3.1: Georeferencing Raster Data
Raster data, including satellite imagery, scanned maps, and aerial photos, is an important data source for GIS analysis and visualization. But just like other GIS data, for reliable results raster data must be accurately referenced to the correct location on the earth’s surface. This course teaches a workflow to align a raster dataset with its real-world location and evaluate the accuracy of georeferencing results. The goals of this assignment are to:
- Determine whether a raster dataset has spatial reference information.
- Prepare raster data for the georeferencing process.
- Determine when to perform automated georeferencing and when to manually georeference a raster.
- Choose an appropriate transformation method for your data and project needs.
- Evaluate errors that can occur during the georeferencing process.
Describe how raster analysis could be used in other courses you have taken currently or throughout your academic career. Give specific examples.
When it comes to raster analysis, I can see how it can be applied to not only physical science, but also to social science. Last semester, when I took Biology, our ePortfolio assignment was to get outside, be in nature, observe it and then write a reflection essay on our experience. I wrote my essay after a day spent hiking to Bell Canyon Reservoir and observing all of the biology of the area. I made observations about native plants and birds throughout my hike and then also while sitting on the shore of the reservoir. When I conducted some research into the history of the Bell Canyon area, Sandy city had quite a bit of historical information as well as more recent studies. It would have been really interesting to analyze my more current observations of Granite Trail and Bell Canyon Reservoir and layer my data in a raster analysis on top of historical maps and the current map furnished by the city. I observed so many different birds on that hike that I have been considering logging my observations into eBird so that other nature and bird lovers can locate the same birds as I did. Thanks to the Cornell Lab of Ornithology, eBird provides “global tools for birders, critical data for science.” I think I must have been in the right place at the right time—perhaps during a migration period through our region of Utah.
I can also see how raster analysis would be useful in social sciences and humanities studies. I recall when I took the course World Religions and how we learned about and discussed the three major world religions (Judaism, Christianity and Islam), but we also touched upon several other religions like the whirling dervishes of Sufism. We also discussed how religious organizations send out missionaries to spread the ‘word’ of a particular faith in hopes of converting non-followers to their particular religion. I think it would be really fascinating to create maps of religious mission migrations today and analyze the data against older maps and missions, like the Spanish Colonial Missions.
3.2: Image Processing
Imagery is a pervasive data source used for geographic context, visualization, and analysis. This course teaches a variety of techniques to enhance and control image display, perform simple change detection, and derive new products from a single image source. In this assignment, you will apply how to:
- Dynamically adjust image display properties to better distinguish surface features.
- Create a multispectral image from multiple single-band images.
- Generate a Normalized Difference Vegetation Index (NDVI) to visualize the distribution and density of vegetation in an area of interest.
- Visualize elevation data using hillshade and shaded relief functions.
- Save image processing output to a layer or file for easy sharing and input to analysis operations.
3.3: ePortfolio Discussion