Geographic Information Science (GISc) (CERT)

Summary

The Undergraduate Certificate in Geographic Information Science (GISc) integrates technologies such as Remote Sensing, Geographic Information Systems (GIS), Global Positioning Systems (GPS), various associated techniques, and programing. The program introduces foundational concepts and basic principles of geospatial information collection, management, and analysis. The certificate ensures that students have sufficient theoretical understanding of geospatial science, and are able to apply the techniques to analyze real world issues. The project-based approach and hands-on activities that heavily utilizes ArcGIS and ERDAS Imagine software provide necessary skills to be successful in this field. The certificate program offered by the Department of Geography provides background and training that enable students to enter careers in the public or private sectors, and to prepare them for graduate study in geospatial sciences. 

Catalog Year

2020-2021

Degree

Certificate

Total Credits

18

Locations

Mankato

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Program Requirements

Major Common Core

The course will be an introduction to the analysis of spatial data using the concept of a geographic information system (GIS). Content of the course will be, to a great extent, based on the NCGIA core curriculum with assignments tailored to the data and software available within the department such as ArcGIS.

Prerequisites: none

Comprehensive examination of GIS for manipulation and analysis of spatially-referenced data, including data structure and organization, input and output problems, data management, and strategies for analytical work.

Prerequisites: GEOG 373 

This is an introductory course on theories and techniques of remote sensing. Focus will be placed on providing students with a general overview of the application of remote sensing to practical problems, and hands-on experience for image processing and analysis.

Prerequisites: none

Major Restricted Electives

Choose 6 - 8 Credit(s).

Four major sets of ideas will be covered: (1) Introduction to Spatial Organization, (2) Network Analysis, (3) Allocation Methods, and (4) Urban Transportation. The emphasis is on these approaches to understanding the geography of transport by description, explanation, and normative or optimal methods.

Prerequisites: none

This course covers the basic strategies for field mapping using data acquired from global positioning systems (GPS).

Prerequisites: GEOG 373 or equivalent 

This course provides students the opportunity to develop further knowledge of remote sensing. Emphasis will be placed on introducing advanced theories and techniques for digital image processing and helping students obtain independent research skills using remote sensing data.

Prerequisites: GEOG 373, GEOG 474

Descriptive statistics, probability, hypothesis testing, introduction to non-parametric statistics, correlation, introduction to regression analysis, spatial statistics, and principles of data representation in graphs and tables.

Prerequisites: none

Introduction to theoretical frameworks for spatial analysis and geographic quantitative methods. Includes basic and advanced geographic principles and techniques for studying spatial patterns. Designed to equip students with the skills necessary to carry out research projects that demand advanced statistics.

Prerequisites: none

This offering will include supervised project work in raster-based and/or vector-based GIS, using problems and data drawn from local or regional agencies or other professional-level organizations with whom the Geography Department maintains a relationship. Students must have completed one of the prerequisite courses, or a course or professional-level experience.

Prerequisites: Prerequisite: GEOG 373, or 473/573, or permission of instructor.

This course teaches students to reconstruct past landscapes and identify environmental hazards related to historical land use using GIS and remote sensing software. Applications include the identification of hazardous waste sites, wetland drainage, bluff erosion and other environmental hazards relevant to local history research, environmental consulting, archaeology, resource management, real estate, planning and civil engineering. Students will learn to use and interpret historical air photos and maps, digital imagery and LiDAR in problem-solving contexts and to report research findings in effective written, graphic and verbal presentation formats used by government agencies and private consulting firms.

Prerequisites: GEOG 373

This course provides students as well as natural resource professionals the opportunity to develop knowledge of natural resources management based on GIS science. Detailed examples and discussions of GIS operations and analyses associated with managing natural resources are provided. Weekly labs and the final project will focus on various GIS applications in this field. For example, integrating GIS and remote sensing techniques for sustainable land development, conservation biology, forest, water, wetland, wildlife, and agriculture management. Students will also learn how to combine GIS concepts with GIS software skills and apply them to real-world natural resources management tasks.

Prerequisites: GEOG 373

In this course, instruction is provided on foundational knowledge related to mapping and analysis of geospatial data using both open source and enterprise level Web Mapping and Web GIS platforms. Students will learn how to use HTML, CSS, JavaScript, Google Maps API, ArcGIS Online, and ArcGIS API for JavaScript to store, retrieve, manage, analyze, and display geographical information. In addition, students will be introduced to the concepts of mobile GIS technologies and Web based 3D mapping. Web mapping and Web GIS theories and techniques are introduced through a combination of lectures, hands-on exercises, reading materials, and individual or team projects.

Prerequisites: none

This is an introductory course of GIS programming. It consists of lecture and laboratory components covering fundamentals of GIS programming concepts and techniques, as well as hands-on practice with Model builder and Python supported by ESRI'S ArcGIS platforms.

Prerequisites: none