GIS Labs - Andrew Wians

Goal and Background The goal of this lab exercise is to become familiar with performing key photogrammetric tasks on aerial photographs and satellite images. Tasks include performing Stereoscopy and performing Orthorectification on satellite images. Completing this lab exercise will help to gain an understanding of the mathematics behind the calculation of photographic scales, measurement of areas and perimeters, and calculating relief displacement.  Lab 7 is split into three parts; (1) Scales, Measurements and Relief Displacements, (2) Stereoscopy, and (3) Orthorectification. Each of these parts are outlined in the Methods and Results sections of this blog post. Methods The methods used to obtain the results for each of the three parts of this lab exercise are outlined below. The data sources used for each part are listed in the Sources section of this blog post. Scales, Measurements and Relief Displacements Calculating Scale: If the actual distance between tw...

Background and Objectives Prior to the extraction of biophysical and sociocultural information from satellite images, the analyst must perform some preprocessing activities. The following lab exercise is designed to introduce the concept of image preprocessing known as Geometric Correction . There are two major types of geometric correction that are normally performed; Image-to-Map Rectification and Image-to-Image Registration. Image-to-Map Rectification In this part of the lab exercise, the analyst will use a United States Geological Survey (USGS) 7.5 minute digital raster graphic (DRG) image of the Chicago Metropolitan Statistical Area and adjacent regions to correct a Landsat TM image of the same area. In order to accomplish this, ground control points (GCPs) must be collected from the USGS 7.5 minute DRG and used to rectify the Landsat TM image. Image-to-Image Registration In the second part of the lab exercise, the analyst will use an already corrected Landsat TM image ...

Background & Objectives The goal of this lab exercise is to gain basic knowledge on LiDAR data structure and processing. LiDAR is a rapidly expanding area within the remote sensing field and there are many new opportunities available to those with applicable experience. Lab 5 is split into three parts, with the goals of each part outlined below. Part 1: Point Cloud Visualization in Erdas Imagine Objective : Load a LAS data file in Erdas Imagine and view the Point Cloud Part 2: Generate a LAS Dataset and Explore LiDAR Points With ArcGIS Objective : You are a GIS manager working on a project for the City of Eau Claire, WI, USA. You have acquired LiDAR point cloud in LAS format for a portion of the City of Eau Claire. First, you want to initiate an initial quality check on the data by looking at its area and coverage, and also verify the current classification of the LiDAR. Create a LAS dataset Explore the properties of LAS dataset Visualize the LAS d...

Goal and Objectives The goal of this lab exercise is to learn how to download and map data from the U.S. Census Bureau. This particular lab will focus on Wisconsin census data. Objectives: 1. Download 2010 Census data (total population) from the US Census Bureau 2. Download a shapefile of the 2010 Census boundaries from the US Census Bureau 3. Join the downloaded data to the Census shapefile 4. Map the data 5. Download and map a variable of your choice 6. Build a layout with both maps 7. Build a web map with one of the variables Instructions to recreate each of the objectives completed in this lab can be found in the Methods section of this post. Methods This section outlines the steps taken to complete each of the learning Objectives for this lab exercise. These procedures can be used in the future to recreate this lab, or can be used as supplemental material when performing similar tasks in the future. Objective 1: Download 2010 Census Data from t...