Monitoring land use changes using geo-information : possibilities, methods and adapted techniques

Monitoring land use with geographical databases is widely used in decision-making. This report presents the possibilities, methods and adapted techniques using geo-information in monitoring land use changes. The municipality of Soest was chosen as study area and three national land use databases, viz. Top10Vector, CBS land use statistics and LGN, were used. The restrictions of geo-information for monitoring land use changes are indicated. New methods and adapted techniques improve the monitoring result considerably. Providers of geo-information, however, should coordinate on update frequencies, semantic content and spatial resolution to allow better possibilities of monitoring land use by combining data sets

LUMIS: A Land Use Management Information System for urban planning

The Land Use Management Information System (LUMIS) consists of a methodology of compiling land use maps by means of air photo interpretation techniques, digitizing these and other maps into machine-readable form, and numerically overlaying these various maps in two computer software routines to provide land use and natural resource data files referenced to the individual census block. The two computer routines are the Polygon Intersection Overlay System (PIOS) and an interactive graphics APL program. A block referenced file of land use, natural resources, geology, elevation, slope, and fault-line items has been created and supplied to the Los Angeles Department of City Planning for the City's portion of the Santa Monica Mountains. In addition, the interactive system contains one hundred and seventy-three socio-economic data items created by merging the Third Count U.S. Census Bureau tapes and the Los Angeles County Secured Assessor File. This data can be graphically displayed for each and every block, block group, or tract for six test tracts in Woodland Hills, California. Other benefits of LUMIS are the knowledge of air photo availability, flight pattern coverage and frequencies, and private photogrammetry companies flying Southern California, as well as a formal Delphi study of relevant land use informational needs in the Santa Monicas

Geographically Referenced Data for Social Science

An estimated 80% of all information has a spatial reference. Information about households as well as environmental data can be linked to precise locations in the real world. This offers benefits for combining different datasets via the spatial location and, furthermore, spatial indicators such as distance and accessibility can be included in analyses and models. HSpatial patterns of real-world social phenomena can be identified and described and possible interrelationships between datasets can be studied. Michael F. GOODCHILD, a Professor of Geography at the University of California, Santa Barbara and principal investigator at the Center for Spatially Integrated Social Science (CSISS), summarizes the growing significance of space, spatiality, location, and place in social science research as follows: "(...) for many social scientists, location is just another attribute in a table and not a very important one at that. After all, the processes that lead to social deprivation, crime, or family dysfunction are more or less the same everywhere, and, in the minds of social scientists, many other variables, such as education, unemployment, or age, are far more interesting as explanatory factors of social phenomena than geographic location. Geographers have been almost alone among social scientists in their concern for space; to economists, sociologists, political scientists, demographers, and anthropologists, space has been a minor issue and one that these disciplines have often been happy to leave to geographers. But that situation is changing, and many social scientists have begun to talk about a "spatial turn," a new interest in location, and a new "spatial social science" that crosses the traditional boundaries between disciplines. Interest is rising in GIS (Geographic Information Systems) and in what GIS makes possible: mapping, spatial analysis, and spatial modelling. At the same time, new tools are becoming available that give GIS users access to some of the big ideas of social science."

A GIS Model for Predicting Disaster Prone Areas Affected by Global Sea-Level Rise: a Case Study of Semarang City

The issue of global warming that increases sea level will certainly have an effect on sustainability of coastal areas, including coastal cities. Some studies predict that in 2050 the potentially flooded areas around the world will increase approximately one to three meters (WOC, 2007). This tendency will in turn influence the sustainability of many Indonesian cities, particularly those located on coastal areas. Regarding the above issue, this research aims at developing a spatial model using Geographic Information System (GIS) for predicting/delineating disaster prone areas in coastal cities. The model involves some GIS analysis’ capabilities, such as spatial overlay, weighting method and spatial query to delineate flooded areas based on the increase of global sea level and its topography. To test the developed model, Semarang City is selected as the case study with consideration that some previous researches have been done in this area so that most of required data have been collected. The model is then validated using empirical data and field visits to compare between the result and the current situation. The result of application shows that the developed model is satisfied. As for the case of Semarang City, the result shows that 71.6 km2 of Semarang coastal areas are potentially flooded, which 5.04 km2 are highly risk. By superimposing the potentially flooded areas and some vulnerability aspects, the model delineates disaster prone zones as high, moderate and low level. In spite of the fact that the model development purpose is accomplished, further studies are still needed, particularly to specify variables of vulnerability due to the Characteristics of the city. Besides, a 3D model can also be combined with the developed model to improve its visual vie

The potential of a GIS-based scoping system: An Israeli proposal and case study

In the environmental impact assessment (EIA) lifecycle, scoping is regarded as the most important stage for the quality of the entire process. Even though many EIA methods exist, only a few of them are specifically suited for scoping. Despite the well-acknowledged potential of geographical information systems (CIS) for EIA and their seemingly widespread use, the applicability of GIS for scoping has not been analyzed sufficiently. This article advances a GIS-based scoping method and discusses the conditions necessary for its utilization. Two specific issues are addressed: the ability of a GIS-based system to identify the pertinent environmental effects on the basis of readily available information under stringent time and budget constraints, and the institutional infrastructure needed for such a system to operate effectively. These issues are analyzed in a case study conducted in Israel. In this case study, the proposed GIS-based scoping system identified all the main effects found independently in a comprehensive environmental impact statement (EIS), as well as issues not analyzed in the EIS. A centralized institutional scoping structure, whereby EIS guidelines are issued by a single entity, is found to be important for the operation of such a system, because it can enjoy the economies of scale and scope involved in setting up and operating a GIS system for scoping purposes

Supporting Cancer Prevention Strategies Using Geospatial Analysis on HRSA data

This paper uses develops a methodology to geospatially analyze factors associated with disparities in cancer rates

A preliminary training guide for utilizing high-altitude, color-infrared photography in compiling soil maps

Instruction for acquiring and analytically processing small-scale color-infrared photography to perform a soil resources inventory over forests of the southern U.S. is provided. Planning the project; acquiring aerial photography, materials, equipment and supplemental data; and preparing the photography for analysis are discussed. The procedures for preparing ancillary and primary component overlays are discussed. The use of correlation charts and dichotomous keys for mountain landforms, water regime, and vegetation is explained