Comparison and evaluation of object-based and pixel-based analysis of LIDAR data and large scale aerial imagery in urban area

Document Type : Persian Original Article

Authors

Faculty. of Geomatics Engineering, K.N. Toosi University, Tehran, Iran

Abstract

The information extraction of urban features is important for managers and city planners. In this
way, we can use remote sensing data and related methods in order to detection of these features efficiently.
In this study, Object-based and pixel-based detection of urban features is done by integration of LIDAR data
and large-scale aerial optical images at the level of decision.Pixel based and object based analaysis is done
based on decision tree classification with consideration of shadow and without it.This study demonstrates
ability of LIDAR data tto solve problems caused by the shadow in urban area. The accuracy of object based
method is more than pixel based method in two classifications. In object based analysis over all accuracy in
both classifications are similar, but classification with shadow class is better than other method. Over all
accuracy of pixel_based classification without shadow class is 0.91 which is the highest accuracy in
pixel_based analysis.

Keywords

Journal of Soft Computing and Information Technology
Volume 4, Issue 3 - Serial Number 3
January 2018
Pages 103-112

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