(c) 2020 ESRI
Concerned with the theories of structuring, storing, analyzing, and managing spatial data, and aims at the development and application of methods for solving specific problems in geosciences (geodesy, geography, geology, geophysics and others). It deals with information about objects, phenomena and processes on and in the earth, such as the physical environment, natural and man-made resources, their uses and changes. Computer systems are now being used pervasively for this purpose. As such, geoinformatics is focused on developments that allow the representation of spatial information or geoinformation using computer models. It uses computer-based geographical information technology and computer cartography for the analysis and presentation of complex spatial data. It draws from many disciplines, including computer science, engineering, environmental sciences, social sciences, business, planning, mathematics, and statistics in order to understand the different ways geographic space is perceived and represented, and thereby critically and effectively carry out spatial modeling, spatial analysis, and visualization of the common space to be managed.
specially intended for those who will be involved in the design and development of geographic information systems (GIS) to support decision-making about the environment. They are people whose organizations are concerned with the collection and use of geoinformation. Upon completing the degree, their skills in doing research and development in the field of geoinformation handling will be improved. Specifically, these include:
Understanding of the underlying principles in collecting, processing, managing, representing, and disseminating geoinformation
Competence in designing of geoinformation systems in order to provide an efficient method for archiving, accessing, and analyzing geoinformation
Capability in designing and carrying out research and development projects in various aspects of geoinformation
Confidence in communicating and transferring geoinformatics knowledge to others
Fundamentals of spatial databases; spatial data modeling including entity-relationship and object-oriented data models; indexes and access methods including B-trees; and query languages and query processing. Prereq: GmE 203. 5 h (2 lec, 3 lab). 3 u.
Spatial data types; data structures for spatial data; point patterns; measures of dispersion; arrangements; patterns of lines; paths, branching, topology and concepts of distance; patterns of area; patterns in fields; the role of spatial scale and spatial aggregation problems; exploratory spatial data analysis; and spatial autocorrelation. Prereq: GmE 203. 5 h (2 lec, 3 lab). 3 u.
Theory and application of advanced techniques in resource estimation, prediction and evaluation using GIS. Design of GIS; Temporal GIS; 3-D GIS; Spatial data quality; Error propagation; Model integration/coupling with GIS; Agent-Based Modeling. Prereq: GmE 203. 5 h ( 2 lec, 3 lab). 3 u.
Fundamental concepts, theory, and applications of integrating spatial technologies with enabling technologies, such as wireless communications and the Internet; studies in positioning technologies and measurement integration; distributed GIS, web mapping, interoperability; location-based services. Prereq: GmE 203. 5 h (2 lec, 3 lab). 3 u.