Object-Oriented Image Analysis
Classifying Urban Land Cover and Land Use
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Creating land-cover and land-use maps for urban areas has always been challenging due to the complexity of an urban landscape. The greater availability of remotely sensed high-resolution imagery and recent advances in object-oriented analysis allow for more detail than ever before in urban image classification. This book explores object-oriented land-cover and land-use classifications with one-meter resolution Ikonos imagery. First, three different ways of classifying land cover, with varying inclusion of ancillary building and road data, are examined. Second, the spatial relations of the land...
Creating land-cover and land-use maps for urban areas has always been challenging due to the complexity of an urban landscape. The greater availability of remotely sensed high-resolution imagery and recent advances in object-oriented analysis allow for more detail than ever before in urban image classification. This book explores object-oriented land-cover and land-use classifications with one-meter resolution Ikonos imagery. First, three different ways of classifying land cover, with varying inclusion of ancillary building and road data, are examined. Second, the spatial relations of the land-cover information are examined to derive land use. Accuracy assessments, as well as statistical and visual evaluations, for the classifications show that the object-oriented approach works well for classifying an urban area. The results confirm the observed trend in the literature to move away from traditional pixel-based techniques for urban image classification in exchange for object-oriented methods. This book will be useful to those who want to develop new ways of efficiently classifying complex urban areas, using object-oriented image classification techniques.
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