Joe Copsey GIS

       This week I completed 4 training courses focused on visibility analysis on ESRI's website. The first course was an introduction to 3D visualization, where I was able to explore the techniques and uses for 3D data in ArcGIS Pro. I compared 2D data and 3D data of Crater Lake in Oregon, and how it is utilized. 3D data is extremely useful for displaying data you are unable to using only a 2D map, showing a much more accurate visualization and analysis of an environment.       The next course was about performing line of sight analysis, a procedure used to determine visibility between an observation point and a target point. I found this segment to be the most interesting, as well as incredibly useful. In the example, I looked at the view of a parade route from multiple observation points, and how the line of sight may be obstructed due to buildings or weather. I used analysis tools such as the Construct Line of Sight and the Line of Sight tool ...

This week I learned more about LiDAR and its uses. LiDAR (Light Detection and Ranging) is a method used to create maps by using remote sensing and light to determine distances. For this weeks module assignment, I created a few maps using LiDAR data from the Virginia Geographical Information Network. I converted the LiDAR (LAS) data to raster data, then calculated the height of the trees by subtracting the non-ground points from the ground points. The map below shows the outcome as well as an accompanying chart   Finally, I used the LiDAR data and geoprocessing steps in ArcGIS Pro to complete this map depicting canopy density in a selected portion of Shenandoah National Park, Virginia. Some of the geoprocessing steps taken where converting the points to raster, counting the ground and vegetation points, then using the plus tool to combine the data. Then, I converted the result of the plus from integer to float data, and divided this result with the vegetation count.

       This week I learned about how GIS is used for crime analysis to help law enforcement. The module was focused on three different methods used to identify crime hotspots. These methods are grid overlay, kernel density, and local Moran's I. The maps below display hotspots for homicides committed in Chicago in 2017 and show the difference of the results of each method. The grid-based overlay uses aggregated data to determine the hotspots. The kernel density map uses point data and weighs points closer to a search areas center more heavily than those on the edge, creating a smoother data result. This was achieved in ArcGIS Pro by using the kernel density tool. The local Moran's I method uses aggregated data to group clusters of high occurring and low occurring instances, as well as outliers such as a high occurrence surrounded by low occurrences, or vice-versa. These maps were achieved by using a spatial join to combine the homicide statistics with census data and ...