Planning And Socioeconomic Applications

This chapter has shown a small sample of GIS applications in economic devel- ment. GIS is a powerful tool for data analysis and presentation, and the economic development rami cations are truly signi cant. The speed at which data and stra- gies can be coordinated is clearly changing the way economic developers approach their job. There are a number of important trends that are likely to result in GIS becoming more pervasive in the economic development community. These include declining costs of GIS software, increased computing power, and the growth of Web-based GIS applications. There also has been increase in GIS skills among economic development professionals. References Bastian, L. (2002). Getting the best from the web. Area Development Site and Facility Planning, March 1–7. Accessed 5 September 2008. Batheldt, H. (2005). Geographies of production: growth regimes in spatial perspective (II) – kno- edge creation and growth in clusters. Progress in Human Geography, 29(2), 204–216. Bathelt,H.,Malmberg,A.,Maskell,P.(2004). Clustersandknowledge: localbuzz,globalpipelines and the process of knowledge creation. Progress in Human Geography, 28(1), 31–56. Bernthal, M., Regan, T. (2004). The economic impact of a NASCAR racetrack on a rural com- nity and region. Sports Marketing Quarterly, 13(1), 26–34. Blackwell, M., Cobb, S. Weinbert, D. (2002). The economic impact of educational institutions: Issues and methodology. Economic Development Quarterly, 16(1), 88–95. Blair, J. (1995). Local Economic Development, Analysis and Practice. Thousand Oaks, CA: Sage Publications.

The Development of Gis. Gis Applications. Theories of Gis. Data Collection and Input. Data Storage. Data Manipulation. Data Output and Display. Towards a Socioeconomic Gis.

The second edition of a bestseller, Quantitative Methods and Socio-Economic Applications in GIS (previously titled Quantitative Methods and Applications in GIS) details applications of quantitative methods in social science, planning, and public policy with a focus on spatial perspectives. The book integrates GIS and quantitative (computational) methods and demonstrates them in various policy-relevant socio-economic applications with step-by-step instructions and datasets. The book demonstrates the diversity of issues where GIS can be used to enhance the studies related to socio-economic issues and public policy. See What's New in the Second Edition: All project instructions are in ArcGIS 10.2 using geodatabase datasets New chapters on regionalization methods and Monte Carlo simulation Popular tasks automated as a convenient toolkit: Huff Model, 2SFCA accessibility measure, regionalization, Garin-Lowry model, and Monte Carlo based spatial simulation Advanced tasks now implemented in user-friendly programs or ArcGIS: centrality indices, wasteful commuting measure, p-median problem, and traffic simulation Each chapter has one subject theme and introduces the method (or a group of related methods) most relevant to the theme. While each method is illustrated in a special case of application, it can also be used to analyze different issues. For example, spatial regression is used to examine the relationship between job access and homicide patterns; systems of linear equations are analyzed to predict urban land use patterns; linear programming is introduced to solve the problem of wasteful commuting and allocate healthcare facilities; and Monte Carlo technique is illustrated in simulating urban traffic. The book illustrates the range of computational methods and covers common tasks and major issues encountered in a spatial environment. It provides a platform for learning technical skills and quantitative methods in the context of addressing real-world problems, giving you instant access to the tools to resolve major socio-economic issues.

The second edition of a bestseller, Quantitative Methods and Socio-Economic Applications in GIS (previously titled Quantitative Methods and Applications in GIS) details applications of quantitative methods in social science, planning, and public policy with a focus on spatial perspectives. The book integrates GIS and quantitative (computational) methods and demonstrates them in various policy-relevant socio-economic applications with step-by-step instructions and datasets. The book demonstrates the diversity of issues where GIS can be used to enhance the studies related to socio-economic issues and public policy. See What’s New in the Second Edition: All project instructions are in ArcGIS 10.2 using geodatabase datasets New chapters on regionalization methods and Monte Carlo simulation Popular tasks automated as a convenient toolkit: Huff Model, 2SFCA accessibility measure, regionalization, Garin-Lowry model, and Monte Carlo based spatial simulation Advanced tasks now implemented in user-friendly programs or ArcGIS: centrality indices, wasteful commuting measure, p-median problem, and traffic simulation Each chapter has one subject theme and introduces the method (or a group of related methods) most relevant to the theme. While each method is illustrated in a special case of application, it can also be used to analyze different issues. For example, spatial regression is used to examine the relationship between job access and homicide patterns; systems of linear equations are analyzed to predict urban land use patterns; linear programming is introduced to solve the problem of wasteful commuting and allocate healthcare facilities; and Monte Carlo technique is illustrated in simulating urban traffic. The book illustrates the range of computational methods and covers common tasks and major issues encountered in a spatial environment. It provides a platform for learning technical skills and quantitative methods in the context of addressing real-world problems, giving you instant access to the tools to resolve major socio-economic issues.

The pursuit of sustainable development and smart growth is a main challenge today in countries around the world. Social capital is an asset of their territorial communities. It is also a precondition for national and local policies that aim to better the economic base and quality of life for all. This change is socially diffused, economically sustainable over time, and smart in its content. A significant stock of social capital facilitates such results because it links into the process of development planning institutional decision makers and socioeconomic stakeholders who share trust, solidarity norms, and a community vision. In the last thirty years, social capital has become a forceful concept in the social sciences, the subject of many scholarly works and a topic of keen interest and debate in policy circles. Yet the main focus has been on defining and measuring social capital, with little attention given to its value in promoting development policies. Social Capital in Development Planning updates and advances the debate on social capital through the analysis of the application of the concept of social capital to programs for sustainable and smart socioeconomic development; empirical findings; and a new paradigm for development planning.