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Lab 8:Spectral Signature Analysis and Resource Monitoring

Goals: The goals of this lab were to practice collecting spectral signatures from a variety of objects in an image of Eau Claire county, Wisconsin and the surrounding areas. The signatures were collected using the signature editor tool in Erdas Imagine software. Additionally, this lab focused on using band ratio to monitor the health of vegetation and soils. Methods Section 1: The first part of the lab focused on collecting and analyzing spectral signatures of  remotely sensed images. Signatures were collected for 12 different surfaces using the signature editor tool in Erdas imagine software. The signatures collected are as follows. 1. Standing Water 2. Moving Water 3. Deciduous Forest 5. Riparian Vegetation 6. Crops 7. Dry Soil (uncultivated) 8. Moist Soil (uncultivated) 9. Rock 10. Asphalt highway 11. Airport runway 12. Concrete Surface The signatures were then compiled on a graph and compared _______________________________________________________________...
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Lab 7-Photogrammetry

Background:  The focus of this lab was to understand photogrammetry and to practice performing  photogrammetric tasks on images. More specifically, this lab focuses on understanding the calculations behind photographic scale, understanding stereoscopy and performing orthorectification   Methods Part 1: The first section of the lab focused on understanding photographic scale. Using various equations, I calculated the scale for two aerial images of Eau Claire county. For the first image I was given the ground distance and measured the photo distance on my screen using a ruler. The scale was then calculated using the equation in figure one below Figure 1: Equation where S=Scale, pd= photo distance and gd=ground distance For the second image, I was given the focal length of the camera, the elevation of the camera above sea level and the elevation of the terrain in the image. The scale was calculated using the equation seen below in figure 2, Figure 2 Equat...
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Lab 6: Geometric Correction

Goals and Background: The goal of this lab was to practice performing geometric correction on digital images. In this lab two types of geometric correction were performed. The following is terminology used throughout this lab Image to Map Rectification- This is when an images data pixel coordinates are transformed, or rectified using their counterpart coordinates on a map Image to Image Rectification- This is similar to Image to Map Rectification, however instead of a map an already corrected reference image is used Ground Control Points- Ground Control Points, or GCP's are paired measurement points used in geometric correction. The higher the distortion, the more GCPs are needed. Spatial Interpolation- When GCP pairs are used to establish a transformation that corrects the pixel value in the output image using the value of a pixel in the input image Intensity Interpolation - When Brightness values are extracted for an X,Y location in the reference image and place i...
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Remote Sensing Lab 5

Purpose:  The purpose of this lab was to gain basic knowledge of LiDAR data structure and processing. This was done in two distinct phases. The first phase involved the retrieval and processing of surface and terrain models. The second phase dealt with the processing and creation of intensity images and other products using Point Cloud data in LAS file format. The data for this lab was sourced from Eau Claire County and the 6th edition of Mastering ArcGIS by Margaret Price. Methods: The first portion of the lab involved retrieving and processing data for analysis. Because of the very large size of the data, a separate folder was created to store it. The next step was to create an LAS dataset in ArcMap. The dataset was created using Lidar Point Cloud data for the City of Eau Claire The data provided by the instructor was copied into a personal folder and an LAS dataset was created within the LAS folder under the ArcMap catalog. The dataset was renamed and the LAS files were ad...
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Remote Sensing Lab 4

1. Background and Goals: The goal of this lab was to learn how to create a subset of an image to isolate a study area and how to perform miscellaneous images functions. These include image fusion, radiometric enhancement, creating an image mosaic, re sampling, and linking a viewer with Google Earth. These functions were performed using Erdas Imagine 2016 software. 2. Methods and results 2.1- Image Sub Setting  The first task of this lab was to create an image subset to highlight an area of interest. For this example the image used was a satellite photo of western Wisconsin and the area of interest was the Eau Claire/Chippewa Falls metro area. To create an image subset, the inquiry box is used to highlight the area of interest. Next, using the subset and chip tool under the raster functions, a subset image may be created and saved. The  subset image may be seen below in figure 1. Figure 1. Subset image showing Eau Claire/Chippewa falls Metro area This same proces...
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