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.     

A Review of: “Fractals in Geoscience and Remote Sensing: Proceedings of Joint JRC/EARSel Expert Meeting,Ispra, Italy, 14–15 April 1994. Report EUR 16092 EN,Image Understanding Research Series Vol I. Edited by G. G. Wilkinson,I. Kanellopoulos and J. Megier”

Geographic information systems (GIS) and spatial regression modeling techniques were used to evaluate the spatially prioritized relationships between grave density and various spatial parameters for a total of 5549 grave locations. Solar radiation was the most important predictor of grave density in the Feng‐Shui locations. Similarly, spatial clustering technology identified the fact that high concentrations of grave necessarily accompany the significantly increasing trends of solar radiation. The results of the regression analyses indicate that the grave density could be explained by the four landform parameters alone yielding R ² values of 0.751. In contrast to the typical theory, slope and aspect were not a dominant determining factor upon the dependent variable of grave density. Also, the significantly increasing trends of grave density were not observed in line with a southern direction. A clear verification has been made for the hidden assumptions in Feng‐Shui's long history that its approach is found to be more appropriate in avoiding shadow conditions, rather than exploring the ideal landform location.     

A Review of “Turf Wars: Discourse,Diversity, and the Politics of Place”

The spatial correlation, or colocation, of two or more variables is a fundamental issue in geographical analysis but has received much less attention than the spatial correlation of values within a single variable, or autocorrelation. A recent paper by Leslie and Kronenfeld (2011) contributes to spatial correlation analysis in its development of a colocation statistic for categorical data that is interpreted in the same way as a location quotient, a frequently used measure in human geography and other branches of regional analysis. Geographically weighted colocation measures for categorical data are further developed in this article by generalizing Leslie and Kronenfeld's global measure as well as specifying a local counterpart for each global statistic using two different types of spatial filters: fixed and adaptive. These geographically weighted colocation quotients are applied to the spatial distribution of housing types to demonstrate their utility and interpretation.     

Emergent Urban Forms,or Emergent Post-Modernisms? A Comparison of Large U.S. Metropolitan Areas

Post-modern urban theory has problematized the universality of existing models of urban form by focusing on fluidity and complexity in the urban landscape. Urban form is "chaotic," "galactic," and even "random" according to this view. Somewhat lost in this perspective are the emergent urban forms occurring in a wide variety of cities. This paper challenges the universalization of landscape complexity that lies at the core of post-modern urbanism by examining landscape changes in the 10 largest metropolitan areas in the United States. The key findings are that landscape complexity vis the mid-20th century city is overstated—not least because the latter was itself quite complicated—and that the unyielding focus on difference deflects attention away from important processes like inner-city revalorization, inner-suburban devalorization, and outer-suburban valorization that are reshaping very different cities in largely similar ways.     

A Review of “Economic Geography: Places,Networks, and Flows”

Landing a rescue helicopter in a wilderness environment, such as Yosemite National Park, requires suitable areas that are flat, devoid of tree canopy, and not within close proximity to other hazards. The objective of this study was to identify helicopter landing areas that are most likely to exist based on available geographic data using two GIScience methods. The first approach produced an expert model that was derived from predefined feature constraints based on existing knowledge of helicopter landing area requirements (weighted overlay algorithm). The second model is derived using a machine learning technique (maximum entropy algorithm, Maxent) that derives feature constraints from existing presence-only points; that is, geographic one-class data. Both models yielded similar output and successfully classified test coordinates, but Maxent was more efficient and required no user-defined weighting that is typically subject to human bias or disagreement. The pros and cons of each approach are discussed and the comparison reveals important considerations for a variety of future land suitability studies, including ecological niche modeling. The conclusion is that the two approaches complement each other. Overall, we produced an effective geographic information system product to support the identification of suitable landing areas in emergent rescue situations. To our knowledge, this is the first GIScience study focused on estimating the location of landing zones for a search-and-rescue application.     

A Review of: “Applications of Spatial Data Structures: Computer Graphics,Image Processing,and GIS”. By H. SAMET. (Addison-Wesley Publishing Company,Inc, 1989.) [Pp. xv + 507; figures,tables, appendix,references, name and credit index,subject index.] Price US $49.95. ISBN 020150300 X (hardback).

The introduction of automated generalisation procedures in map production systems requires that generalisation systems are capable of processing large amounts of map data in acceptable time and that cartographic quality is similar to traditional map products. With respect to these requirements, we examine two complementary approaches that should improve generalisation systems currently in use by national topographic mapping agencies. Our focus is particularly on self‐evaluating systems, taking as an example those systems that build on the multi‐agent paradigm. The first approach aims to improve the cartographic quality by utilising cartographic expert knowledge relating to spatial context. More specifically, we introduce expert rules for the selection of generalisation operations based on a classification of buildings into five urban structure types, including inner city, urban, suburban, rural, and industrial and commercial areas. The second approach aims to utilise machine learning techniques to extract heuristics that allow us to reduce the search space and hence the time in which a good cartographical solution is reached. Both approaches are tested individually and in combination for the generalisation of buildings from map scale 1:5000 to the target map scale of 1:25 000. Our experiments show improvements in terms of efficiency and effectiveness. We provide evidence that both approaches complement each other and that a combination of expert and machine learnt rules give better results than the individual approaches. Both approaches are sufficiently general to be applicable to other forms of self‐evaluating, constraint‐based systems than multi‐agent systems, and to other feature classes than buildings. Problems have been identified resulting from difficulties to formalise cartographic quality by means of constraints for the control of the generalisation process.     

A Review of “The Future of Intermodal Freight Transport: Operations,Design, and Policy”

This article analyzes the interrelationship among resource consumption, sociospatial justice, and what is popularly known as global warming by interrogating the ecological footprint of professional geographers, especially in terms of their conference-going involving air travel. In this spirit, the article introduces and employs the concepts of ecological privilege (as well as its inextricably related antithesis, ecological disadvantage) and dys-ecologism as a way to understand the roots and implications of professional geographers’ fossil fuel use and those of globally advantaged classes more broadly. To illustrate this, the article measures the flight-related ecological footprint of the 2011 annual meeting of the Association of American Geographers (AAG) in Seattle, Washington. In doing so, the article examines how professional geographers, in the form of the AAG, have responded to their travel-related ecological footprint. It thus highlights the importance of scrutinizing the complex and dynamic interrelationships among consumption; associated socioecological benefits and detriments and their systemic manifestations; and hierarchy-related and power-infused categories of race, class, and nation—and their spatialities.     

A Review of “Politics of Urban Runoff: Nature,Technology, and the Sustainable City”

California sage scrub (CSS) is a highly threatened vegetation community in coastal Southern California, 90 percent of which has been lost. Understanding CSS recovery is critical to its survival. This study compares long-term effects of grazing, cultivation, and mechanical disturbance in Southern California by tracking the extent of exotic grassland in two valleys in the Santa Monica Mountains over sixty years using aerial image analysis. Native shrubs returned to the grazed valley over one and one-half times faster than they did in the cultivated valley. Cultivation might result in a type conversion of CSS to exotic annual grassland that resembles a new steady state.     

A Review of “Darkening Peaks: Glacier Retreat,Science, and Society”

This study is motivated by insufficiencies in two areas in the literature. First, some technical barriers have hindered investigations of changing job–housing patterns over time. Second, traditional dichotomous studies (black–white) of ethnically divided commuting patterns are insufficient to paint the big picture of such dynamics in a multiethnicity metropolitan area. This research fills the gap by presenting an approach to the spatio-temporal analysis of commuting patterns by ethnicity. A case study is performed to track changing commuting patterns for whites, blacks, and Latinos in Atlanta over the last two decades. The results shed light on our understanding of the changing job–housing dynamics, particularly that of Latinos.     

A Review of “Latino Immigrants and the Transformation of the U.S. South”

Research on small cities has begun to attract the attention of scholars who argue that contemporary urban scholarship, in its preoccupation with the largest and most advanced world-class cities, have largely ignored small to medium-sized cities. In China, although much attention has been paid to economically advanced urban centers, there actually has been a steady stream of work on small cities. This article profiles how a comparatively smaller city in western China attempts to market itself by selectively placing itself within various social–spatial and political–economic realities. Through Jinghong, we illustrate how local officials and planners attempt to center the city as a gateway to Southeast Asia. By activating, often discursively, multiscalar transborder strategies, local officials in Jinghong not only mobilize ethnic imaginaries, but they also adopt forms of entrepreneurial tactics to promote growth. Developmental strategies of Jinghong not only vacillate between (and draw on) both rural and urban resources; they are furthermore expected to alleviate rural poverty. Through highlighting the agency of small cities like Jinghong in China, this article speaks to the broader developmentalist critique of third- and fourth-world cities as an unfortunate footnote in global urban restructuring, often depicted as places of uniform marginalization and structural irrelevance. Indeed, by focusing on the geography of small cities and giving due attention to their size and proximity to rural spaces, case studies like Jinghong might yet point empathetically to different ways and imperatives of “being urban” where the weight that they carry can also be duly recognized.