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Environmental Spatial Data Analysis

EAS
543
Description

This advanced GIS course focuses on frequently used quantitative methods in spatial analysis within the R programming environment. These methods help answer questions such as:

  • Are features of interest in my study area spatially clustered or independently distributed?
  • How can I interpolate between field-collected point data to create a spatially continuous map?
  • Is my data spatially autocorrelated, and how does this affect my analysis?
  • What underlying variables best explain or predict land cover patterns in my study area?

Course Topics Include:

  • Use of R in spatial analysis
  • Assessment of spatial autocorrelation
  • Spatial point pattern analysis and clustering analysis
  • Spatial interpolation
  • Spatial regression analysis

Course Format:

  • Emphasizes hands-on lab work, utilizing R (and some ArcGIS).
  • Labs (homework) will require additional time to finish outside of scheduled lab sessions.

Required Prerequisites:

  • One GIS course (e.g., EAS 531 or similar)
  • One introductory statistics course (e.g., EAS 538 or similar)
  • Basic familiarity with the R environment (If you have no previous R experience, contact the instructor for permission to enroll; some preparatory work may be required).
Faculty/Instructor
Silvia Cordero-Sancho
Syllabus
File
EAS_543.001_Fall_2021.pdf
Credits
Minimum credits
3.00
Maximum credits
3.00
Pass / Fail
Pass/Fail or S/U optional
Undergrad
No
Graduate
Yes
Prerequisites
EAS 531 and EAS 538 or equivalent
Offered Fall Semester
Yes
Offered Winter Semester
No
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University of Michigan School for Environment and Sustainability
Dana Building
440 Church Street
Ann Arbor, MI 48109
(734) 764-6453
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