Object-based vs. per-pixel classification of aster imagery for land cover mapping in semi-arid areas

Mustafa M. El Abbas; E. Csaplovics

doi:10.1117/12.898317

26 October 2011 Object-based vs. per-pixel classification of aster imagery for land cover mapping in semi-arid areas

Mustafa M. El Abbas, E. Csaplovics

Proceedings Volume 8181, Earth Resources and Environmental Remote Sensing/GIS Applications II; 81810O (2011) https://doi.org/10.1117/12.898317
Event: SPIE Remote Sensing, 2011, Prague, Czech Republic

Abstract

Due to complexity and spectral similarity in semi-arid areas, land cover mapping with remotely sensed data encounters serious problems when applying methods based on spectral information and ignore spatial information. A research was conducted in the Blue Nile area of Sudan to evaluate the effectiveness of Object-Based analysis (OB) approaches versus pixel based approach to generate Land Use Land Cover (LULC) thematic maps based on multi-spectral imagery data. Maximum Likelihood Classifier (MLC) was applied to examine if the spectral properties of the selected classes alone can be discriminated effectively. Nine land cover classes were generated with only about 82% overall accuracy. Different segmentation strategies were applied with the OB paradigm that might be effective to separate similar spectral values into a basic unclassified image objects in groups of relatively homogeneous pixels based on shape and compactness criterion at different scales. The segmented objects assigned to different classes with methods of membership functions and Nearest Neighbor Classifiers (NNC). The membership functions (RB) provided highly overall classification accuracy (95%), while NNC achieved about 89% accuracy. This study emphasized that the OB methods applied in this study provides more accurate results than the classical per-pixel approach especially when user's expert knowledge is presented.

Citation Download Citation

Mustafa M. El Abbas and E. Csaplovics "Object-based vs. per-pixel classification of aster imagery for land cover mapping in semi-arid areas", Proc. SPIE 8181, Earth Resources and Environmental Remote Sensing/GIS Applications II, 81810O (26 October 2011); https://doi.org/10.1117/12.898317

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
12 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Image segmentation

Image classification

Image processing

Agriculture

Vegetation

Image analysis

Image processing algorithms and systems

Show All Keywords

Keywords/Phrases

Search In:

Publication Years