Web GIS GeoProcessor (http://www.geo.iitp.ru/app.php?link=gis:geoproc2) is targeted to perform analysis of spatial geographic information as well as to solve problems of spatial forecasting. The field of application comprises spatial-data analysis, geological environment research and decision-making support in such problems as seismic hazard assessment and environmental zonation. Analytical abilities of GIS are supplemented by visual research methods, vector and grid-based data calculations, operations of spatial forecasting and pattern recognition, etc. Considering examples of earthquake damage assessment, seismic hazard analysis, geophysical properties forecasting, GeoProcessor 2.0 proved to be an effective tool for fundamental and applied problem investigation.
Web-GIS GeoTime 2.0 is intended for spatio-temporal process analysis and simulation. The field of application comprises seismic hazard, earthquake precursor analysis etc. The system consists of the kernel and a set of user-defined plug-ins that make the system capable to solve the problems in the specific areas of study. The animated visualization facilities of GIS provide visual exploration of 3D raster fields and 4D event catalogues as well. The system possesses a wide range of advanced analytical functions. Along with common vector and 3D grid-based calculations there are a number of additional plug-ins designed for computation of spatio-temporal fields of seismic characteristics. They comprise plug-in for minimal representative magnitude field estimation (Mmin), b-value, seismic activity, RTL, plug-in for detection and significance estimation of spatio-temporal earthquake precursors etc.
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Open-Source GIS plays a pivotal role in advancing GIS education, fostering research collaboration, and supporting global sustainability by enabling the sharing of data, models, and knowledge. However, the integration of big data, deep learning methods, and artificial intelligence deep learning in geospatial research presents significant challenges for GIS education. These include increasing software learning costs, higher computational power demand, and the management of fragmented information in the Web 2.0 context. Addressing these challenges while integrating emerging GIS innovations and restructuring GIS knowledge systems is crucial for the evolution of GIS Education 3.0. This study introduces a Visual Programming-based Geospatial Cyberinfrastructure (V-GCI) framework, integrated with the replicable and reproducible (R&R) framework, to enhance GIS function compatibility, learning scalability, and web GIS application interoperability. Through a case study on spatial accessibility using the generalized two-step floating catchment area method (G2SFCA), this paper demonstrates how V-GCI can reshape the GIS knowledge tree and its potential to enhance replicability and reproducibility within open-source GIS Education 3.0.
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Web GIS GeoProcessor (http://www.geo.iitp.ru/app.php?link=gis:geoproc2) is targeted to perform analysis of spatial geographic information as well as to solve problems of spatial forecasting. The field of application comprises spatial-data analysis, geological environment research and decision-making support in such problems as seismic hazard assessment and environmental zonation. Analytical abilities of GIS are supplemented by visual research methods, vector and grid-based data calculations, operations of spatial forecasting and pattern recognition, etc. Considering examples of earthquake damage assessment, seismic hazard analysis, geophysical properties forecasting, GeoProcessor 2.0 proved to be an effective tool for fundamental and applied problem investigation.