Special Topics in GIS Lab 9

This week in the lab we learned about accuracy statistics when using Digital Elevation Models (DEMs). In order to accomplish the analysis process you need a DEM to analyse and test elevation points that cover the DEM extent. This analysis is only for the vertical elevation accuracy. We focused on horizontal accuracy in the first part of the semester. For the vertical accuracy statistics we plotted the test points against the DEM then derived the elevation values of the DEM pixels at the test point locations. By comparing the two values we were able to calculate RMSE including the 95th and 68th percentile statistics. The image below shows the result of the vertical accuracy testing. The letters a through e are the different types of land cover represented in the test  points. These were provided as comparison factors for the accuracy statistics. The overall accuracy is listed at the end under All.

Special Topics in GIS Lab 8

This week in the lab we focused in using interpolation methods to analyse water quality data near Tampa Bay, FL. The data given was point data for water quality levels over a body of water near Tampa Bay. The interpolations we used were the Thiessen, IDW, and Spline methods. All three are used popularly today for many applications. The image below is a representation of an Inverse Distance Weighting (IDW) interpolation.

I like the representation of this interpolation because it is visually pleasing even though it is not always the most accurate of the interpolations. The Thiessen or Nearest Neighbor or polygon (all the same) method basically divides up the area into polygons around the individual data points. This method keeps the integrity of the original data and uses that value for the rest of the polygon area. This method is not a very aesthetically pleasing one, but is more accurate than the IDW at times. Finally the spline method uses trends in the data to smooth out the visual to best represent the data as a whole. There are many ways to set up a spline, but as we learned in the lab they are not always the most accurate and are dependent upon the correctness of the collected data.

Special Topics in GIS Lab 7

This week we worked with TINs and DEMs. For those of you new to elevation models the TIN is a network of triangulated elevation points that are laid out in a grid with slope, aspect, and elevation represented. The DEM is a digital elevation model that basically assigns an elevation to a grid area based on the resolution of the area. This week we practiced creating elevation models in ArcGIS and analyzing them. We started with the TIN and found many ways to adjust the symbology of the data to represent exactly view we need from the product. TINs were fairly easy to work with and visualize especially when converted to a 3D image in ArcScene. Finally working with the DEMs we created a slope analysis for a ski resort and were able to display the areas with ideal slope for medium skill level skiers. This document could show the resort the best places to form the next run and what skill level to label it. Below is a screenshot of the DEM analysis in ArcScene. You can see the categorized slope areas along with their aspect and overall elevation.

Special Topics in GIS Lab 6

This week in class we focused on Location-Allocation analysis. It involved determining the best solution based on selected criteria for matching locations with central hubs. A good example is many customers in different locations around the U.S. needing service from package handlers like UPS that has central hubs in different areas. The analysis would provide a solution to which customers should be serviced by which hubs.

This week we focused on a solution that matched customers to a distribution center. After the analysis was run we compared the solution to an overlay of the market areas. Some of the customers were being serviced by distribution centers that were not responsible for their market area. To fix the outliers we simply needed to re-designate some of the market areas. The image below shows the new market areas. It only differs slightly from the original market areas due to the small number of outliers. It is interesting to see the simple analysis that we performed this week. It has so many possible applications and could save companies a lot of money by increasing efficiency.

Special Topics in GIS Lab 5

This week in class we learned a lot about solving Vehicle Routing Problems using ArcGIS. I really enjoyed the week because it involved getting down into the settings of the software to really see what the program is capable of. The goal was to analyse data given for a company that needed to deliver orders to different customers in the south Florida region. The orders were located at a central distribution facility and there were 22 trucks and drivers available to deliver. In the beginning we restricted ourselves to 14 trucks to try and save on costs, but it resulted in many orders not getting delivered and some being delivered late. After the addition of two more routes all packages were delivered and only one was slightly late (2 minutes). The addition of the two extra routes greatly improved customer service and increased revenue. An image including the delivery zones and routes surrounding the central distribution center shows where all of the drop-off sites are located.

The system took in all of the information provided by the user and followed strict constraints to produce the solution that would decrease distance and time costs while stopping at the maximum amount of drop-off sites.