GIS 520 Portfolio

To find out more about Mandy, and her quest for sustainable local food, click on the About Me page.

Advanced Geospatial Analytics (NCSU GIS 520) follows Introduction to Geographic Information Science and builds geoprocessing skills and knowledge of the analysis capabilities of geospatial technology. This portfolio presents the topics examined over the semester. This is one of the two required courses (6 hours out of 15 credits) for the GIS Certificate, which I completed in the spring of 2016.

Learning objectives were as follows:

  • Describe the analysis capabilities of different geospatial technologies,
  • Select and perform appropriate advanced geoprocessing functions for specific objectives,
  • Integrate and analyze data in various formats,
  • Identify data limitations for particular analytical applications,
  • Apply appropriate analysis techniques for different types of decision making objectives,
  • Search for, retrieve, evaluate the suitability of, and integrate data sets for specific types of analysis applications, and
  • Build simple customizations for the user interface.

This was accomplished through weekly modules and ESRI courses. The course evaluation explains how this course will impact my career.

Assignment

Objectives

Map Design Fundamentals (ESRI)
  1. Demonstrate Cartographic design concepts.
  2. Utilize Proper Color in cartographic design
  3. Use proper Visual variables and symbology
  4. Adding text and labels to map features
Geocoding Tabular Data
  1. Identify methods in ArcMap to geocode tabular data by zip code and street names.
  2. Apply interactive techniques to locate addresses.
  3. Formulate and perform a batch geocoding procedure.
AutoCAD Integration Exercise
  1. Understand basic data structure of CAD created data compared to ESRI format feature layers.
  2. Georeference a CAD dataset in ArcMap.
  3. Perform data translation from CAD format into a geodatabase.
Database Cardinality Issues in ArcGIS
  1. Understand the issues and processes as they relate to data cardinality in ArcGIS.
  2. Learn the process of joining tabular data to spacial data in ArcGIS.
 Census Data Exercise
  1. Develop the ability to independently locate, filter, link, and map U.S. Census Bureau Data from American Fact Finder and TIGER/Line® shapefiles.
 Linear Referencing
  1. Demonstrate an elementary understanding of linear referencing.
 Exploring Spatial Patterns in Your Data Using ArcGIS
  1. Examine the spatial distribution to identify clusters and spatial relationships in the data.
  2. Find outliers using a semivariogram cloud, Voronoi map, histogram, and normal QQ plot.
  3. Assess which analysis tools are appropriate given the spatial distribution and data values.
  4. Use a trend analysis graph to identify patterns in your data.
 Spatial Pattern Analysis
  1. Test for statistical significance using the average nearest neighbor, Getis-Ord D, Ripley’s K, and Moran’s I statistic.
  2. Evaluate the z-statistic, random distribution, and clustering.
 Using Raster Data for Site Selection
  1. Reclassify raster layers that store different types of data so they can be used together for analysis.
  2. Perform a weighted overlay analysis to find locations that satisfy a range of suitability criteria.
  3. Perform fuzzy overlay analysis to identify areas that have a high likelihood of meeting project criteria.
 Suitability Analysis and Weighted Overlay Exercise
  1. Demonstrate an understanding of Spatial Analysis including Suitability Analysis, Weighted Overlay function, and Model Builder in ArcGIS.
 Image Classification
  1. Demonstrate an understanding of Image Classification within the ArcGIS interface.
 Customizing the ArcMap Interface
  1. Extend the ArcMap interface by creating custom toolbars and menus to access built-in functionality.
  2. Locate, install and use add-ins available through ESRI online Resource Center.
  3. Explore and suggest customization techniques for your research or work applications.

 

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