Special Topics in Environmental Sciences (390-0-02)
Topic
GIS - Raster & Remote Sensing
Meeting Info
Technological Institute F285: Mon 9:30AM - 10:50AM
Overview of class
We will focus on the raster GIS environment, which is the core analytical GIS data structure used for natural resource modeling and environmental analysis. Students will learn the raster structure and its advantages and limitations; will learn tools and techniques used to display, process, and analyze remotely sensed data, including appropriate raster data management and procedures; raster surface modeling and image interpretation; map-algebra concepts using ArcGIS Spatial Analyst; proximity and dispersion modeling. Student will be assessed on in-class exercises, homework assignments, weekly labs, a final exam, and a final project in which students will demonstrate their ability to apply new skills to a real-world situation of academic interest by preparing and presenting a research poster.
Registration Requirements
Some basic GIS knowledge preferred, however students without prior GIS experience will independently complete ~ 4 hour online pre-course learning tutorial provided by the instructor.
Pre-registration - majors/minors in ENVR SCI, EARTH, EPC.
Regular Registration - Any 3 prior STEM courses
Learning Objectives
In this course, students will:
Understand the connection between raster and vector data
Understand raster data types, management and conversions
Use raster and terrain data and techniques to analyze natural environments to solve problems and address spatial questions using GIS.
By the end of this quarter, students should be able to:
Be able to navigate and use the software interface
Develop and maintain a project Log for workflow documentation.
Use digital elevation model to model slope, aspect and other terrain derivatives to perform basic surface hydrological analyses.
Apply surface interpolation techniques and principles
Apply Raster Overlay techniques and Map ap algebra operations to identify landscapes that meet certain conditions and create suitability models.
Create high quality maps/figures to include in illustrated academic, scientific and professional high-quality reports or presentations.
Exercise critical "spatial" thinking and creative problem-solving skills
Teaching Method
This class will be taught with combined lecture/activity sessions. Each class will include a theoretical knowledge base, an in-class exercise, and a relevant homework assignment to build skills.
Class Materials (Required)
We will use the ESRI ArcGIS Pro software in this course.
The ideal personal laptop for this course is a PC Windows machine with Window 10 or 11 64x, 4 cores CPU (2 is the minimum), 32 GB of RAM (8GB is the minimum, and a 32 GB or more Hard Disk on a solid-state drive (SSD).
For those with laptop limitations, all students will have access the NUIT Virtual lab, in which you can access ArcGIS Pro via remote connection to a virtual machine over the internet.
NOTE: It is not possible to install ArcGIS Pro directly on a MAC (or Linux for that matter). If your Mac has a quad-core Intel processor or M-series (Apple Silicon) processor, 256 GB storage and 8 GB RAM or more, you can either run ArcGIS Pro natively on a Windows partition (Boot Camp) or run ArcGIS Pro in a virtual environment, and in this case a Parallels Desktop version 15 or later and Windows x64 installed as the guest operating system are required.
To access ArcGIS Pro, all students need to be part of an ESRI ArcGIS Online Organization, for which students will receive an email invitation by the second class. Once you have this account, you can download and install the software on your personal laptop.
NOTE: If a personal laptop capable of downloading the software is a limitation, please first see if you can secure a "loaner laptop" from the Northwestern Library. You may also reach out to Dr. Beddows to discuss what may be other options if the library does not have a unit for you.
Class Materials (Suggested)
Recommended Textbooks:
1. GIS Fundamentals: A First Text on Geographic Information Systems", Edition: 7th, Author: BOLSTAD 9780971764750
2. Remote Sensing: Principles, Interpretation, and Applications, Fourth Edition Floyd F. Sabins, Jr., James M. Ellis. Waveland Press, Inc. ISBN 10: 1-4786-3710-2 - ISBN 13: 978-1-4786-3710-3
Enrollment Requirements
Enrollment Requirements: Pre-requisite: Students must have completed at least three units of Math, Chemistry, Physics, Statistics, Environmental Sciences, Earth & Planetary Sciences, or Biological Sciences.
Associated Classes
LAB - Technological Institute F285: Wed 9:30AM - 10:50AM