{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,28]],"date-time":"2025-11-28T04:47:57Z","timestamp":1764305277027,"version":"build-2065373602"},"reference-count":56,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2013,5,21]],"date-time":"2013-05-21T00:00:00Z","timestamp":1369094400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Urban economic modeling and effective spatial planning are critical tools towards achieving urban sustainability. However, in practice, many technical obstacles, such as information islands, poor documentation of data and lack of software platforms to facilitate virtual collaboration, are challenging the effectiveness of decision-making processes. In this paper, we report on our efforts to design and develop a geospatial cyberinfrastructure (GCI) for urban economic analysis and simulation. This GCI provides an operational graphic user interface, built upon a service-oriented architecture to allow (1) widespread sharing and seamless integration of distributed geospatial data; (2) an effective way to address the uncertainty and positional errors encountered in fusing data from diverse sources; (3) the decomposition of complex planning questions into atomic spatial analysis tasks and the generation of a web service chain to tackle such complex problems; and  (4) capturing and representing provenance of geospatial data to trace its flow in the modeling task. The Greater Los Angeles Region serves as the test bed. We expect this work to contribute to effective spatial policy analysis and decision-making through the adoption of advanced GCI and to broaden the application coverage of GCI to include urban economic simulations.<\/jats:p>","DOI":"10.3390\/ijgi2020413","type":"journal-article","created":{"date-parts":[[2013,5,21]],"date-time":"2013-05-21T14:22:12Z","timestamp":1369146132000},"page":"413-431","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["A Geospatial Cyberinfrastructure for Urban Economic Analysis and Spatial Decision-Making"],"prefix":"10.3390","volume":"2","author":[{"given":"Wenwen","family":"Li","sequence":"first","affiliation":[{"name":"GeoDa Center for Geospatial Analysis and Computation, School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85287, USA"}]},{"given":"Linna","family":"Li","sequence":"additional","affiliation":[{"name":"Center for Spatial Studies, Department of Geography, University of California, Santa Barbara, CA 93106, USA"}]},{"given":"Michael","family":"Goodchild","sequence":"additional","affiliation":[{"name":"Center for Spatial Studies, Department of Geography, University of California, Santa Barbara, CA 93106, USA"}]},{"given":"Luc","family":"Anselin","sequence":"additional","affiliation":[{"name":"GeoDa Center for Geospatial Analysis and Computation, School of Geographical Sciences and Urban Planning, Arizona State University, Tempe, AZ 85287, USA"}]}],"member":"1968","published-online":{"date-parts":[[2013,5,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2615","DOI":"10.1098\/rsta.2007.2089","article-title":"Introduction. 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