Introduction to ucgis Priority Research Fields

Introduction to ucgis priority research areas.

Physical Basis of Geographic Information Science:
The concepts, classifications, relationships, and evolution of geographies at different scales are studied, including their interactions.

Geographic Information Representation:
Extends existing data models and structures to represent multi-dimensional spatial entities and processes (temporal). Develops spatial analysis methods, especially for large data volumes and distributed spatial databases.
The restriction of spatial representation is to use the two-dimensional and single-resolution Representation Methods of traditional cartography.

Space Data Acquisition and integration:
Methods and technologies for improving spatial data acquisition and integration, such as data collection standards, location accuracy, measurement and sampling theory, classification systems, metadata, location matching, and privacy issues.
The Error Analysis on data has an album on j geo sys of 2004.

Spatial Scale Problems:
The main problem is to understand how a scale affects human prediction, how to effectively and accurately measure and describe the scale, how to select appropriate data based on the scale, and how to automatically select a scale; how scale and its changes affect the content, analysis, model, and process of information (for example, Spectral Study ?).
The problem of scale is a cross-disciplinary issue.

Research on cognition of geographic information space:
This article studies people's understanding, memory, reasoning, and communication of actual and digital spatial objects and the temporal and temporal attributes of events. Research fields include data collection and storage, visual representation, user interface design, spatial analysis, interoperability, decision-making, and social GIS.
The availability, efficiency, and usefulness of GIS software can benefit from the study of spatial cognition.

Space, time-space Analysis and Modeling :
The methods, technologies, and routes of modeling spatial and temporal data using GIS are studied, and how to store, select, operate, explore, analyze, and display spatial data using GIS.
GIS provides the basis and tools for Spatial Data Operations and Analysis. The application of geographic modeling can analyze natural sciences and social sciences through GIS.
Possible research areas:
§ Disease distribution
§ Traffic Management
§ Environment problems
§ Description and management of land and resources
§ Social, cultural, and economic analysis
§ Natural processes, such as floods and disasters
§ Public GIS or service-type GIS
Preferred research areas:
§ Develop technical methods that can operate on large data volumes
§ To analyze spatial and temporal data, we must develop analysis methods that can analyze spatial and temporal data to reflect the real world.
§ Develop deterministic and meaningful analysis methods (available methods for others)
§ Use the variance chart and the kerkin Method
§ Analysis scale function, research the Independent Analysis Method of scale
§ Study local and global effects and their differences
§ Methods of research and development that can differentiate general and special phenomena
§ Apply and use new computing and analysis methods, such as wavelet, neural networks, artificial intelligence, and pattern recognition, to study the use of these methods in GIS analysis.
§ Combination of economic model and GIS
§ Spatial Interaction Model
§ Supply operation research

Uncertainty Analysis of geographic information

Geographic Visualization Research

GIS and Society

Geographic Information Engineering (Geographic Information Engineering)
includes distributed computing, basic structure of geographical information in the future, spatial information mining, and knowledge recognition. A key aspect of distributed computing is grid and GIS. The so-called infrastructure includes GIS interoperability, standards, national standards, basic geographic data, and platforms; knowledge mining should be a sunshine field in the future.