There is no single textbook for this class. Required reading
materials will be given in the class or be placed on reserve at the library
This course is an introduction to spatial modeling using raster GIS. Basic theories and concepts of spatial modeling will be discussed and students will learn how to use various modeling techniques available in a raster GIS for solving complex environmental and management problems.
Each lab assignment will be considered as an exercise
and is due following week. Late submission will not be accepted! Please see me
if you have an emergency. Laboratory exercises will contribute substantially to
your course grade. Students may be asked to repeat work that is not satisfactory.
*** The above grading is subject to change at the instructor's
discretion ***
Midterm: FINALGRADING:
Requirements:
GIS:122: Spatial Modeling with Raster GIS
Lecture Topics Outline
WEEK/DATE
TOPIC
Week 1
Introduction to spatial modeling and raster GIS
LAB: Introduction to IDRISI
Week 2
Data structure and automation
LAB: Creating digital data layers
Week 3
Raster Data and File Types, Sources of GIS Data
LAB: Input and Viewing Cartographic Data
Week 4
Data Types, Encoding techniques, and Entry Methods
LAB: Analysis and manipulation of spatial data
Week 5
Logical Operations and Map Overlay
Lab: Reclass and Overlay
Week 6
DEM and Surface Analysis
Lab: Generating Slope, Aspect, and new data layers from existing
digital data
Week 7
Written Part (closed book) and Computer Part(open book)
Week 8
Modeling with overlay
Lab: Selecting suitable sites
Week 9
Spatial query
Lab: Reclassification and grouping
Week 10
Viewshed and Watershed Analysis
Lab: Multicriteria decision making in a GIS
Week 11
Siting problems and Proximity analysis
Lab: Selecting suitable sites for Landfill
Week 12
SPRING BREAK
Week 13
Satellite Image and GIS Data
Lab: Feature detection
Week 14
Change Detection
Lab: Detection and monitoring urban growth and development
Week 15
Map making process and presentation
Lab: Map composition
Week 16
Review and mock exam
Week 17
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