Emily McRae's GIS Blog

For this module, I worked through the free Esri learning plan Get Started with Visibility Analysis, which contains four web courses. In the web courses, there are learning materials and examples of tools to work through in ArcGIS Pro using data provided by Esri. I will detail the important take aways from each of the four web courses.  3D Visualization Using ArcGIS Pro Use cases for 3D terrain and surface modeling are outlines, such as modeling natural features or cities.  Steps recommended by Esri for 3D modeling:  Have a clear purpose for your 3D scene. Some use cases may be a better fit for a 3D scene, which is the 3D version of a map basically, than a 2D map, while others may not. Consider your purposes and end goals when deciding if a scene is the best direction to go. Make your scene local or global.  This is a decision that has to do with your view extent, and the coordinate system you wish to use. While any scene can function in local or...

In this weeks module, LiDAR data is used and converted using several different methods to obtain information about tree height and canopy density in a grid section of Shenandoah, VA. Data transformation methods and tools include Minus, LAS to MultiPoint, IS NULL, Con, Plus, Divide, and data to raster tools for different data types. The input data is a LAS grid of Shenandoah obtained from Virginia LiDAR, and the outputs are raster datasets showing tree height, surface elevation, and canopy elevation. The following tools are used to determine tree height: The Minus tool is used to determine the difference in feature height from elevation and ground surface features which is useful in determining tree height.  The following tools are detailed as they are used to determine the biomass density of the grid patch.  LAS to Multipoint converts the LAS into a format more useful to analytics. This is performed on both the surface and vegetation datasets. IS NULL is used to i...

Purpose: To determine the suitability of land for development based on 5 criteria, at different weighted values. Process Summary: Land cover, soil type, proximity to rivers, proximity to roads, and degree of slope raster files are reclassified to reflect predetermined categories of rank from 1 to 5. Not all five layers will include a ranking in each 5 categories. These five outputs are combined to create a single ranking using the Weighted Overlay tool. This tool allows layers to be input, and their values assigned to a scale with specified number of values. In this case, the scale runs from 1 - 5. Each layer is set independently to match their value to reflect the scale, such as value of 1 matching scale 1, value of 5 matching scale value 5, and so on. The wieght of each criteria is assigned by percent out of 100. This process is done twice, creating two separate outputs. One output in which all criteria represent an equal weight of 20% each, the other assigning a greater percent...

Purpose: To establish probable corridors of movement of black bears between two separated protected areas of the Coronado National Forest. Process Summary: Cost Distance from both sections of the forest are determined using the Cost Distance analysis tool twice, once for each area of the forest. The polygons representing the forest are converted into raster files, and those raster files used as inputs for the cost distance tool. The cost input is set the a Weighted Overlay of the area, where roads, elevation, and land cover are used to score areas for bear movement. The two outputs for the Cost Distance from each section of the forest are used as inputs in the Corridor analysis tool. This output is then reclassified into 3 classes, based off of the corridor output automatic 10 category grouping. Visually, values that fall within categories 1 and 2 appear suitable for bear movement, while the other areas did not. All other areas were classified as zero, and other values cla...

My name is Emily McRae, I am pursuing my Master's in GIS Administration. I started the program in the spring of 2020, so this will be the last class of my second semester here at UWF. It is moving along quickly.  I got my undergrad in Geography at the University of South Florida in 2016. I live now in Albuquerque, NM where I work for a data hub website run in part through the states Department of Health. We support communities across the state with data and mapping tools and capacity building.  Personally, I enjoy the outdoors and a little bit of hiking. My favorite season if the Fall so I am waiting eagerly for that to roll around. I enjoy crafting a little bit as well, especially with resin and pressed flowers. I love animals, I have four cats and a dog. And I expecting my first child in November.  I joined this program because I noticed that educationally, I was behind a lot of my coworkers. I want to be able to help my organizational capacity expand, and a more...

Brief Overview of Module 6 This module involves creating a .txt file in Python, identifying vertices in a .shp file, and transferring selected information from the .shp file into the newly created .txt file.  In this flowchart a basic process is summarized for the creation of the script. 1)The input workspace environment is defined, along with the output, and the file that the data will be taken from, which was a shapefile of rivers.  2)A textfile is created next using the open() command, and is set to enable the file to allow writing.  3) A search cursor is created within the rivers shapefile to identify the object ID, the Shape, and the Name.  4) A vertex ID created unique for each vertex within the object next. This is done using a nested for loop, in which actions are performed for each row. First, the vertex ID is defined starting with 1, then the XY data is obtained using the getPart function.  5) This information is then written to the te...

Overview: In this module, a new file geodatabase is created in Python, files from one folder are copied into the gdb, a selection from one file is made using an SQL query format, and the output is used to inform a dictionary. The dictionary ultimately displays all New Mexico cities which are county seats, and their populations. Process:  To begin this module, I had already completed the exercises, which was very helpful. It provided a very clear direction for where to go with the different sections in this module. 1) Input arcpy and set the input and output data paths, and ensure they are able to be overwritten. This includes creating an output to a new file gdb. 2) Define a list of feature classes in the environment, and copy them to the new gdb. 3) Create a search cursor to search within the FEATURE column and select out all rows which contain the value of County Seat. 4) Create a dictionary that defines the key as the city name, and the value as the population, for thos...