We estimate a hedonic model of the housing market that includes a spline surface defined on geospatial data (i.e., the longitudes and latitudes of individual dwellings). House price indexes are then obtained by imputing prices for individual dwellings from the hedonic model and then inserting them into the Fisher price index formula. Using data for Sydney, Australia we compare the performance o...

Seismic site effects are influenced mainly by geospatial uncertainties corresponding to geological or geotechnical spatial variance. Therefore, the development of a geospatial database is essential to characterize site-specific geotechnical information in multiscale areas and to optimize geospatial zonation methods with potentially high degrees of spatial variability based on trial-and-error ge...

As networking and data storage technologies advance, web services have become a commonplace for data mining and sharing in an e-business model. Compared with business information, geospatial information is normally overwhelmed by the sheer volume of data. There has been a great need for the integration of web services and geospatial information to provide a platform for geospatial information d...

Geospatial research increasingly relies on shared geospatial data, interconnected models and successively refined analysis which requires not only more powerful but also more accessible cyberinfrastructure systems for support. In this study, we propose to integrate data grid, ontology and Web-based workflow technologies to build more accessible cyberinfrastructure systems for geospatial computi...

As geospatial data grows explosively, needs for the incorporation of data mining techniques into Geographic Information Systems (GISs) are in great demand. Association rules mining is a core technique in data mining and is a solid candidate for the cause-effect analysis of large geospatial databases. It efficiently detects frequent asymmetric causal patterns in large databases. In this paper, w...

Geospatial clustering is a very important research topic in the field of „Geospatial Knowledge Discovery.‟ Its main purpose is to group similar objects, from large geospatial datasets, into clusters, based on the objects‟ spatial and non-spatial attributes. This capability is very useful for better understanding the patterns and distributions of geographical phenomena. With the emerging availab...

UNLABELLED We present a REST web service to assess the geospatial quality of primary biodiversity data. It enables access to basic and advanced functions to detect completeness and consistency issues as well as general errors in the provided record or set of records. The API uses JSON for data interchange and efficient parallelization techniques for fast assessments of large datasets. AVAILAB...

Linked geospatial data has recently received attention, as researchers and practitioners have started tapping the wealth of geospatial information available on the Web. Incomplete geospatial information, although appearing often in the applications captured by such datasets, is not represented and queried properly due to the lack of appropriate data models and query languages. We discuss our re...

Towards geospatial semantic search: exploiting latent semantic relations in geospatial data Wenwen Li a , Michael F. Goodchild b & Robert Raskin c a GeoDa Center for Geospatial Analysis and Computation, School of Geographical Science and Urban Planning, Arizona State University, Tempe, AZ, USA b Center for Spatial Studies (Spatial@UCSB), University of California, Santa Barbara, CA, USA c NASA J...