Urban and Regional Modeling versus
Planning Practice: Bridging the Gap
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Version 7/22/2008
P.A.J. van Oort, M.C. Kuyper, A.K. Bregt, J. Crompvoets
ABSTRACT
Despite the exponential growth in geoportals at all levels of organization, from local to worldwide, surveys indicate stagnating or even declining trends in visitor numbers. The cause of these trends is poorly understood. In this paper we present a marketing analysis of geoportals. We identify their main competitors, and the two domains in which geoportals can do better than their competitors: creating market transparency and supporting cross-selling. Also we discuss the importance of responding to user feedback and of giving feedback to users. We show what can be practically done by geoportals in those domains. A survey among 48 of geoportals indicates that those which are more active at providing market transparency also have more positive trends in visitor numbers. Other marketing variables were also positively correlated. The theory in this paper can be helpful for geoportal managers in setting up a marketing strategy and that it is worth doing so.
Tomáš Václavík
ABSTRACT: The Olomouc region in the Czech Republic has undergone significant changes in the past several decades, including the change in political system of the country in 1989. Although the political and cultural transformation is generally recognized as an important driver of land use (Ptáček 2000), there have been few studies conducted that would empirically assess and quantify land use/land cover changes in the Czech Republic, especially in the context of the post-socialistic transformation (Fanta et al. 2004; Zemek et al. 2005). In this study, I present an approach for identifying major land use/land cover changes in the Olomouc region applying remote sensing techniques to compare data from multispectral satellite sensors acquired twelve years before and twelve years after the revolution in 1989. I pay closer attention to specific trends in land cover changes: changes in agricultural areas, forested areas, and residential development. The results support initial assumptions that the land cover will reflect the changes in human perception of landscape and natural resources, such as smaller need for intensive agriculture, shift to environmental friendly management of forested areas, or increased development and suburbanization.
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Download Volume 19, Number 2 in PDF format
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(Version 11/7/07)
Donna L. Goldstein
ABSTRACT: For better or worse, computers have revolutionized every aspect of our lives. As we quickly make the transition from an industrial to an information age, computer literacy skills have become a basic necessity. Technology skills are now referred to as the "Fourth R" in education. To successfully learn and use GIS (Geographical Information Systems) technology, one must incorporate the skills of reading, writing, and arithmetic. Understanding and utilizing a GIS system requires a holistic combination of reading instructions, data, and maps; writing hypotheses, reports, and presentations; and using arithmetic to understand queries and spatial analysis. Thus the 4th R as it relates to GIS is a new elevated skill that incorporates the three original R’s in education. Teaching GIS may be just the boost our public educational system needs to adequately prepare students for entrance into the emerging global society.
(Version 11/5/07)
Ahmed F. Elaksher and James S. Bethel
ABSTRACT: High quality 3D building databases are essential inputs for urban area Geographic Information Systems. Since manual generation of these databases is very costly and time consuming, the development of automated algorithms is of great need. This article presents a new algorithm to automatically extract accurate and reliable 3D building information. High overlapping aerial images are used as input to the algorithm. Radiometric and geometric properties of buildings are utilized to distinguish building roofs in the images. This is accomplished using image segmentation and neural network techniques. A rule-based system is used to extract the vertices of the roof polygons in all images. The 3D coordinates of these vertices are computed using photogrammetric mathematical models. The algorithm is tested on a number of buildings in a complex urban scene. Results showed a detection rate of 99% and a false alarm rate of 5.0%. The root mean square error for the extracted building vertices is 0.25 meter using 1:4000 scale aerial photographs scanned at 30 micron.