Geography’s Inner Worlds: Pervasive Themes in Contemporary American Geography. Ronald E. Abler,Melvin G. Marcus,and Judy M. Olson,eds.; Postmodemism,or the Cultural Logic of Late Capitalism. Fredric Jameson

New regional growth may perpetuate social and economic inequalities caused by uneven urban development, or may reverse such trends by expanding housing options that make possible the dispersal of lower-income households among suburban areas offering better social, economic, and educational opportunities. Supply-side housing approaches can facilitate a more equitable redistribution of housing options. In this research, we examine the role of the Low-Income Housing Tax Credit (LIHTC) program in expanding the geography of opportunity in one fast-growing region—the Dallas/Fort Worth Metroplex. Findings suggest that although LIHTC developments are penetrating the suburbs, they are not expanding opportunities for these households. Just under half of LIHTC units are found in highly clustered areas characterized by high poverty rates, minority concentrations, poor educational opportunities, and rampant crime. The remaining units are dispersed in areas with moderate conditions. Suggestions are made for altering program guidelines to achieve better dispersal, income-mixing, and regionwide distribution.     

The Changing Geography of U.S. Hispanics from 1990–2006: A Shift to the South and Midwest

Abstract

Between 1990 and 2000 the U.S. Hispanic population increased by 14 million, which is the largest decadal population rise in United States history. This increase was not spread evenly throughout the United States, nor was it isolated to locations that already had large Hispanic populations. On the contrary, areas that previously had a relatively small Hispanic population experienced large percentage increases. In this article the regional variability in Hispanic population growth is explored, along with an emphasis on the economic pull factors driving those demographic changes. This analysis illustrates how restructuring in the meatpacking industry, and the associated economic impacts, have created a dependence on a low wage, illegal labor force that has shaped the recent demographic trend in the South and Midwest.     

Foreign-Area Expertise in U.S. Geography: An Assessment of Capacity based on Foreign-Area Dissertations, 1977–1991∗

Interpretations of a decline in foreign-area specialization have raised concerns about the capacity of geography in the United States to serve the expected increase in demands for foreign-area expertise. An assessment of foreign-area dissertations awarded by U.S. geography programs over a 15-year period (1977–1991) fails to support the concerns raised. No significant declines, if any at all, are found for early career interest and research in foreign areas. Several caveats are warranted, however. Geography has lost three doctoral programs with strong foreign-area dissertation records for the period in question. Also, non-U.S. citizens, many of whom do not remain in the United States after completion of their doctorate work, account for a significant proportion of foreign-area dissertations. Various questions that must be addressed to analyze the capacity question more broadly are identified.     

A Review of: “Accuracy of Spatial Databases”. Edited by M. Goodchild and S. Gopal. (London: Taylor & Francis, 1989.) [Pp. 290.] Price £35.00.

The integration of multisource heterogeneous spatial data is one of the major challenges for many spatial data users. To facilitate multisource spatial data integration, many initiatives including federated databases, feature manipulation engines (FMEs), ontology-driven data integration and spatial mediators have been proposed. The major aim of these initiatives is to harmonize data sets and establish interoperability between different data sources.

On the contrary, spatial data integration and interoperability is not a pure technical exercise, and there are other nontechnical issues including institutional, policy, legal and social issues involved. Spatial Data Infrastructure (SDI) framework aims to better address the technical and nontechnical issues and facilitate data integration. The SDIs aim to provide a holistic platform for users to interact with spatial data through technical and nontechnical tools.

This article aims to discuss the complexity of the challenges associated with data integration and propose a tool that facilitates data harmonization through the assessment of multisource spatial data sets against many measures. The measures represent harmonization criteria and are defined based on the requirement of the respective jurisdiction. Information on technical and nontechnical characteristics of spatial data sets is extracted to form metadata and actual data. Then the tool evaluates the characteristics against measures and identifies the items of inconsistency. The tool also proposes available manipulation tools or guidelines to overcome inconsistencies among data sets. The tool can assist practitioners and organizations to avoid the time-consuming and costly process of validating data sets for effective data integration.     

A Review of: “Remote Sensing of Soils and Vegetation in the USSR”. By P. J. CURRAN,G. M. FOODY,K. YA. KONDRATYEV,V. V. KOZODEROV and P. P. FEDCHENKO. (London: Taylor & Francis, 1990.) [Pp. 200.] Price £30·00. ISBN 085066 4020.

As they increase in popularity, social media are regarded as important sources of information on geographical phenomena. Studies have also shown that people rely on social media to communicate during disasters and emergency situation, and that the exchanged messages can be used to get an insight into the situation. Spatial data mining techniques are one way to extract relevant information from social media. In this article, our aim is to contribute to this field by investigating how graph clustering can be applied to support the detection of geo-located communities in Twitter in disaster situations. For this purpose, we have enhanced the fast-greedy optimization of modularity (FGM) clustering algorithm with semantic similarity so that it can deal with the complex social graphs extracted from Twitter. Then, we have coupled the enhanced FGM with the varied density-based spatial clustering of applications with noise spatial clustering algorithm to obtain spatial clusters at different temporal snapshots. The method was experimented with a case study on typhoon Haiyan in the Philippines, and Twitter’s different interaction modes were compared to create the graph of users and to detect communities. The experiments show that communities that are relevant to identify areas where disaster-related incidents were reported can be extracted, and that the enhanced algorithm outperforms the generic one in this task.