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Applications for GIS Week 5: Damage Assessment

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This week I learned how GIS is utilized to assess damage after natural events such as hurricanes. First I created a map tracking the path of Hurricane Sandy, using custom symbology to represent the storm types. Next I learned how to create data in ArcGIS Pro, and how this data is used to assess damage and effectively provide relief after a natural disaster. I compared images from before and after Sandy, and determined the damage level of each structure within a study area. It was easy to identify which buildings had been destroyed or majorly damaged by the storm, but determining lesser levels of damage and flooding was more difficult using only an aerial view. I looked for debris surrounding the structures to give me an idea of the damage. I also had to use my better judgement when determining structure types outside of residential, and data detailing that would have been useful. I was not sure what to mark parcels containing parking lots, so I just classified them as unknown. I then n...
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Applications for GIS Week 4: Coastal Flooding Hazards

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 This week I looked at the process for coastal flooding assessment. Using data from the effects of Hurricane Sandy on Mantoloking, New Jersey, I was able to see how the damage was assessed. This process is important for portraying the impact of the storm and structural damage. I created a raster comparing the shoreline of Mantoloking before and after Sandy, pictured in the map below.
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Applications for GIS Week 3: Visibility Analysis

       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 ...
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Applications for GIS Week 2: LiDAR

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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.
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Applications for GIS Week 1: Crime Analysis

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       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 ...
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GIS Programming Week 5

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This week I learned about manipulating spatial data within Python. I used what I learned to create a script that creates a new geodatabase, copies shapefile data to that new database, and creates a Search Cursor and dictionary to isolate and print County Seat cities in New Mexico and their respective population circa 2000. I found the first few steps of the lab straightforward, but first ran into trouble when creating the Search Cursor. At first, the output printed on the same line and looked very messy. To fix this, I ended each line by inserting an escape character <\n> to the script, which fixed that issue. I had the most trouble populating the empty dictionary. The output initially only gave me the last key in the dictionary, but I realized this was because the line of code creating the empty dictionary was blocking the for loop, so I moved it up a few lines and was able retrieve the whole dictionary successfully. I also ran into trouble while trying to place all of my print ...
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GIS Programming Week 4

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     This week I learned how to create a model for geoprocessing function in ArcGIS using ModelBuilder. Creating a model using ModelBuilder within ArcGIS Pro was a great visual tool that helped me understand geoprocessing tools and visualize the workflow. It is very useful when creating tasks that need to be repeated. Below is the model I created to show the process of clipping a feature, and then erasing a selection within the feature, as well as the output. In this case, removing any polygons representing "Not prime farmland" within a map of soil clipped from a basin. After running model Before running model      The next part of my assignment was to write my own script in ArcGIS Notebook that could run add XY coordinates, buffer, and dissolve tools. I exported the model I created to a Python script and inspected it, which further reinforced my understanding of how the geoprocessing tools function. This, along with the readings and practice assignment gav...
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