Land use classification utilizing thermal band-based on wavelet transform

الملخص EN

Thermal band is generally not applied for land use classification, in the application of remote sensing, due to its inferior spatial resolution.

However, thermal band data possess valuable informations, especially in the expression of the temperature of the Earth's surface and land cover and hence cannot be neglected.

The present study aims at the interpretation of data within the thermal band in the land use classification after merging with other bands and by using wavelet transform method.

The study focuses on two main parts; the first is the use of Mahalanobis Distance (Mah) method for land use classification.

The method gave good results when applied to multi-spectral TM images of Mosul city, in comparison with other conventional methods.

The second part is the adoption of a new method for merging thermal band TM6 with the remaining bands, on the basis of wavelet transform and the use of different wavelet filters such as Daubechies ('db4'), Symlet ('sym4'), and Coiflet ('coif4').

Finally, the method of merging thermal band with other band and using wavelete transform is compared with other conventional methods, like principle component analyses (PCA).

It was noted that using wavelet transform, the classification accuracy is better.

The best results are obtained in the third level, when using 'db4' wavelet filter.

It has also been noted that urban areas are completely separated from the barren regions, in addition to the separation of different agricultural regions.

This means that the thermal band informations are of great value in the classification of land use.