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Geospatial Methods

Author Profile
Abuduwasiti Wulamu

Saint Louis University
a
University with graduate programs, including doctoral programs
.

Summary

The class introduces concepts, theories, and techniques in geospatial methods, and principles of spatial analysis, and data mining with integration of GIS, remote sensing and GPS. Varies applications of the techniques are also discussed with special attention on its applications in environmental studies such as risk assessment and mitigation, environmental modeling, resources exploration, natural resource management, air-pollution & control, forest fire management.

Course URL:
Resource Type: Course Information
Special Interest: GIS
Grade Level: Graduate/Professional
Course Size:

less than 15

Course Context:

This is an upper-division elective course with no prerequisites. However, an introductory course in GIS and/or remote sensing is helpful. The course does not serve as a prerequisite for other courses. Students can take the course to satisfy their general education requirements.

Course Goals:

-Familiar with geospatial technology and the methods used to derive information from spatial data.
-Familiar with geoprocessing techniques such as spatial autocorrelation, sampling, georeferencing, interpolation, and associated uncertainties with them.
-Be able to perform spatial modeling using varies data sources, and produce geostatistical summaries from spatial data.
-Carrying out optimization studies to identify desired point locations and routes.
-Understand how to integrate remote sensing and GPS into GIS for data mining, effective maintaining and updating of organizational databases.
-Familiar how to use GIS and geospatial methods to solve their own research problems.

Attitudinal Goals

-Understand how to integrate remote sensing and GPS into GIS for data mining, effective maintaining and updating of organizational databases.
-Be able to design, develop and maintain geodatabases, relational databases and online live maps.
-Be able to perform spatial modeling using varies data sources, and produce geostatistical summaries from spatial data.
-Carrying out optimization studies to identify desired point locations and routes.
-Familiar how to use GIS and geospatial methods to solve their own research problems.

Assessment

30% - Lab assignments (10×3) A (≥ 93 points)
10% - Discussions (5×2) B+ (90 – 92 points)
08% - Project proposal B (83 – 89 points)
10% - Project Abstract B- (80 – 82 points)
10% - Project presentation C (73 – 79 points)
25% - Quizzes (5×5) F (≤ 72 points)
07% - Attendance

Syllabus:

Geospatial Methods Course Syllabus (Microsoft Word 2007 (.docx) 28kB May27 10)

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