Earth System Science (ESS) research and applications often involve in collecting, analyzing and modeling with distributed heterogeneous geospatial data. Those data are processed step-by-step in geospatial analysis systems to extract information and knowledge products for applications and decision makings. Conceptually, such a step-by-step process forms a geospatial processing model that represe...

Geospatial clustering is an important method for geospatial information analysis. However, most clustering methods do not consider semantic information during the clustering process. In this paper, we present a formal geospatial clustering ontology framework, which can provide the background for geospatial clustering. Using the ontology, geospatial clustering can become a knowledge-driven process.

The need for more cost-effective, accurate and efficient methods of using geospatial information has been around a long time. However, development of GIS software solutions and information technologies enabled the distribution, access and manipulation of geospatial data over the Web. In this paper is represented a new access to geospatial data and the possibility of integrating geospatial data ...

A Cyberinfrastructure (CI) is a combination of data resources, network protocols, computing platforms, and computational services that brings people, information, and computational tools together to perform science or other data-rich applications in this information-driven world. Most science domains adopt intrinsic geospatial principles (such as spatial constraints in phenomena evolution) for ...

Linked geospatial data has recently received attention as researchers and practitioners have started tapping the wealth of geospatial information available on the Web. With the rapid population of the Web of data with geospatial information, applications to manage it have also started to emerge. What the semantic geospatial web lacks, though, compared to the technological arsenal of the traditi...

Geospatial data is vitally important to the ways thousands of government agencies, private companies and non-profit organizations do their businesses. The widespread access and sharing of geospatial data on the Internet yield many benefits. But, there are two important barriers in front of sharing and accessing geospatial data; non-interoperability and insufficient message exchange patterns of ...

This paper situates geospatial technologies as a constructivist tool in the K-12 classroom and examines student experiences with real-time authentic geospatial data provided through a hybrid adventure learning environment. Qualitative data from seven student focus groups demonstrate the effectiveness of using real-time authentic data, peer collaboration, and geospatial technologies in learning ...

DEFINITION Distributed Geospatial Computing (DGC) refers to the geospatial computing resides on multiple computers connected through computer networks. Figure 1 illustrates DGC within the C/S architecture [1]: where the geospatial computing is conducted by the geospatial components, which can communicate with each other or communicate through wrapping applications, such as web server and web br...

The ability to represent geospatial semantics is of great importance when building geospatial applications for the Web. Semantic Web Service technology provides solutions for intelligent service annotation, discovery, composition and invocation in distributed environments. Deploying this technology into geospatial web applications has the potential to enhance discovery, retrieval and integratio...

As geospatial data are becoming more widely used through mobile devices and location sensitive applications, the potential value of linked open geospatial data in particular has grown, and a foundation is being developed for the Semantic Geospatial Web. Protocols such as GeoSPARQL and stSPARQL extend SPARQL in order to take advantage of spatial relationships inherent in geospatial data. This pa...