Mohammad Javad Valadan Zoej

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1 Using SDI and Web-Based System to Facilitate Disaster Management A. Mansourian, A. Rajabifard, M. J. Valadan Zoej, I. Williamson mansourian@kntu.ac.ir, abbas.r@unimelb.edu.au, valadanzouj@kntu.ac.ir, ianpw@unimelb.edu.au : Faculty of Geodesy & Geomatics Eng., K.N.Toosi University of Technology : Center for Spatial Data Infrastructure and Land(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)
To present a new method for building boundary detection and extraction based on the active contour model, is the main objective of this research. Classical models of this type are associated with several shortcomings; they require extensive initialization, they are sensitive to noise, and adjustment issues often become problematic with complex images. In(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)
One of the main challenges of disaster management concerns to proper management of information. In more details, while most of the information required for disaster management has spatial component or location, current studies show that there are different problems with collection, dissemination, access and usage of spatial data/information for disaster(More)
The role of spatial data and related technologies in disaster management has been well-known worldwide. One of the challenges concerned with such a role is access to and usage of reliable, accurate and up-to-date spatial data for disaster management. This is a very important aspect to disaster response as timely, up-to-date and accurate spatial data(More)
The growing availability of high-resolution satellite imagery provides an opportunity for identifying road objects. Most studies associated with road detection are scene-related and also based on the digital number of each pixel. Because images can provide more details (including color, size, shape, and texture), object-based processing is more(More)
This paper proposes an innovative spectral feature extraction (SFE) method called prototype space (PS) feature extraction (PSFE) based only on class spectra. The main novelties of the proposed SFE lie in the following: representing channels in a new space called PS, where they are characterized in terms of reflection properties of classes; and proposing(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)