Land cover classification with an expert system approach using Landsat ETM imagery: a case study of Trabzon

The main objective of this study is to generate a knowledge base which is composed of user-defined variables and included raster imagery, vector coverage, spatial models, external programs, and simple scalars and to develop an expert classification using Landsat 7 (ETM+) imagery for land cover class...

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Bibliographic Details
Published in:Environmental monitoring and assessment 2010, Vol.160 (1-4), p.431-438
Main Authors: Kahya, Oguzhan, Bayram, Bulent, Reis, Selcuk
Format: Article
Language:English
Subjects:
Accuracy
Animal, plant and microbial ecology
Atmospheric Protection/Air Quality Control/Air Pollution
Biological and medical sciences
Case studies
Cities
Classification
Datasets
Earth and Environmental Science
Ecology
Ecotoxicology
Environment
Environmental Management
Environmental monitoring
Environmental Monitoring - methods
Expert system
Expert systems
Fundamental and applied biological sciences. Psychology
General aspects. Techniques
Geodetics
Geography
Land
Land cover classification
Land use
Landsat
Landsat ETM
Landsat satellites
Monitoring/Environmental Analysis
Photogrammetry
Remote sensing
Satellite Communications
Statistical analysis
Teledetection and vegetation maps
Trabzon
Turkey
Urban areas
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Summary:The main objective of this study is to generate a knowledge base which is composed of user-defined variables and included raster imagery, vector coverage, spatial models, external programs, and simple scalars and to develop an expert classification using Landsat 7 (ETM+) imagery for land cover classification in a part of Trabzon city. Expert systems allow for the integration of remote-sensed data with other sources of geo-referenced information such as land use data, spatial texture, and digital elevation model to obtain greater classification accuracy. Logical decision rules are used with the various datasets to assign class values for each pixel. Expert system is very suitable for the work of image interpretation as a powerful means of information integration. Landsat ETM data acquired in the year 2000 were initially classified into seven classes for land cover using a maximum likelihood decision rule. An expert system was constructed to perform post-classification sorting of the initial land cover classification using additional spatial datasets such as land use data. The overall accuracy of expert classification was 95.80%. Individual class accuracy ranged from 75% to 100% for each class.
ISSN:0167-6369
1573-2959
DOI:10.1007/s10661-008-0707-6