Geospatial information systems provide avenues to fulfill users’ quest for both absolute and relative locations of features/objects. To achieve this, the users need to have access to different geospatial data sets from various sources. This calls for integration of data from different geospatial sources. But, there are shortcomings as different data sets may not map exactly onto one another, on...

Geospatial data sharing is a concern in geospatial science because of the heterogeneity of existing geographical information systems. This study aims to examine the use of Geospatial Semantic Web technologies such as ontology, web services and the service-oriented architecture for enabling disparate heterogeneous legacy GIS to share and integrate information in a cost effective way to reduce sp...

 The NSDI, through the Federal Geographic Data Committee (FGDC) Secretariat, facilitates the technologies, policies, and people necessary to promote sharing of geospatial data throughout all levels of government, the private and non-profit sectors, and the academic community.  The National Map is the product of a consortium of federal, state, and local partners who provide geospatial data t...

In the Digital Forestry area, there is more and more requirements for spatial information connection and processing. From a prototype of geospatial computational grid (GCG), the relationship between the geospatial computational grid and OGC Interoperability protocols is proposed in this paper. A prototype of geospatial information grid is given in this paper. Digital Forestry Grid is proposed a...

ologies and technologies have strengthened their position in the areas of data and knowledge management. Standards for organizing and querying semantic information, such as RDF(S) and SPARQL are adopted by large academic communities, while corporate vendors adopt semantic technologies to organize, expose, exchange and retrieve their data as Linked Data [1]. RDF stores have become robust enough ...

Geographic Space still lacks the semantics allowing a unified view of spatial data. Indeed, as a unique but all encompassing domain, it presents specificities that Geospatial Applications are still unable to handle. Moreover, to be useful, new spatial applications need to match to human cognitive abilities of spatial representation and reasoning. In this context, eMerges, an approach to geospat...

Earth science (ES) applications handle very large geospatial data sets and interactive response time is required by its query processing. Spatial selection is one of the very important basic operations for geo-spatial databases. It retrieves all the objects that intersect with a given point or rectangle. This paper presents a novel approach for the parallel processing of spatial selection of ve...

In distributed geospatial applications with heterogeneous databases, an ontology-driven approach to data integration relies on the alignment of the concepts of a global ontology that describe the domain, with the concepts of the ontologies that describe the data in the distributed databases. Once the alignment between the global ontology and each distributed ontology is established, agreements ...

Geospatial processing tasks like solar potential analyses or floodplain investigations within flood scenarios are often complex and deal with large amounts of data. If such analysis operations are performed in distributed web-based systems, technical capabilities are mostly not sufficient. Major shortcomings comprise the potentially long execution times and the vast amount of messaging overhead...

To optimize the efficiency of the geospatial service in the flood response decision making system, a Parallel Agent-as-a-Service (P-AaaS) method is proposed and implemented in the cloud. The prototype system and comparisons demonstrate the advantages of our approach over existing methods. The P-AaaS method includes both parallel architecture and a mechanism for adjusting the computational resou...