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Showing posts from September, 2022

Module 2.1 - TINs and DEMs

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  This module examined TIN and DEM elevation models. For part of this exercise I used a DEM to develop a suitability map for a ski resort. This analysis involved creating several rasters and reclassifying them to show the most desirable locations for a ski resort. The map above shows the results of this analysis. The areas in green are the most suitable locations based on desired elevation, slope, and aspect.

GIS Internship #1

 While I would love to be able to participate in a traditional internship, due to my current full-time employment status I was unable to secure a remote internship or one through my current employer. Therefore, I will be will participating in Group 2 and taking part in the ESRI Online Training Program. 

Module 1.3 - Data Quality - Assessment

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Below are the steps I used to complete the assessment of the road network quality. ·            Used Clip Layer tool to isolate only roads within the Grid for both the Centerlines shapefile and the      TIGER Roads shapefile. ·          Used the Intersect tool to clip the Centerlines and TIGER clipped shapefiles to the Grid. ·          Used Tabulate Intersection tool to calculate the length of each segment of both shapefiles that occurred    in each grid  section.         I then exported the attribute tables to Excel to complete all calculations and readded the excel sheet back into my map to create the choropleth.     

Module 1.2 - Standards

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This image shows the city streets and the test points I selected using the provided data. Upon completion of determining test and reference points using the provided data for the city of  Albuquerque, NM, StreetMap USA, and the DOQQs, I added the XY coordinates to attribute tables for each set of points. Then I exported the tables in Excel and used the provided spreadsheet to calculate the horizontal accuracy. For the City Street data: Using the National Standard for Spatial Data Accuracy, the data set tested 19.78 feet horizontal accuracy at 95% confidence level.     For the StreetMap USA data: Using the National Standard for Spatial Data Accuracy, the data set tested 147.08 feet horizontal accuracy at 95% confidence level.  

Module 1.1 - Fundamentals

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Horizontal Precision (68%): 10.3m Vertical Precision (68%): 5.88m Distance between my average location and the reference is 11.4m. This lab introduced the fundamentals of determining the precision and accuracy of data. Accuracy is the closeness of agreement between a test result and the accepted reference value. Precision is the closeness of agreement between independent test results obtained under stipulated conditions.