GIS5100 Lab 1: Suitability Analysis

Below is the final product for the last part of this week's lab. To get to this, the suitability was based on land cover, soils, slopes, rivers, and roads. I used the Euclidean distance tool to get my suitability for the roads and rivers data, changed the soils vector data to raster, used to the Slope tool to determine the slope from the elevation DEM, and reclassified everything to 5 suitability ratings. Then I used the Weighted Overlay tool a couple times to get my final products. First, I used Set Equal Influence for all five criteria, then for the second map I manually changed the weight factors for an alternative result.

Lab 10: Supervised Classification

For this lab we were to take an image of Germantown, MD and classify a variety of land use types from given coordinates and then recode them into 8 classes.

I used a combination of tools including created polygons and adding them to the signature editor, as well as using the grow tool and adding those results to the editor. After recoding the image, I imported the final product into ArcMap and changed the symbology for each class to a more appropriate color.

This was my final map, which includes the distance image as well as the main, recoded supervised classification:

GIS4035 Lab 8: Thermal & Multispectral Analysis

For this weeks lab, we first created multispectral images by combining several layers into one image. This was done in both ArcMap and ERDAS. Then, we were to take one of the new images, identify a feature on it, and create a map showing that feature using the best band combination to make it stand out.

This was the map I made. I chose to identify the two bridges that crossed the river at both forks. I used a Red-3, Green-5, and Blue-6 band combination to make them stand out the best, being that the river had low temperature and low near-infrared, while the bridges had higher temperatures and low near-infrared.

Lab 7: Multispectral Analysis

For this week's lab, we were to first get familiar with using image histograms and the inquire cursor to interpret image data and identify features on an image. From there, we were given pixel information about three different features on an image and had to find the features and change the band combinations to make said features stand out.

For the first one I used a combination that made the water stand out against the land features:

For the second one, I used a combination that make the snow contrast well with the vegetation:

And for the final one, I used a combination that again made the water stand out. Only this water had a much brighter pixel value than all of the other bodies of water in the image.

GIS 4035 Lab 5a

For this week's lab, we were introduced to ERDAS IMAGINE and worked through the basics of the program. While we only touched on minor parts of the program, it seems like there's a lot to learn about it, and I rather enjoyed working with it.

For the last exercise, we were to import a raster dataset into ERDAS, and from there add a new field to its attribute table and, by using the inquire box, select a section of the data to export into ArcMap to create a new map.

This was my final product. I tried to select a portion that included a good variety of the features contained in the data, to better see how everything transferred over from ERDAS to ArcMap.

Remote Sensing Lab 4

For this lab, we were to take our map from last week and check the accuracy of our classifications. To do this, I created a new shapefile that consisted of 30 random points on the map. From there, I used Google Maps to get a better view of the location of each point and check whether it really was what I classified it as. It was a fairly straightforward assignment and all went pretty smoothly, for the most part. This was the finished product:

Module 11: Sharing Tools

For our final assignment in GIS Programming, we were to take a toolbox, tool, and script and share it for others to use, after password protecting it. Even though this one was brief and simple, it was still interesting to learn how to do it. I've learned a lot of useful skills in this class that I'll hopefully be using a lot in the near future. Overall, this class wasn't nearly as painful and stressful as I expected it to be. 

This is what was created when the tool was ran in ArcMap: