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Course Description
Course Description
This course focuses on important spatial concepts related to geospatial data, data/information representation themes, spatial analysis, spatial modeling, information synthesis and decision support. It also provides students with technical exposure to algorithms and workflows that can be used for producing quantitative and thematic information using geographic information systems (GIS). Furthermore, it emphasizes the concepts and limitations associated with empiricism and uncertainty, and the need for the use of the scientific method and domain knowledge to produce scientifically acceptable results for applied problem solving. It emphasizes mastering the theoretical and fundamental principles of GIS-based analysis and modeling, and science-based utilization of geospatial technologies and algorithms for applied problem solving. Students will receive exposure to the latest issues, concepts, information technologies, and application perspectives.
Learning Outcomes:
Learning Outcomes:
1. Understand the advantages and limitations associated with GIS.
2. Understand numerous multi-faceted spatial concepts.
3. Apply spatial interpolation algorithms for generating data.
4. Spatially analyze raster and vector data.
5. Apply spatial analysis algorithms to extract information from geospatial data.
6. Develop and use models that enable spatio-temporal prediction.
7. Synthesize technical and application domain knowledge to address mapping problems.
GEOG475 Lab 1 Girard.pdfLab 1: Spatial Interpolation
This lab 1 exercise is designed to provide students with exposure to representation issues and spatial interpolation algorithms
The emphasis will be on the evaluation of interpolation approaches that are commonly used on raster and vector data, and how these algorithms govern the magnitude and distribution of climate and landscape properties/attributes
Students will explore the use of various interpolation algorithms and evaluate the consequences of using different algorithm parameter values
Collectively, this lab 1 exercise will familiarize students with understanding the advantages and disadvantages of data represented in different ways and on how interpolation algorithms and their implementation parameters impact that results have on the representation of spatial information
Lab 2: Spatial Metrics and Statistics
Point Distance and Variability Metrics, Point-Pattern Analysis, Spatial Statistic Metrics, Spatial Autocorrelation Metrics using ArcGIS Pro and ENVI Digital Image Processing Software.
GEOG 475 Lab 2.pdfGEOG 475 Lab #3 Girard.pdfLab 3: Terrain Analysis
This map used slope maps, Slope-azimuth (Aspect) maps, Zonal Statistics and Focal Statistics under the topics of Univariate Statistics, First-Order Derivatives, Second-Order Derivatives.
Lab 4: Criteria-Based Modeling
Identify the optimum location for building a new home in Brazos County. You will need to establish criteria that will be applied to data that attempts to characterize various themes of suitability for home selection. Use the following four suitability themes to help you identify the best home location:
Maximum distance from flooding zones
Presence of forest land cover.
Proximity to the road
Located as close as possible to the OM building
GEOG 475 Lab #4 Girard (1).pdfPage updated
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