Friday, March 18, 2016

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
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
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
*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

US Web Soil Survey
Raster describing soil types across the United States
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.

2 comments:

  1. Thank you for providing the best information.I can sure this can help to update my knowledge.For more careers and latest GIS Jobs in Hyderabad.

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  2. Hi Morgan:
    Well how is everything in Thailand? I am not sure you will get this message as I really don't understand how this really works. I want to communicate but I guess am dumb about it. I hope you get this message and respond to me so I know if you are getting my messages or not. I have been more than busy busy busy. I think I want to retire ha ha haha ha! Are you laughing yet?? Well I think I should go to bed and get some sleeeeeeeeeeeeeeep. I think it is much needed so I will say goodnight and hope you get this short message and you will know I am thinking about you OK?? Love ya, Granny

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