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Landslide inventory mapping is essential for hazard assessment and mitigation. In most previous studies, landslide mapping was achieved by visual interpretation of aerial photos and remote sensing ima...
In this paper a method for automatic extraction of building roof boundaries is proposed, which combines LiDAR data and highresolution aerial images. The proposed method is based on three steps. In the...
Digital Elevation Models (DEMs) are considered as one of the most relevant geospatial data to carry out land-cover and land-use classification. This work deals with the application of a mathematical f...
The information in a pixel of satellite data within the instantaneous Field of View (IFOV) of the sensor is a mixture of different land cover types, and the individual land cover components can be est...
In this paper, a methodology is proposed for the geometric refinement of LiDAR building roof contours using high-resolution aerial images and Markov Random Field (MRF) models. The proposed methodology...
Bayesian methods coupled with Markovian frameworks has several applications in remote sensing images processing, such as the pixel level applications like filtering, segmentation and classification, a...
The objective of this study is to automatically detect changed areas caused by natural disasters from bi-temporal co-registered and calibrated TerraSAR-X data. The technique in this paper consists o...
Information technology is increasingly used to support civil infrastructure systems that are large, complex heterogeneous, and distributed. These dynamic systems include communication systems, roads, ...
Markov random field (MRF) is an effective method for description of local spatial-temporal dependence of image and has been widely used in land cover classification and change detection. However, ex...
MRF model is recognized as one of efficient tools for image classification. However, traditional MRF model prove to be limited for high resolution image classification. This paper presents a joint pix...

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