Recent advances in sensor and platform technologies such as satellite systems, unmanned aerial vehicles (UAV), manned aerial platforms, and ground-based sensor networks have resulted in massive volumes of data is produced and collected about the earth. Processing, managing, and analyzing these data is one of the main challenges in 3D synthetic representation used in modeling and simulation (M&S...

The increasingly available Graphics Processing Units (GPU) hardware resources and the emerging General Purpose computing on GPU (GPGPU) technologies provide an alternative and complementary solution to existing cluster based high-performance geospatial computing. However, the complexities of the unique GPGPU hardware architectures and the steep learning curve of GPGPU programming have imposed s...

Public geospatial data (geodata) is created at all levels of government, including federal, state, and local (county municipal). Local governments, in particular, are critical sources geodata because they produce foundational datasets, such as parcels, road centerlines, address points, land use, elevation. These datasets sought after by other public agencies for aggregation into state national ...

The paper, focusing on the problem that the overall correlation level of the research result is low in the current geospatial data search system, establishes users’ search intention models, researches the intelligent and professional geospatial information search method, and makes use of spatial cognition theory and knowledge engineering methods to make up for the shortcomings of the lack of se...

Recent advances in sensor and platform technologies, such as satellite systems, unmanned aerial vehicles (UAV), manned aerial platforms, and ground-based sensor networks have resulted in massive volumes of data being produced and collected about the earth. Processing, managing, and analyzing these data is one of the main challenges in 3D synthetic representation used in modeling and simulation ...

Disasters are events that cross geographical, organisational and other human-made or natural boundaries. Therefore, disaster management requires that various geospatial data producers and users collaborate together in an ad hoc manner, despites their different background and contexts. While semantic interoperability is meant to support meaningful communication between geospatial databases, sema...

The fuel driving the engine of growth and sustainable development of any nation is the nation’s access to reliable and adequate geospatial information (GI). Over 80% of socio-economic and environmental management decisions are based on quality and accurate information on natural resources and other geospatial data. On the other hand, the roots of under-development of the third world countries, ...

There has been enormous progress in geospatial data acquisition in the last decade. Centralized data collection, mainly by land surveying offices and local government agencies, has changed dramatically to voluntary data provision by citizens. Among a broad list of initiatives dealing with user generated geospatial information, OpenStreetMap (OSM) is one of the most famous crowd-sourced products...

Geospatial software tools (GIS) are used for creating, viewing, managing, analyzing, and utilizing geospatial data. Geospatial data can include socio-economic, environmental, geophysical, and technical data about the Earth and societal infrastructure and it is pivotal in environmental modeling and management (EMM). Desktop, web-based, and embedded geospatial tools and systems have become an ess...

AbstrAct Multi-agent system is specialized in studying the collective effects of multiple intelligent agents. An intelligent agent is a computer system with autonomous action in an environment. This technology is especially suitable for studying geospatial phenomena since they are complex in nature and call for intertwined actions from different forces. This chapter describes multi-agent system...