. An object based approach was applied for the land cover change detection. The results showed that the threshold of normalized variance difference had most stable values across the sample set, however applying optimized thresholds the achieved accuracy was comparable for all tested methods.|
|JRC Institute:||Sustainable Resources|
Files in This Item:
There are no files associated with this item.
Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.