G.Hudson Mastering GIS

Exercise 1 deliverable Exercise 2 deliverable Welcome to the first week of GIS5027 - Photo Interpretation and Remote Sensing! The first week of class introduced students to Remote Sensing, its fundamentals and the basis of interpreting images, inclusive of identifying features. As such, the lab assignment helped students learn how to identify various tones and textures in an image, as well as identify features based on shape/size, shadow, pattern and being associated with another feature. We also had the opportunity to distinguish features based on true color imagery and false color infrared imagery. Pictured above are the deliverables for exercise 1 and 2. For exercise 1 I identified the various tones and textures found in the image. For exercise 2 I identified 3 objects based on shape/size, shadow, pattern and association. 

  The time has come. The end is here. It is the final week/s of GIS5050. As such, we were expected to complete a final project. For our final assignment we were tasked with performing an analysis of the Florida Power and Light (FPL) Bobwhite-Manatee Project Transmission Line, which allowed us to utilize the various skills we learned during the semester. To do this we had four criteria which included defining homes within proximity of the transmission line, schools within proximity of the transmission line, imposition of the transmission line on parcels and environmentally sensitive line, and determining the length of the transmission line. My map of environmentally sensitive land imposed on by the transmission line is displayed above. Once we completed our analysis we then had to present it in the form of a power point presentation or a story map. I chose to do a story map titled "FPL Bobwhite-Manatee Transmission Line Feasibility Analysis" . The final project was quite inter...

  As the title of this blog post suggests, week 6 tasked students with georeferencing raster layers, editing two vector layers and using LiDAR data to produce a 3D map. Georeferencing raster layers proved to be quite an intricate process. It required identifying features on the raster image that matched the spatially accurate vector data. While choosing common features it was important to choose features that are static/stagnant or unlikely to change such as buildings or road intersections. Once a common feature was identified we input control points that would line the raster layer up with the spatially accurate vector layers. Once the raster layers were georeferenced, we then edited the buildings and roads layers. Using the georeferenced images of the UWF campus we digitized building 072 and Campus Lane. We also created a multiple ring buffer for a protected Eagles Nest on UWF campus property. The georeferenced images, digitized building and road, and the multiple ring buffer can...