As an intermediate step between raw remote sensing data and digital urban maps, remote sensing data classification has been a challenging and long-standing research problem in the community of remote sensing. In this work, an effective classification method is proposed for classifying high-resolution remote sensing data over urban areas. Starting from high resolution multi-spectral images and 3...

We introduce a method to texture 3D urban models with photographs that even works for Google Streetview images and can be done with currently available free software. This allows realistic texturing, even when it is not possible or cost-effective to (re)visit a scanned site to take textured scans or photographs. Mapping a photograph onto a 3D model requires knowledge of the intrinsic and extrin...

Adaptive fusion of new information in a 3D urban scene is an important goal to achieve in computer vision, graphics, and visualization. In this work we acquire new image pairs of a scene from closer distances and extract 3D models of successively higher resolutions. We present a new hierarchical approach to register these texture-mapped 3D models with a coarse 3D texture mapped model of an urba...

In the paper we address the applied problem of detecting and recognizing street name plates in urban images by a generic approach to structural object detection and recognition. A structured object is detected using a boosting approach and false positives are filtered using a specific method called the texture transform. In a second step the subregion containing the key information, here the te...

The spatial and temporal distribution of land cover is a fundamental dataset for urban ecological research. An expert (or hypothesis testing) system has been used with Landsat Thematic Mapper (TM) data to derive a land cover classification for the semiarid Phoenix metropolitan portion of the Central Arizona-Phoenix Long Term Ecological Research (CAP LTER) site. Expert systems allow for the inte...

In the context of increasing greenhouse gas emission and global demographic change with the simultaneous trend to urbanization, it is a big challenge for cities around the world to perform modifications in energy supply chain and building characteristics resulting in reduced energy consumption and carbon dioxide mitigation. Sound knowledge of energy resource demand and supply including its spat...

One of the results of urban renovation is population displacement. If these renovations lead to live prosperous social classes, it is called gentrification. In this regard one of the urban renovation strategies is gentrification that is equal in "the acceptability of texture in public opinion" and is known as a synonym of "improving the quality of living environment for residents and citizens"....

Accurate analyses concerning the ecological value of urban railway sites are required to ensure a sustainable development of inner urban open space. One problem in this context is the great heterogeneity of such areas. New opportunities to investigate heterogeneous urban areas arose with the advent of geometric very high resolution (VHR) satellite data. A bundle of panchromatic and multispectra...

In this paper, we investigate the usefulness of high-resolution multispectral satellite imagery for classification of urban and suburban areas and present a fuzzy logic methodology to improve classification accuracy. Panchromatic and multispectral IKONOS image datasets are analyzed for two urban locations in this study. Both multispectral and pan-sharpened multispectral images are first classif...

The objective of this research is to assess the multitemporal very high resolution single polarization SAR data for urban land cover/land-use mapping using a novel knowledge-based SEM algorithm. Three-date RADARSAT-2 ultra-fine beam SAR data were collected over the rural-urban fringe of Greater Toronto Area. A modified Stochastic Expectation-Maximization (SEM) algorithm which employs an adaptiv...