Texture classification of Mediterranean land cover


Berberoglu S. , CURRAN P. J. , LLOYD C. D. , ATKINSON P. M.

INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, cilt.9, ss.322-334, 2007 (SCI İndekslerine Giren Dergi) identifier identifier

  • Cilt numarası: 9 Konu: 3
  • Basım Tarihi: 2007
  • Doi Numarası: 10.1016/j.jag.2006.11.004
  • Dergi Adı: INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION
  • Sayfa Sayısı: ss.322-334

Özet

Maximum likelihood (ML) and artificial neural network (ANN) classifiers were applied to three Landsat Thematic Mapper (TM) image sub-scenes (termed urban, agricultural and semi-natural) of Cukurova, Turkey. Inputs to the classifications comprised (i) spectral data and (ii) spectral data in combination with texture measures derived on a per-pixel basis. The texture measures used were: the standard deviation and variance and statistics derived from the co-occurrence matrix and the variogram. The addition of texture measures increased classification accuracy for the urban sub-scene but decreased classification accuracy for agricultural and semi-natural sub-scenes. Classification accuracy was dependent on the nature of the spatial variation in the image sub-scene and, in particular, the relation between the frequency of spatial variation and the spatial resolution of the imagery. For Mediterranean land, texture classification applied to Landsat TM imagery may be appropriate for the classification of urban areas only. (C) 2006 Elsevier B.V. All rights reserved.