Date

2004

Author

Şencan, Seçil

Metadata

Show full item record

Item Usage Stats

113
views

44
downloads

Cite This

A decision tree (DT) classification approach was used to identify summer (August) crop types in an agricultural area near Karacabey (Bursa), Turkey from multi-temporal images. For the analysis, Landsat 7 ETM+ images acquired in May, July, and August 2000 were used. In addition to the original bands, NDVI, PCA, and Tasselled Cap Transformation bands were also generated and included in the classification procedure. Initially, the images were classified on a per-pixel basis using the multi-temporal masking technique together with the DT approach. Then, the classified outputs were applied a field-based analysis and the class labels of the fields were directly entered into the Geographical Information System (GIS) database. The results were compared with the classified outputs of the three dates of imagery generated using a traditional maximum likelihood (ML) algorithm. It was observed that the proposed approach provided significantly higher overall accuracies for the May and August images, for which the number of classes were low. In May and July, the DT approach produced the classification accuracies of 91.10% and 66.15% while the ML classifier produced 84.38% and 63.55%, respectively. However, in August nearly the similar overall accuracies were obtained for the ML (70.82%) and DT (69.14%) approaches. It was also observed that the use of additional bands for the proposed technique improved the separability of the sugar beet, tomato, pea, pepper, and rice classes.

Subject Keywords

Classes of Plants.

URI

http://etd.lib.metu.edu.tr/upload/12605503/index.pdf
https://hdl.handle.net/11511/14522

Collections

Graduate School of Natural and Applied Sciences, Thesis