Download Volume 20, Number 2 in PDF format
In this issue:
Download Volume 20, Number 1 in PDF format
In this issue:
Note: Complete text of Journal articles are in Adobe Acrobat (.pdf) format
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.
In this issue:
In this issue:
Download Volume 19, Number 2 in PDF format
In this issue:
Note: Complete text of Journal articles are in Adobe Acrobat (.pdf) format
(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.
(Version 8/3/07)
F. Canisius and C. Nancy
ABSTRACT: Flood is one of the severe and common natural perils risking life and property in every corner of the world and has become more frequent in resent years due to increasing human intrusion in the environment. Damages caused by flood create great loss to individuals and it is difficult to recover from impacts. Since there are many factors that influence the flooding and cannot be prevented there is no other better way to quickly recover from financial loss than insuring properties. Flood insurance is providing financial protection against losses from flooding. In some countries, though flood insurance is available still the individuals could not able to obtain flood insurance or facing prospect of higher premium. This is because insurance companies charge premium based on region rather than location of individual house. In case of Trinidad, very general traditional way of premium calculation is in practice combined with standard property insurance. By integrating GIS to flood insurance flood risk of each and every individual private house can be evaluated and come up with reasonable premium. In this study GIS based flood insurance system was developed for Trinidad to handle flood insurance for private households and applied to San Juan Downstream to demonstrate feasibility to use the system. The system uses flood and house information from GIS database and client provided information to bring out reasonable premium based on business related variables from insurance companies. This will enable both parties of the insurance market to be benefited.