Post-classification comparison of land cover using multitemporal Landsat and ASTER imagery: the case of Kahramanmara angstrom, Turkey


ALPHAN H. , Doygun H., ÜNLÜKAPLAN Y.

ENVIRONMENTAL MONITORING AND ASSESSMENT, cilt.151, ss.327-336, 2009 (SCI İndekslerine Giren Dergi) identifier identifier identifier

  • Cilt numarası: 151
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1007/s10661-008-0274-x
  • Dergi Adı: ENVIRONMENTAL MONITORING AND ASSESSMENT
  • Sayfa Sayısı: ss.327-336

Özet

This study assessed land cover (LC) changes in Kahramanmara angstrom (K.Mara angstrom) and its environs by using multitemporal Landsat and ASTER imagery, respectively belong to 1989, 2000 and 2004. A priori defined nine land cover classes in the classification scheme were urban and built-up, forest, sparsely vegetated areas, grassland, vegetated stream beds, unvegetated stream beds, bare areas, crop fields, and water bodies. Individual classifications were employed using the combination of both unsupervised and supervised classification methods. Iterative Self Organizing Data Analysis (ISODATA) was used to reduce spectral variation in the scenes arising from complex pattern of crop fields. Maximum Likelihood classifier was used in the LC classification of the individual images. Image pairs of consecutive dates were compared by overlaying the thematic LC maps and cross-tabulating the LC statistics. Urbanization and expansion of agriculture were the major reasons for the dramatic LC conversions. The amount of conversion from crop fields to water occurred as large as 927.67 ha, accounting for 73% of the total land-to-water conversion. Conversions to agriculture have mainly been occurred from grasslands and sparsely vegetated areas as large as 1,314.95 and 1,325.84 ha, respectively. Urban coverage doubled in this period as a result of 1,443.45 ha of increase. Urban area increased in the second period from 2,920 to 3,526 ha. Conversions to agriculture occurred at high amounts. A total of 1,075.79 ha area changed from sparsely vegetated areas to crop fields. A landscape-level environmental monitoring scheme based on satellite remote sensing was proposed for effective environmental resource management.