Exercise 5: Part 2 - Data Gathering

Goals and Objectives

The goal of this assignment, part 1, was to become familiar with the process of downloading data from different sources on Internet, importing the data to ArcGIS, projecting the data from the different sources into one coordinate system, then building and designing a geodatabase to store the data.  The lab also has the goal of working with metadata to check the accuracy of the data and their sources.  This blog post will cover how and where the data was downloaded, some maps to show the some of the data and raster's converted in pyscripter with maps. Then the blog will go over the data accuracy by collecting the metadata from each source.  

General Methods

Data was obtained from multiple websites and was stored in our class folder.  However because this website data contains so much storage the data, in the form of a zip file, was first saved in a temporary folder that will delete files after 30 days.  The zip file was then extracted into our personal class folder for future use.  The data from these sites the class is interested in is strictly in Trempealeau county, clipping the data and projecting it so it can be used in the future was a critical step as can be seen in my previous post 2.

US Department of Transportation, 2014 rail lines were downloaded.  This data shows the rail lines located in Trempealeau county.  

http://www.rita.dot.gov/bts/sites/rita.dot.gov.bts/files/publications/national_transportation_atlas_database/index.html 

UGSG National Map Viewer, Trempealeau county had to be selected and land cover 2011 3x3 Extent was downloaded.  Also, another data set was downloaded, National Elevation Dataset 45 (1/3).

http://viewer.nationalmap.gov/viewer/ 

USDA Geospatial Data Gateway, much naviation was needed here to find Trempealeau County and download land cover - cropland data.  

http://datagateway.nrcs.usda.gov/GDGOrder.aspx 

Trempealeau County Land Records, a Trempealeau geodatabase was downloaded from the counties website itself.

http://www.tremplocounty.com/landrecords/

USDA NRCS Web Soil Survey, Soil data was downloaded from this site, which I found to the most difficult, creating an AOI of trempeauleau county was critical in downloading the soil data.  

http://websoilsurvey.sc.egov.usda.gov/App/WebSoilSurvey.aspx

After all the data was downloaded and stored in the correct folders the python script and data were ready to be edited.

Maps

High Value: Green   Low Value: White

High Value: White   Low Value: Black

The maps above represent the process I have taken to download, project, and clip the data into Trempealeau county.  The first three maps are products of projecting and clipping them into Trempealeau county through pyscripter. As you can see all three were successful and will be used in future labs when analyzing frac sand mining.  

Data Accuracy

Numbers in red were calculated by myself from lecture
and Lo Chapter 4

Finding all of the metadata for each data set was very difficult because the metadata did not include all of the necessary information.  Some of the data accuracy fields had to be calculated by hand from lecture notes and from readings.  

Attribute accuracy is defined as the closeness of the descriptive data in the geographic database to the true or assumed values of the real-world features that they represent.  For the metadata of the lab I could not find any information on the attribute accuracy, however the minimum level of accuracy in identifying land-use and land cover categories should be at least 85 percent. 

Minimal Mapping Unit is the smallest polygon or feature mapped on the raster or vector.  When working with a small scale mapping a tiny park area inside a urban is not necessary because of the size of the scale. 

Conclusion

I found this lab to the most challenging of my college career, from downloading the data, writing the python script, and finding the metadata took a great amount of time.  However, I feel like I learned a lot about the challenging things above especially navigating the data to keep it one place and writing the python script to specify the rasters. When using the data sets in future labs I want to be able to understand the attribute tables better especially the soils data.  The soils attribute table help a lot of information after joining and the map it created was confusing.  Metadata is something of great importance and I feel I did not do a great job in finding all of the necessary steps.  Improving on this is a goal before I graduate.   

Exercise 5: Part 1 - Python Script

Introduction

Post 2 will cover the python script created for the 2nd part of the lab.  The first part of the lab will be discussed in post 3.  The objectives of this lap were to write a Python script to project, clip, and load all the data into a geodatabase.  

Python is a open source programming language that uses a scripting language to run functions of programs.  In our case (GIS II) we write python scripts in for ArcGIS especially ArcMap.  Python is a common application used in the work field and will be viable for our future in working and finding a job.  For this assignment the python script will project, clip, and store the rasters that were downloaded, see part 3, into the Trempealeau county database.  We will use these newly projected rasters in futures labs when analyzing sand mining in Trempealeau county.  For more about Python you can click here or here. 

Python Script

Figure 1: Completed Python Script

Above you can see the completed python script and the results of the new rasters can be seen in part 3 of my blog.  They script took a while to complete and a one error that gave me trouble was I had name my folder raster and the script would not run, giving me errors.  Because there were so many raster words in the script I changed the folder name to part 2 and the script was able to run clean.  As I stated earlier the completed raster's can be seen in part 3 of the lab.

Exercise 4: Sand Mining in Western Wisconsin Overview

Introduction

Frac Sand Mining in Wisconsin has been occurring for over 100 years, but recently their has been an increase in the mining for the use of hydraulic fracturing.  The sand mining is primarily located in western Wisconsin as you can see in figure 2 below, because of the abundant amount of sandstone that fits the needs of the hydraulic fracturing mines.  Throughout the semester our GIS (Geographic Information Systems) II class will analyze and investigate the impacts of sand mining in western Wisconsin. This post will be an introduction to sand mining with the following post being more detailed into the project.  

Hydraulic Fracturing 

Figure 1: This image shows the drill process and how
the sand is used to keep the cracks open.
http://www.h2odistributors.com/contaminant-fracking.asp 

First a background on what hydraulic fracturing is will be given because the frac sand's primary use is for hydraulic fracturing.  This process involves drilling thousands of feet beneath the earth's surface to create cracks in rock.  This process is used to extract oil or natural gas in places like Texas, North Dakota, and others.  After the the cracks in the rocks are created the frac sand, along with water and chemicals, is pumped below to keep the cracks open so the oil and natural gas can be extracted.  With recent technological advancements, horizontal drilling, it is possible to extract oil and natural gas that was previously not available along with need for fuel is causing the demand for frac sand from Wisconsin to rise.

Frac Sanding Mining in Wisconsin

Figure 2: Locations of Frac Sand Mines and Sandstone in Wisconsin
http://curiousterrain.wordpress.com/2012/10/30/frac-sand-in-wisconsin/

Wisconsin has an a great amount of resources of sand and has been mined in Wisconsin since the 19th century for many different uses.  Frac sand is silica sand or silicon dioxide SiO2, quartz.  It has many uses including: paving roads, filtering drinking water, and used in the hydraulic fracturing process.  Most sand is mined and recent demand is used for the of hydraulic fracturing process  The sand deposits and mines are primarily located in western Wisconsin, as seen if figure 2 below.  Because this mining is taking place so close to home our GIS project and the mining being a 'hot topic' it will have a significance.

Figure 3: http://dnr.wi.gov/topic/Mines/documents/
SilicaSandMiningFinal.pdf

However, not all silica sand can be used for hydraulic fracturing, it has to meet a specific need.  Wisconsin is lucky enough to have an abundant amount of sand that can meet this needs as illustrated in red in figure 3 below. The removal of this sand from landscapes involves the destruction of land and along with all mines cause environmental problems and hazards.

Impacts of Frac Sand Minding 

Although sand mining  can be very beneficial it has many environment impacts which will be a study through out the semester.

Air Impacts: dust can be released into the air from handling the sand and also pollutants from the equipment used to mine will be released into the air.  This can effect near by farmers or communities which live near the farm.

Water Resources: the mine has the chance of impacting ground water, rivers, and streams by causing them to change path or pollution.  Wells used by near by farmers have the potential to decrease because the ground water has shifted from the mining.  The mine also can impact the runoff of water because of the removal of land, the streams and rivers can pick up sediment when running through a mine, contaminating the water source.  The sand mines also need a lot of water to wash the sand before it is sent to the hydraulic fracturing mine.  This cause the depletion of lakes, rivers, streams and ground water greatly impacting the surrounding area.

Deforestation: to get the sand forest cover must be removed for the mining to take place.  This reduced wildlife habitat and causes them to find a new home.

Mine's location: The location of the mine impacts near by farmers.  Because almost all mines are located in the agricultural fields of western Wisconsin, this cause the mines to buy land and sometimes cause families to be moved.  The noise that also comes from a mine can effect communities wild life and hunting areas.

How GIS will be used in the project

GIS can be used in this project to evaluate the locations of specific mines.  We can also use GIS to detect where the right places or wrong places to build mines may be.  By using land cover data it these places can be predicted.  The following posts will describe how GIS is used when analyzing this project. 

Sources

http://www.h2odistributors.com/contaminant-fracking.asp

http://dnr.wi.gov/topic/Mines/documents/SilicaSandMiningFinal.pdf

http://curiousterrain.wordpress.com/2012/10/30/frac-sand-in-wisconsin/

http://www.jsonline.com/news/wisconsin/frac-sand-mining-splits-communities-b9962665z1-217312971.html