共查询到20条相似文献，搜索用时 31 毫秒
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PAUL MATHER 《International journal of geographical information science》2013,27(2):258-259
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. 相似文献
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《Urban geography》2013,34(5):490-500
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. 相似文献
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Itzhak Benenson 《International journal of geographical information science》2013,27(5):1047-1053
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David J. Magutre 《International journal of geographical information science》2013,27(4):487-488
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. 相似文献