Quality of life in urban environments is closely related to vegetation cover. The Urban growth and its related environmental problems, planners are forced to implement policies to improve the quality of urban environment. Thus, vegetation mapping for planning and managing urban is critical. Given the spectral complexity of the urban environment and the sparse vegetation in these areas, to gener...

Attempts to analyze urban features and to classify land use and land cover directly from high-resolution satellite data with traditional computer classification techniques have proven to be inefficient for two primary reasons. First, urban landscapes are composed of complex features. Second, traditional classifiers employ spectral information based on single pixel value and ignore a great amoun...

In this paper, we introduce the concept and an implementation of geospatial 3D image spaces as new type of native urban models. 3D image spaces are based on collections of georeferenced RGB-D imagery. This imagery is typically acquired using multi-view stereo mobile mapping systems capturing dense sequences of street level imagery. Ideally, image depth information is derived using dense image m...

In this paper we describe a novel interactive modelling technique, which allows the non-expert user to create plausible models of urban scenes with 2D image operations only. This technique may be treated as an enhancement of the famous image based modelling and photo editing (IBPE) (Oh et al., 2001) approach towards more automation and ease to use. The are several contributions in this paper. F...

A series of studies in urban growth involve the segmentation of urban built up area. This segmentation may used as input to geospatial models to quantify and map urban growth. The segmentation may be used as well to study the dynamics of urban growth on a certain time span. We present in this work a method to segment urban built up area from Landsat multi-spectral images. Our method uses the ex...

the main goal of the present study was to implement a hybrid pattern of cellular automata model and particle swarm optimization algorithm based on tm and etm+ imagery of landsat satellite from 1988 to 2010 for simulating the urban sprawling. in this study, an alternative model was implemented in two ways: the first method was based on two images (1988 and 2010) and the second one was based on t...

Urban morphology as “knowledge of urban form”, has notable capacities to participate in comprehension and management of urban development, specially in this days cities have faced with unprecedented changes that create problem for cities inhabitants in perception and creation of cities image and also have confronted designers with a serious question to control and guide new constructions. Use o...

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...

Mapping land cover in urban areas helps understanding the complexity of the urban landscape and environments. High resolution image data effectively captures such urban complexities and offers great potential for mapping the urban features in detail. The land cover information derived from remote sensing data has proven its usefulness for a wide range of urban applications. The traditional pixe...

Object-based image analysis is becoming increasingly popular in classification of very high resolution (VHR) imagery over urban areas. The spectral resolution of VHR imagery (generally they possesses 1 pan and 4 multispectral bands), however, is limited and insufficient for differentiating many urban land cover classes. Due to the spectral similarity of building roofs, roads and parking lots, s...