GIS II Lab 2: Data Gathering

Data Downloading, Interoperability, and Working with Projections in Python

Sand Mining Suitability Project

Goals

Technical Goals

• Familiarization with data downloading from a variety of internet sources
• Prepare data and importing it to ArcGIS
• Join data and building a geodatabase
• Projecting data
• Write a technical report about data sources and accuracy

Project Goals

To demonstrate the technical goals, I will be building a sutiability and risk model for sand mining in western Wisconsin with Trempealeau County and a few other western Wisconsin counties as the area of interest. For this portion of the multi-lab project I:

• Downloaded and prepared relevant data
• Wrote a technical report about the data sources and accuracy
• Produced four maps
• County Location
• County Elevation
• County Land Cover
• County Agriculture Crop Type

General Methods

A variety of  base data was collected for this project from a variety of online sources. Data sets and their descriptions are listed in the table below.  For each set I went to the source website (hyperlinked in the source column), downloaded, unzipped, and saved each file. Additional data preparation is described in the Necessary Preparation column. After all files have been properly prepared, they were added to the Trempealeau County geodatabase

Base Data Set	Description	Source	Necessary Preparation
US Railway Network Shapefile	Shapefile of US railways	National Transportation Atlas Database	Clip data to Trempealeau County, change to Trempealeau County’s Projection
National Land Cover Raster and Digital Elevation Models (DEM) for Trempealeau County	Raster of US land cover types and DEMs for Trempealeau County and surrounding area	United States Geological Survey	Used Mosaic to New Raster tool to combine the two DEMs. *Raster
Wisconsin Crop Cover Raster	Raster describing the types of crop cover across Wisconsin	United States Department of Agriculture	*Raster
Trempealeau County Land Records Geodatabase	Geodatabase containing a variety of datasets for Trempealeau County including Boundaries, Cadastral, Emergency, Land Use, Recreation, and Transportation shapefiles	Trempealeau County Wisconsin
US Web Soil Survey	Raster describing soil types across the United States	United States Department of Agriculture Natural Resources Conservation Service	Imported tabular text files to geodatabase schema. *Raster

*Check out my Python Scripts post Script 1 which describes how rasters were prepared to import to the geodatabase.

Data Accuracy

Base Data Set	Scale	Effective Resolution	Minimum Mapping Unit	Planimetric Coordinate Accuracy	Lineage	Temporal Accuracy	Attribute Accuracy
US Railway Network Shapefile	1:24,000 to 1:100,000	NA	NA	NA	Official Railway Guide, State DOTs, Rail companies, FRA’s Automated Geometry Locations	6/19/2015	NA
National Land Cover Raster	1:100,000	30m	5 pixels	25m	Multi Resolution Land Characteristics	04/09/2004 to 11/11/2011	Not yet conducted
DEMs for Trempealeau County	1:24,000	10m	NA	NA	US. Geological Survey	4/10/2015	NA
Wisconsin Crop Cover Raster	1:100,000	30m	5 pixels	25m	USDA/NRCS/NASS	2002 to 2016	All attributes: accuracy between 85% and 95%
US Web Soil Survey	1:12,000 to 1:63,360	NA	3 acres	0.01in	USDA Soil Conservation Service (1977) National Resources Conservation	2004	All attributes tested against standard tables of valid soil attributes.

Python Scripts

Python is the scripting language that ArcMap uses. This blog series will demonstrate my acquired skills in python by using PyScripter to run tools and queries on desired spatial data. All functions of the series are used to further my GIS II Lab project, Sand Mining Suitability.

Script 1

The purpose of this scrip was to list all of the rasters in the data, convert their projections to the proper projection (NAD_1983_HARN_WISCRS_Trempealeau_County_Feet), and add them to the Trempealeau County Geodatabase.

Script 3

This script has a similar goal to my goal in GIS II Raster Modeling: Raster Analysis. A raster describing the potential impact of sand mining in southern Trempealeau County, Wisconsin is created using the same five criteria as the other lab. This time however, the calculation is performed in pyscripter and the Proximity to Residential Areas variable was weighted.