This course (GIS) is designed to introduce you to how GIS and remotely-sensed data can complement each other, with the goal of answering questions you may have about the natural world (which includes humans!) and sociological phenomenon. Incidentally, you will also be introduced to a range of software (both open source and proprietary) that can be used for the processing, organization, and analysis of GIS/RS data. This single course is not enough to give you a full understanding of GIS/RS software systems and applications. Instead, my aim is to introduce you to the main concepts, methods, and software that are currently used in GIS/RS so that you can build a base of knowledge from which you can seek out resources that are pertinent to whatever analyses you need to conduct in the future.
The software and methods in this course will serve you well, regardless of whether you decide to go to work for industry, the government, academia, an NGO, etc. In fact, because many of these software tools are free and open source (FOSS), it can be quite straight-forward for you to gain the expertise and abilities you need to tackle almost any geospatial problem you can think of. While I will provide some learning activities that involve mastering the basic terminology and concepts in GIS/RS, most of our time will be spent “learning by doing”. You will not be following “recipes” to perform standard analyses. Instead, each module is designed so that you will perform never-before-attempted analyses on geographic areas of your choosing so that you will be learning techniques and generating new knowledge at the same time. What you produce in this class will be as useful as you want it to be and can be posted online for anyone to access.
I am a user and advocate of free and open source software. The free software philosophy is essentially the same as the academic philosophy of shared knowledge production for the common good. I try to incorporate open source software in my teaching, and to encourage students to use open source software for their research and writing and to find open knowledge outlets to share their research and writing. The labs in this course will be taught using a mix of FOSS (QGIS, R), free proprietary software (Google Earth) and expensive proprietary software (ArcGIS) to provide you with a diverse resumé.