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Spatial data and related technologies have proven to be crucial for effective collaborative decision-making in disaster management. However, there are currently substantial problems with availability, access and usage of reliable, up-to-date and accurate data for disaster management. This is a very important aspect to disaster response as timely, up-to-date(More)
In this article, the possibility of using artificial neural networks for road detection from high resolution satellite images is tested on a part of RGB Ikonos and Quick-Bird images from Kish Island and Bushehr Harbour respectively. Then, the effects of different input parameters on network's ability are verified to find out optimum input vector for this(More)
Nowadays, automatic extraction of man-made objects such as buildings and roads in urban areas has become a topic of growing interest for photogrammetric and computer vision community. Researches in this domain started from late 1980s and used quite different types of source images ranging from single intensity images, color images, laser range images to(More)
—Common endmember extraction algorithms presume that the number of materials present is either known or may be predetermined by using spectral databases or other approaches. In this letter, we propose a new method called genetic orthogonal projection (GOP) for endmember extraction in imaging spectrom-etry. GOP is based on a fully unsupervised approach and(More)
Attaining geospatial information is a challenge for many scientific practitioners. Such information is a necessary tool for spatial decision making. Remote Sensing (RS) is the leading art/science providing the data for many global or local applications such as: green house effect, pollution, military, urban and land use. Graphical elements of geospatial(More)
In this article, a new method for road extraction from high resolution Quick Bird and IKONOS pan-sharpened satellite images is presented. The proposed methodology consists of two separate stages of road detection and road vectorization. Neural networks are applied on high resolution IKONOS and Quick-Bird images for road detection. This paper has endeavoured(More)
The need to geo-spatial data in different applications particularly for knowledge-based sustainable development is considerable. However, various problems encountered with production, dissemination and accessing geo-spatial data makes users to face with many difficulties when intending to use them. Spatial Data Infrastructure (SDI) is introduced as a(More)
The number of high resolution space imageries, in the civilian market is growing fast.This images have great interest in the photogrammetric and remote sensing communities. The problem with this images for many users, at the present time is the lack of sensor calibration information and precise ephemeris data. Consequently it is not possible to apply the(More)