Intraurban land-use change and factors affecting it are critical subjects in land-use planning. If unplanned, such changes can reduce the quality of life and spatial justice and ultimately lead to urban unsustainability. This paper aims to identify factors influencing unsustainable land-use change and analyze the intensity of such changes based on those factors. The artificial neural network an...

The arrival of new-generation, high-spatial-resolution satellite imagery (e.g., Ikonos) has opened up new opportunities for detailed mapping and analysis of urban land use. Drawing on the traditional approach used in aerial photointerpretation, this study investigates an “object-oriented” method to classify a large urban area into detailed land-use categories. Spatial metrics and texture measur...

Radar and Landsat data were used to classify land cover in north central Ethiopia. Both images were registered and resampled to 12.5 m spatial resolution. Maximum Likelihood Classifier (MLC) and C4.5 algorithm were applied. The original radar data produced low overall classification accuracy (66%). To improve this classification accuracy, de-speckling and texture measures were used for image en...

Texture features have long been used in remote sensing applications to represent and retrieve image regions similar to a query region. Various representations of texture have been proposed based on the Fourier power spectrum, spatial co-occurrence, wavelets, Gabor filters, etc. These representations vary in their computational complexity and their suitability for representing different region t...

Change extraction of building is needed to revise building data effectively. Many change detection algorithms use height difference analysis using temporal data such as LIDAR. However, remarkable changes of buildings cannot be detected in urban dense areas. On the other hand, building textures might change with higher possibility. However, the change cannot be detected due to influences of shad...

Fractal dimension is an index which can be used to characterize urban areas. The use of the curve of scaling behaviour is less common. However, its shape gives local information about the morphology of the built-up area. This paper suggests a method based on a k-medoid for clustering these curves. It is applied to forty-nine wards of European cities, and shows that the curves add interesting in...

Texture models are potentially very useful for automated urban data revision. We propose a ‘model-based change detection algorithm’ using three-dimensional urban data. In this algorithm, temporal images are projected on a common three-dimensional geometry model and the latest textures are compared with previous textures to detect an object’s change accurately. In addition, a shadow simulation w...

Conventional spectral-based classification methods have significant limitations in the digital classification of urban land-use and land-cover classes from high-resolution remotely sensed data because of the lack of consideration given to the spatial properties of images. To recognize the complex distribution of urban features in high-resolution image data, texture information consisting of a g...