Module 4 - Hazards: Coastal Flooding

     This week's module focused on the necessary procedures for coastal flooding assessment. Using DEMs, we assessed destruction, storm surge/flood risk and flood zones.

    I created this map starting from USGS and LiDAR DEM rasters by using various geoprocessing tools, including the Reclassify tool and the Region Group tool. This map omits low-lying areas that were not connected to the larger USGS/LiDAR DEMs. Exclusion of these low-lying disconnected areas could lead to an underestimation of storm surge risk. These areas could still flood if they are connected through drainage systems. Hydrological modeling could help identify flow paths of watersheds to help with increasing accuracy in the assessment of flood risk.

Module 3 - Visibility Analysis

     This week's module involved completing select courses from the "Get Started with Visibility Analysis" Esri Learning Plan. I learned the difference between the different elevation types (on ground, relative to ground, and absolute height) from the "Introduction to 3D Visualization" course. The course also offered examples of extrusion types for 3D symbology, such as polygon features being extruded vertically to represent buildings.

    The "Performing Line of Sight Analysis" course listed the inputs required for performing a line of sight analysis, and described the workflow for doing so. The image below is one of the example images used in the course, where the green lines represent areas that are visible, and the red lines represent areas not visible. The course also described how to use the Construct Sight Lines and Line of Sight tools.

 

    The "Performing Viewshed Analysis in ArcGIS Pro" course describes how to create an output raster that represents the visible area from an observer point, similar to the previous course. The main difference between the two analyses is that the Line of Sight analysis determines obstructed and unobstructed view along a line, and the Viewshed analysis symbolizes an area as visible or not visible. This course instructed me on how to use the Viewshed tool.

    The final course, "Sharing 3D Content Using Scene Layer Packages" mainly taught me how to create and use Scene Layer Packages.

Module 2 - LiDAR

    This week's module focused on how to generate DEM's, DSM's, and tree heights and densities from LiDAR data. The study area for this module is the Shenandoah National Park located in Virginia. This module introduced me to working with LAS datasets and LAS-related ArcGIS tools such as the LAS to MultiPoint tool or the LAS Dataset to Raster tool. 

    This layout contains the LiDAR scene as well as the DSM I had generated.

    This layout depicts the tree height distribution in the quadrant. The graph tells us that most of the trees in the area are 54.69 ± 20.55 ft in height. There are very few trees taller than 90 ft in the area. There are a few “trees” with negative values, but these can be attributed to the man made features in the area.

 

    And this is a layout of the canopy density of the quadrant. This layout clearly depicts the man-made features such as Skyline Dr to the east.

Module 1 - Crime Analysis

  The topic of this course's first module was hotspot analysis. We were tasked to make three maps of 2017 Chicago homicides using local clustering. The three methods used were grid-based mapping, kernel density and local Moran's I.

   From left to right: grid-based, kernel density and local Moran's I.

   The steps I took to create these maps were as follows:

Grid-based

     First, I used the Spatial Join Tool to join the overlaid grid with the 2017 homicides feature layers. Then, from the grids that contained greater than 0 homicides I exported the top quintile into a new feature layer. I used the Dissolve Tool to finalize the grid-based map.

 Kernel Density

    I started by using the Kernel Density Tool on the 2017 homicides point feature layer. I changed the output feature to consist of 2 classes and used the Reclassify Tool. Lastly I used Select By Attributes to export the gridcode 2 features to use as the final map.

Local Moran's I

    The first step was to use the Spatial Join Tool to join the census tracts and 2017 homicide features. After, I used the Cluster and Outlier Analysis (Local Moran's I) Tool on the spatially joined features using a calculated Crime Rate field. To finalize the map I used the Dissolve Tool to dissolve previously exported HH features.

GIS 5100: Applications in GIS Intro Post

My name is Keanu, I was born and raised in Suriname and I am a Dutch-English bilingual. I have a Bachelor's degree in Biological Science, obtained from Florida State University in Tallahassee. I am currently employed full time with the Florida DEP's Division of Environmental Assessment and Restoration as an Environmental Specialist I, where I assist in monitoring the state's water quality. We analyze water samples obtained from all across the state for microbiological indicators.

I joined the GIS Master's Program because I wanted to tie in the experience I have gained in the environmental field along with my computer skills. I hope to achieve my master's degree in GIS Administration by the end of 2026.

 Please find a link to my story map here: https://arcg.is/1LDnvC