Term Project

Image Processing of Crawford County, including Haze reduction, Laplacian edge detection, and Implementation of the Normalized Difference Vegetation Index for Identifying Susceptible areas along the Kickapoo River.

Introduction

As indicated by the title of this project, and the maps located below, my study area was Crawford County.  Crawford County is about 600 square miles in size with a population of 16,644 people according to the U.S. Census Bureau.  Towns and communities located in Crawford County include Prairie du Chein, Seneca, Soldiers Grove, and Gays Mills.  Crawford County was close to Vernon County where I am originally from.  My family used to go to Crawford County and spend time around the Kickapoo River.  The Kickapoo River is an important feature of Crawford County and it has received the nickname of the crookedest river in Wisconsin.

Maps throughout this post were created using ArcGIS® software by Esri. ArcGIS® and ArcMap™ are the intellectual property of Esri and are used herein under license. Copyright © Esri. All rights reserved. For more information about Esri® software, please visit www.esri.com

In this project, what I wanted to do was take a look at the riparian zones around the Kickapoo River, particularly areas that I think may be at greater risk for pollution from run off due to degrades riparian buffers.  I downloaded an image from the U.S. geological service and did multiple forms of remote sensing analysis.  The processes I performed are listed below

Haze reduction

Image subset

Laplacian edge detection

Normalized Difference vegetation Index

Remote Sensing Analysis

My first step was to download the satellite image that I wanted to use for my project.  I searched on USGS global visualization viewer to find the area that I wanted to study.  I had already signed up for an account and since I had found an image that was listed as downloadable, downloading the satellite image went relatively smoothly.  I then unzipped the downloaded file and saved it to a folder. 

I then opened Erdas Imagine and selected import data under manage data.  I input the TIFF files I had, to get the output img files that I wanted. The next step was to layer stack these image files.  I made a mistake originally by stacking all of the layers 1-7, and the image appeared with strange colorations on it.  I then went back and excluded band 6 the thermal layer and then the image appeared normal.

Stacked Image (USGS, 2014)

 

 

The Image was somewhat hazy, so I performed a haze reduction, clicking under raster and radiometric and then clicking haze reduction and saving my output file in a folder labeled Haze reduction

 

Image with Haze reduction

 

Next I decided to take a subset image of Crawford County.  To do this I changed the projection of the Crawford county shapefile to match the projection of the image.  Then I imported the image, selected it and made it an area of interest and then performed a subset and clip.

Subset Image of Crawford County

 

Next I wanted to more easily distinguish the Kickapoo River, so I applied a Laplacian edge detection to the image.  I went to raster, spatial, convolution and selected Laplacian edge detection and then saved the resulting image in a folder labeled edge effects.  The Kickapoo River can be seen more noticeably in this photograph essentially highlighted in red.

Crawford County with Laplacian edge detection

Next I wanted to look specifically at levels of vegetation, so I went under raster unsupervised and performed a Normalized Difference Vegetation Index saving the resulting image in a folder labeled NDVI.

Crawford County NDVI Image

 

The next step in my project was to sync the viewer to Google earth.  Using the NDVI image and the Laplacian edge detection image I was able to find the Kickapoo River and find areas along it that had little to no vegetation.  I was able to find four areas along the River that have little vegetative barrier and are relatively exposed to pollution and runoff from adjacent farms, mining operations and communities

 

Conclusions

 

 

Sources

 

 

U.S. Geological Survey (2014) Landsat Scene "LT50250302011256PAC01" [Satellite photograph]

            Retrieved from http://glovis.usgs.gov/

ESRI (2013) Topographic Base Map [Raster Layer]

            Retrieved from ArcMap 10.2

ESRI (2013) Imagery Base Map [Raster Layer]

            Retrieved from ArcMap 10.2

ESRI (2013) US Counties [Shapefile]

            Retrieved from ESRI 2013 geodatabase

Google Earth (2014) Crawford County, Wisconsin [Aerial Photography]

            Retrieved from Google Earth Pro