Upper Midwest Aerospace Consortium - EdParc
User’s Guide
Prairie to Mountain Explorer
Version 2.0
Prairie to Mountain Explorer
Version 2.0
User’s Guide
Prairie to Mountain Explorer
Version 2.0
CDROM Development Team
Patricia McClurg, Project Director
Holly Lerner Copeland, Instructional Designer and GIS Coordinator
Mary O’Neill, GIS Coordinator
Alan Buss, Instructional Designer
Rick Shafer, Technical Assistant
Pam Reid, Artistic Designer
Bimende Malik, GIS Technician
Pravara Thanapura, GIS Technician
Development of Prairie to Mountain Explorer was graciously funded or supported by:
Upper Midwest Aerospace Consortium, NASA
Planetary and Space Science Center (PASS) – Univ. of Wyoming
Wyoming Energy EPSCOR
Title II Eisenhower – Higher Education Competitive Professional Development Program
Environmental Systems Research Institute, Inc.
Education PARC Members
Patricia A. McClurg, Project Director - University of Wyoming
Idaho
Kay Lynn Brothers - University of Idaho
Jo Dodds - O'Leary Junior High School
Dale Johnson - University of Idaho New Century Classroom
Bob Turner - Fernan Elementary School
Montana
George Bailey - University of Montana
Chris Erlien - Montana State University
Mark Lalum - Flathead High School
William Peterson - Cascade Elementary School
Van Shelhamer - Montana State University
North Dakota
Bonny Berryman - Eric Ramstead Middle School
Michael Burton - Discovery Junior High School
Lars Helgeson - University of North Dakota
Bob Klemisch - Custer Elementary & Collins Elementary
Barry Olson - Discovery Junior High School
Roger Palmer - Red River High School
Donald Schwert - North Dakota State University
South Dakota
Joel Albright - Douglas High School
Tony Burns - Douglas Middle School
Deanna Hansen - Axtell Park Middle School
Joseph Hillberry - South Dakota School of Mines & Technology
Kelly Lane - Douglas Middle School
Mary O'Neill - South Dakota State University
Cassie Soeffing - Axtell Park Middle School
Wyoming
Bryan Aivazian - Wyoming Center for Problem-Based Education
Alan Buss - University of Wyoming
Holly Lerner Copeland - University of Wyoming
Dave Hamaker - Niobrara County High School
Greg Lundvall - Washington Elementary School
Table of Contents
1.0 Introduction 7
2.0 Acknowledgements 8
3.0 Hardware and Software Requirements 9
4.0 Installation Notes 10
MAC Install Notes 13
5.0 GIS Data Descriptions 14
5.1 Prairie-Mountain States Data (Regional) 14
Data in “Regional” (Prairie-Mountain States) data folder 14
Data in Regional/Lewiscla data folder 15
Agricultural Crops 15
Livestock 17
Agricultural Data by Zip Code 18
Airports 20
Cities 21
Climate 21
Climate 10k 21
Coal Regions 24
County Boundaries 25
Continental Divide 25
Demographic Data by Pop1990 25
Earthquakes 28
Ecoregions 28
Federal Lands 28
Geology 29
Highways 30
Interstate Highways 30
Lakes 30
Lewis and Clark Route and Camp Sites 30
Linkcity 32
Major Rivers, Creeks and Lakes 32
Mean Annual Temperature by Degrees Fahrenheit 32
Mean Annual Precipitation in Inches 33
National Rivers 33
Pollution Emissions 34
Public Land System Township Boundaries 34
Railroads 35
Rivers 35
Shaded Relief 35
SIR C Shots – HOT! 35
State Boundaries 36
Watersheds 36
5.2 State Data for Idaho, Montana, North Dakota, South Dakota and Wyoming 37
Local Data in “State” folders 37
Agricultural Crops 37
Cities (Idaho, Montana, North Dakota and South Dakota) 37
Cities (Wyoming) 38
Coal Regions 38
County Boundary 38
Demographic Data 38
Faults 38
Glacial Drift Aquifers 39
Landmarks 39
Livestock 40
NDVI (Normalized Difference Vegetation Index) 40
Annual Precipitation (Inches) 42
Soil Properties 43
Species Data 46
Streams/Rivers 51
Watersheds 52
5.3 County Data for Idaho, Montana, North Dakota, South Dakota and Wyoming 53
Local Data in “County” folders 53
County Boundary 53
Elevation Contours 53
Geology 54
Land Cover 55
Land Ownership 58
Shaded Relief 60
Transportation 61
Appendix A: Contact Information 62
Appendix B: Data Distribution and Use Statement 63
1.0 Introduction
Prairie to Mountain Explorer
February 1999
Hello and welcome to the second edition of the Prairie to Mountain Explorer!
This user’s guide contains install and data set information to help you load the data and use them wisely. We hope you find these GIS data useful in your K-12 classrooms. Many hours of work have gone into compiling and preparing the GIS data layers. However, we realize that this product will not be perfect or error free. We encourage you to call or email us with any errors you find or suggestions you have to improve this product.
Sincerely,
The Prairie to Mountain Explorer Team
2.0 Acknowledgements
We would like to gratefully acknowledge the financial support and work done by various others to make this project possible:
…NASA who made this project possible through funding our grant.
…ESRI for their generous financial support of our project and their wonderful K-12 team (George Dailey, Charlie Fitzpatrick, Angie Lee) for lots of help, support, and advice along the way.
…Scott Bassingthwaite and Doug Olsen at the University of North Dakota for producing 10 km climate data sets of temperature, precipitation and growing degree days.
…Dr. Jerry Nielsen at Montana State University for providing guidance in processing the soils data sets.
…Chris Erlien and her students for thoroughly beta-testing and reviewing Prairie to Mountain Explorer before production.
…Lara Merriam for assistance with the User’s Guide.
…Wyoming Water Resources Center, a source for various GIS data and technical support.
…Chalk Butte, Inc. in Boulder, Wyoming for allowing us to reproduce their shaded elevation map of Wyoming.
…Oregon State University for allowing us to use their precipitation data.
3.0 Hardware and Software Requirements
|Hardware/ |Minimum Requirements |Preferred Requirements |
|Software | | |
|Computer |Power MAC or |Power MAC or |
| |486 processor, 33-MHz IBM- |Pentium processor, 133 MHz IBM- |
| |compatible PC |compatible PC |
|Hard Disk Space |200 megabytes |600 megabytes |
|RAM |16 megabytes |32 megabytes |
|Operating System |MAC OS or Windows95 |MAC OS |
| | |Windows95 or greater |
|ArcView 3.0 or 3.1 |ArcView 3.0 |ArcView 3.0a or 3.1 |
Note: We strongly recommend that you use Prairie to Mountain Explorer with the Preferred Requirements. Many K-12 teachers have expressed frustration stemming from the practical difficulties of teaching with under-powered computers.
4.0 Installation Notes
PC and MAC Install Instructions
The complete set of Prairie to Mountain Explorer CDROMs consists of three CDs containing:
1) Idaho and Montana datasets (state and county)
2) North Dakota and South Dakota datasets (state and county)
3) Wyoming (state and county) and Regional (all five states) datasets
These datasets are intended for use with ArcView geographic information system (GIS) software from Environmental Systems Research Institute (ESRI).
You may wish to install all or some of these datasets. Each CD, however, contains more than 500 megabytes of data. Therefore, for most users it will not be practical to install all of the data onto your hard disk.
The procedure below for installing data to your hard disk must be run for each state or regional dataset you wish to install. For example, if you wish to install the Idaho and Regional datasets, you must run the procedure for the Idaho datasets and then run it again to install the Regional datasets (or Regional first and then Idaho – order is not a consideration). Make sure that all datasets installed are stored in the same directory (C:\ is the default location). When installing the Regional data you will have the option of installing 7.5-minute quads for the capital cities in the five states in addition to the standard Regional data. When installing data for the individual states, you will have the option of selecting specific counties for which you may install county datasets in addition to the statewide datasets. Each county dataset will require approximately 3 to 30 megabytes of space. For Wyoming you additionally have the option of installing datasets showing the distribution of various species of animals throughout the state.
If you do not have sufficient space on your hard disk, you can open and run the ArcView project files from the CDROM (see “Running Prairie to Mountain Explorer from the CDROM” on the next page.)
Installing the data onto your hard disk:
Step 1: Put the Prairie to Mountain Explorer CD that corresponds to the state or Regional dataset you wish to load into the CDROM.
Step 2: Run (double-click on) the install file that corresponds to your platform (MAC or PC) and the state or Regional dataset that you wish to install, e.g., Wyoming PC Install.exe or Regional MAC Install.exe.
Step 3: Enter a drive/directory in which to place the data. The installer will automatically create a directory called PTME and put the data in that directory. Do not put the data into a directory that has a space in the name (e.g., GIS Files).
Step 4: For state datasets, click the “Details” button to select the county (or counties) you wish to install. You can install additional counties later, if you wish. You can also install all counties at once.
Step 5: Run ArcView 3.0 or 3.1 and load the “ptmepc.apr” (ArcView 3.0a Windows users), “ptmepc31.apr” (ArcView 3.1 Windows users) or “ptmemac.apr” (ArcView 3.0a Macintosh users) project.
Running Prairie to Mountain Explorer from the CDROM:
Step 1: Put the Prairie to Mountain Explorer CD that corresponds to the state or Regional dataset you wish to load into the CDROM drive.
Step 2: Run ArcView 3.0 or 3.1
Step 3: Open the ArcView project (ptmepc.apr, ptmepc31.apr, or ptmemac.apr) that corresponds to your platform (Mac or PC) and the state or Regional dataset that you wish to install.
Special notes:
1. A 32x CDROM works very well in this mode. Anything less will run, but may be fairly slow.
2. Known bugs: Do not attempt to load an ArcView project for one state, then switch CDROMs to another state without closing ArcView. This will crash ArcView.
MAC Install Notes
To run ArcView 3.0 on a Macintosh, you need a Powermac with at least 16 mb of RAM, preferably more.
Memory Configuration:
You will likely need to re-configure your Macintosh’s memory so that ArcView GIS will run properly. These are some suggestions to try first:
1. Turn virtual memory on. To do this, open the Memory control panel (Open Apple ( Control Panels ( Memory) and set Virtual Memory to on.
2. Increase cache size. To do this, open the Memory control panel (Open Apple ( Control Panels ( Memory) and set the Cache Size to 512K.
3. Allocate more memory to ArcView. To do this: Click once on the ArcView Icon to select it. Choose Get Info from the File menu. In the dialog box that appears, set the Preferred Size to 16,500K.
4. Reduce the number of colors displayed by your monitor. To do this, open the Monitors or Monitors and Sound control panel (Open Apple ( Control Panels ( Monitors or Monitors and Sound). Set the Color Depth to thousands.
Known bug: Sometimes when loading the datasets on a Macintosh, ArcView will bring up a warning message “nls codepage not found.” Simply click OK and continue. This warning will not cause any problems with ArcView.
5.0 GIS Data Descriptions
5.1 Prairie-Mountain States Data (Regional)
Data in “Regional” (Prairie-Mountain States) data folder
|Shapefile Name |Data Description |
|Agcrops.shp |Agriculture data by county for ID, MT, ND, SD, WY |
|Livestoc.shp |Agriculture data for livestock by county for ID, MT, ND, SD, WY |
|Ag_zips.shp |Agriculture data by zip code for ID, MT, ND, SD, WY |
|Airports.shp |Airfields for ID, MT, ND, SD, WY |
|Cities.shp |Cities in ID, MT, ND, SD, WY |
|Climate.shp |Climate zone boundaries, mean annual temperature and mean annual precipitation for ID, |
| |MT, ND, SD, WY |
|Climate10k.shp |Climate data (precipitation, temperature, growing degree days) by 10k cell for ID, MT, |
| |ND, SD, WY |
|Coal.shp |Coal bearing regions for ID, MT, ND, SD, WY |
|County.shp |County boundary file for ID, MT, ND, SD, WY |
|Demograp.shp |Demographic Data by county for ID, MT, ND, SD, WY |
|Ecoregn.shp |Ecoregions by Bailey for ID, MT, ND, SD, WY |
|Fedland.shp |Federal lands for ID, MT, ND, SD, WY |
|Geology.shp |Geology for ID, MT, ND, SD, WY |
|Highway.shp |Major Roads for ID, MT, ND, SD, WY |
|Na_roads.shp |Interstate roads |
|Lakes.shp |Major Lakes for ID, MT, ND, SD, WY |
|Linkcity.shp |Capital cities in ID, MT, ND, SD, WY with hot link information |
|Majriver.shp |Major rivers in ID, MT, ND, SD, WY. Derived from EPA Basins “Reaches” file. |
|Na_river.shp |Major North America rivers |
|Climate.shp |Mean average temperature and precipitation |
|Emissions.shp |Air pollution emission data for sites in ID, MT, ND, SD, WY |
|Plss.shp |Public Land Survey System township boundaries for ID, MT, ND, SD, WY |
|Railroad.shp |Railroads for ID, MT, ND, SD, WY |
|Reaches.shp |Reach (rivers) file for ID, MT, ND, SD, WY from EPA Basins |
|Rivers.shp |Rivers for ID, MT, ND, SD, WY from USGS DLG |
|Sirc_loc.shp |Spaceborne Imaging Radar CD-ROM |
|State.shp |State boundary file for ID, MT, ND, SD, WY |
|US_quake.shp |Major US earthquakes since 1970 |
|US48_div.shp |Continental divide line for the US |
|Watershe.shp |Watershed boundaries for ID, MT, ND, SD, WY |
Data in Regional/Lewiscla data folder
|Shapefile Name |Data Description |
|Key_pass.shp |Key passes traversed by the expedition |
|La_pur1.shp |Louisiana Purchase |
|Lc_sites.shp |Lewis and Clark camp site points |
|Lewiscla.shp |Lewis and Clark route |
Agricultural Crops
Source: 1992 Census of Agriculture, U.S. Department of Commerce, Bureau of the Census
General Description: Selected crop data are presented by county. All data are presented in acres or 10ths of acres for the county. A value of –99 for a given county indicates that No Data are available for that county because there are no crops of that type, or the numbers are not counted because they would violate privacy/disclosure laws.
Attribute Description:
Shape- polygon- ArcView shape category
Name– name of the county
State_Name- state that the county is in
State_fips- Federal Information Processing Standard code for state
Cnty_fips- Federal Information Processing Standard code for county
Fips – Federal Information Processing Standard code for state and county
Acres- area of the county, in acres
Barley_92 – Barley for grain, harvested (acres) in 1992
Barley_87 – Barley for grain, harvested (acres) in 1987
Barley_82 – Barley for grain, harvested (acres) in 1982
Wheat_92 – Wheat for grain, harvested (acres) in 1992
Wheat_87 – Wheat for grain, harvested (acres) in 1987
Wheat_82 – Wheat for grain, harvested (acres) in 1982
Irrwheat_92 – Wheat for grain, irrigated (acres) in 1992
Irrwheat_87 – Wheat for grain, irrigated (acres) in 1987
Irrwheat_82 – Wheat for grain, irrigated (acres) in 1982
Corn_92 – Corn for grain, harvested (acres) in 1992
Corn_87 – Corn for grain, harvested (acres) in 1987
Corn_82 – Corn for grain, harvested (acres) in 1982
Potato_92 – Irish Potatoes, harvested (10ths of acres) in 1992
Potato_87 – Irish Potatoes, harvested (10ths of acres) in 1987
Potato_82 – Irish Potatoes, harvested (10ths of acres) in 1982
Sorghum_92 – Sorghum, harvested (acres) in 1992
Sorghum_87 – Sorghum, harvested (acres) in 1987
Sorghum_82 – Sorghum, harvested (acres) in 1982
Alfalfa_92 – Alfalfa for grain, harvested (acres) in 1992
Alfalfa_87 – Alfalfa for grain, harvested (acres) in 1987
Alfalfa_82 – Alfalfa for grain, harvested (acres) in 1982
Hay_92 - Hay-alfalfa, other tame, small grain, grass silage, green chop (acres)
Hay_87 - Hay-alfalfa, other tame, small grain, grass silage, green chop (acres)
Hay_82 - Hay-alfalfa, other tame, small grain, grass silage, green chop (acres)
Irrhay_92 – Hay-alfalfa, other tame, small grain, grass silage, green chop. Irrigated (acres) in 1992
Irrhay_87 – Hay-alfalfa, other tame, small grain, grass silage, green chop. Irrigated (acres) in 1987
Irrhay_82 – Hay-alfalfa, other tame, small grain, grass silage, green chop. Irrigated (acres) in 1982
Oats_92 – Oats for grain, harvested (acres) in 1992
Oats_87 - Oats for grain, harvested (acres) in 1987
Oats_82 - Oats for grain, harvested (acres) in 1982
Sugarbt_92 - Sugar beets for sugar, harvested (acres) in 1992
Sugarbt_87 - Sugar beets for sugar, harvested (acres) in 1987
Sugarbt_82 - Sugar beets for sugar, harvested (acres) in 1982
Irrigat_92 – Irrigated land (acres) in 1992
Irrigat_87 – Irrigated land (acres) in 1987
Irrigat_82 – Irrigated land (acres) in 1982
Apples_92 – Apples (10ths of acres) in 1992
Apples_87 – Apples (10ths of acres) in 1987
Apples_82 – Apples (10ths of acres) in 1982
Drybean_92 – Dry edible beans – excl. lima beans, harvested acres in 1992
Drybean_87 – Dry edible beans – excl. lima beans, harvested acres in 1987
Drybean_82 – Dry edible beans – excl. lima beans, harvested acres in 1982
Sunflwr_92 – Acres of Sunflower Seed, harvested in 1992
Sunflwr_87 – Acres of Sunflower Seed, harvested in 1987
Sunflwr_82 – Acres of Sunflower Seed, harvested in 1982
Veg_92 – Land used for Vegetables, harvested (10ths of acres) in 1992
Veg_87 – Land used for Vegetables, harvested (10ths of acres) in 1987
Veg_82 – Land used for Vegetables, harvested (10ths of acres) in 1982
Bees_92 – Number of Bee Colonies and Honey in 1992
Bees_87 – Number of Bee Colonies and Honey in 1987
Bees_82 – Number of Bee Colonies and Honey in 1982
Livestock
Source: 1992 Census of Agriculture, U.S. Department of Commerce, Bureau of the Census
General Description: Selected livestock data are presented by county. A value of –99 for a given county indicates that No Data are available for that county because there are no livestock of that type, or the numbers are not counted because they would violate privacy/disclosure laws.
Attribute Description:
Shape- polygon- ArcView shape category
Name- name of the county
State_name- name of the state
Fips- Federal Information Processing Standard code for state and county
Acres- area of the county, in acres
State- state that the polygon is in
Cattle_92 – inventory 1992, number of head of cattle
Cattle_87 – inventory 1987, number of head of cattle
Cattle_82 – inventory 1982, number of head of cattle
Milkcow_92 – inventory 1992, number of head of milk cows
Milkcow_87 – inventory 1987, number of head of milk cows
Milkcow_82 – inventory 1982, number of head of milk cows
Beefcow_92 – inventory 1992, number of head of beef cows
Beefcow_87 – inventory 1987, number of head of beef cows
Beefcow_82 – inventory 1982, number of head of beef cows
Sheep_92 – inventory 1992, number of head of sheep
Sheep_87 – inventory 1987, number of head of sheep
Sheep_82 – inventory 1982, number of head of sheep
Shshorn_92 – inventory 1992, number of head of sheep and lambs shorn
Shshorn_87 – inventory 1987, number of head of sheep and lambs shorn
Shshorn_82 – inventory 1982, number of head of sheep and lambs shorn
Hogs_92 – inventory 1992, number of head of hogs and pigs
Hogs_87 – inventory 1987, number of head of hogs and pigs
Hogs_82 – inventory 1982, number of head of hogs and pigs
Broiler_92 – inventory 1992, number of broilers and other meat-type chickens
Broiler_87 – inventory 1987, number of broilers and other meat-type chickens
Broiler_82 – inventory 1982, number of broilers and other meat-type chickens
Mlkgoat_92 – inventory 1992, number of head of milk goats
Mlkgoat_87 – inventory 1987, number of head of milk goats
Mlkgoat_82 – inventory 1982, number of head of milk goats
Agricultural Data by Zip Code
Source: 1992 Census of Agriculture, U.S. Dept. of Commerce, Bureau of the Census
General Description: Selected farm count data are presented for all zip code regions. Data items include total number of farms; farms by size; operator characteristics; cropland harvested, land use characteristics; value of agricultural products sold; inventory and sale of livestock and poultry items; and major crops harvested.
Note: This dataset must be added as an ArcView theme from the CDROM. It does not get copied to the hard drive along with the other Regional datasets.
Attribute Description:
Shape- polygon- ArcView shape category
Area- area of the polygon in square miles
Zip- zip code that the polygon falls under
Po_Name- name of zip code polygon
State- state that the polygon is in
Sumblkpop- summary of the bulk population for the zip code polygon
Pop1996- estimated population for the polygon in 1996
Other Attributes:
|FARMS |Farms by size all farms |
|LAND1 |Farms by size 1 to 49 acres |
|LAND2 |Farms by size 50 to 999 acres |
|LAND3 |Farms by size 1,000 acres or more |
|SALES1 |Market value of agricultural products sold total farms |
|SALES2 |Market value of agricultural products sold less than $10,000 |
|SALES3 |Market value of agricultural products sold $10,000 or more |
|SALES6 |Market value of crops sold including nursery greenhouse, total |
|SALES8 |Market value of grains sold total farms |
|SALES9 |Market value of grains sold $100,000 or more |
|SALES10 |Market value of corn for grain sold total farms |
|SALES12 |Market value of wheat for grain sold total farms |
|SALES14 |Market value of soybeans for beans sold total farms |
|SALES16 |Market value of sorghum for grain sold total farms |
|SALES18 |Market value of barley for grain sold total farms |
|SALES20 |Market value of oats for grain sold total farms |
|SALES22 |Market value of other grains sold total farms |
|SALES28 |Market value of hay, silage, and field seeds sold total farms |
|SALES32 |Market value of fruits, nuts, and berries sold total farms |
|SALES34 |Market value of nursery and greenhouse crops sold total farms |
|SALES36 |Market value of other crops sold total farms |
|SALES38 |Market value of livestock, poultry, and their products sold total farms |
|SALES40 |Market value of poultry & their products total farms |
|SALES42 |Market value of dairy products sold less total farms |
|SALES44 |Market value of cattle and calves sold total farms |
|SALES45 |Market value of cattle and calves sold $50,000 or more |
|SALES46 |Market value of hogs and pigs sold total farms |
|SALES48 |Market value of sheep, lambs, and wool sold total farms |
|SALES49 |Market value of sheep, lambs, and wool sold $50,000 or more |
|SALES50 |Market value of horses and ponies of all ages sold total farms |
|SALES52 |Market value of other livestock and livestock products sold total farms |
|OWNER1 |Full owners |
|OWNER2 |Part owners |
|TENANT |Tenants |
|OPERAT3 |Operators living on the farm operated |
|OPERAT4 |Operators not living on the farm operated |
|OPERAT5 |Operators not reporting place of residence |
|OPERAT6 |Operators by days of work off the farm, none |
|OPERAT7 |Operators by days of work off the farm, any |
|OPERAT8 |Operators by days of work off the farm 1 to 99 |
|OPERAT9 |Operators by days of work off the farm 100 to 199 |
|OPERAT10 |Operators by days of work off the farm 200 days or more |
|OPERAT11 |Operators by days of work off the farm, not reported. |
|CROP1 |Cropland harvested total farms |
|CROP2 |Cropland harvested 1 to 49 acres |
|CROP3 |Cropland harvested 50 to 499 acres |
|CROP4 |Cropland harvested 500 acres or more |
|CROP5 |Cropland used for pasture or grazing total farms |
|CROP7 |Cropland in cover crops, legumes, and soil improvement grasses not harvested and not pastured|
| |total farms |
|CROP11 |Cropland in cultivated summer fallow total farms |
|CROP13 |Cropland idle total farms |
|WOOD1 |Total woodland total farms |
|PAST1 |Pasture and rangeland other than cropland or woodland pastured total farms |
|PAST2 |Pasture and rangeland other than cropland or woodland pastured 100 acres or more |
|OLAND1 |All other land total farms |
|CONSR1 |Land under Conservation Reserve or Wetlands Reserve Programs total farms |
|CONSR2 |Land under Conservation Reserve or Wetlands Reserve Programs 100 acres or more |
|CATTLE1 |Cattle and calves inventory total farms |
|CATTLE2 |Cattle and calves inventory 1 to 49 head |
|CATTLE3 |Cattle and calves inventory 50 to 199 head |
|CATTLE4 |Cattle and calves inventory 200 or more head |
|BEEF1 |Beef cow inventory total farms |
|BEEF2 |Beef cow inventory 1 to 49 head |
|BEEF3 |Beef cow inventory 50 to 199 head |
|BEEF4 |Beef cow inventory 200 or more head |
|MILK1 |Milk cow inventory total farms |
|MILK2 |Milk cow inventory 100 or more head |
|CATTLE5 |Cattle and calves sold total farms |
|CATTLE6 |Cattle and calves sold 1 to 49 head |
|CATTLE7 |Cattle and calves sold 50 to 199 head |
|CATTLE8 |Cattle and calves sold 200 or more head |
|HOGS1 |Hogs and pigs inventory total farms |
|HOGS5 |Hogs and pigs sold total farms |
|SHEEP1 |Sheep and lambs inventory total farms |
|SHEEP2 |Sheep and lambs inventory 1 to 24 |
|SHEEP3 |Sheep and lambs inventory 25 or more |
|HENS1 |Hens & pullets laying age inventory total farms |
|HORSE1 |Horses and ponies of all ages inventory total farms |
|BROIL1 |Broilers & other meat type chickens sold total farms |
|TURKE1 |Turkeys sold total farms |
|CORN1 |Corn for grain total farms |
|CORN5 |Corn for silage total farms |
|SORGHU1 |Sorghum for grain total farms |
|WHEAT1 |Wheat for grain total farms |
|WHEAT2 |Wheat for grain 1 to 49 acres |
|WHEAT3 |Wheat for grain 50 to 249 acres |
|WHEAT4 |Wheat for grain 250 acres or more |
|BARLEY1 |Barley for grain total farms |
|OATS1 |Oats for grain total farms |
|RICE1 |Rice, total farms |
|SUNFL1 |Sunflower seed total farms |
|COTTON1 |Cotton total farms |
|SOYBEA1 |Soybeans for beans total farms |
|DRYEDI1 |Dry edible beans total farms |
|IRISH1 |Irish potatoes total farms |
|SUGARB1 |Sugar beets for sugar total farms |
|SUGARB2 |Sugar beets for sugar 1 to 49 acres |
|SUGARB3 |Sugar beets for sugar 50 to 249 acres |
|SUGARB4 |Sugar beets for sugar 250 acres or more |
|PEANUT1 |Peanuts for nuts total farms |
|HAY1 |Hay-alfalfa, other tame, small grain, etc. total farms |
|HAY2 |Hay-alfalfa, other tame, small grain, etc. 1 to 49 acres |
|HAY3 |Hay-alfalfa, other tame, small grain, etc. 50 to 249 acres |
|HAY4 |Hay-alfalfa, other tame, small grain, etc. 250 acres or more |
|VEGETA1 |Land used for vegetables total farms |
|VEGETA2 |Land used for vegetables 0.1 to 14.9 acres |
|VEGETA3 |Land used for vegetables 15.0 to 99.9 acres |
|VEGETA4 |Land used for vegetables 100.0 acres or more |
|ORCHAR1 |Land in orchards total farms |
|BERRIE1 |Berries total farms |
Airports
Source: USGS Digital Line Graph, 1:2,000,000
General Description: This theme shows airports in ND, SD, ID, MT, WY
Attribute Description:
Shape- point - ArcView shape category
Name- name of the airport
Cities
Source: USGS National Atlas, 1970
General Description: This theme shows cities in ND, SD, ID, MT, WY. Note: there are many small towns where the population is reported as “-99” which indicates no population data for this town in this data set. In general, these towns have a population less than 100 persons.
Attribute Description:
Shape- point- ArcView shape category
Area- a code for the area, which is 0 for points
Perimeter- a code for the perimeter, which is 0 for points
Feature- describes the population category of the city
Name- name of the city or town
Fips– Federal Information Processing Standard code for county and state
Population– population of the city or town (See note above)
Climate
Source: National Climatic Data Center
General Description: This is data of climate divisions from the National Climatic Data Center. It was intended for displaying regional maps of precipitation and temperature.
Attribute Description:
Shape- polygon-ArcView shape category
Area-area of the polygon, in decimal degrees
Perimeter-perimeter of the polygon, in decimal degrees
Name-the name of the region in state
State-state name
Mean_prec-mean precipitation values for the area, in inches
Std_prec-standard deviation for precipitation value
Mean_temp-mean temperature values for the area, in Fahrenheit
Std_temp-standard deviation
Pct-unknown value
Climate 10k
Source: National Climatic Data Center (NCDC), University of North Dakota
General Description: This map has polygons that are 10 x 10 kilometers showing climate variables: temperature, precipitation, and Growing Degree Days (day degrees).
Background on Growing Degree Days:
Growing Degree Days are the number of degrees above the base temperature accumulated over the month represented. For example, if the number of Growing Degree Days is 1000, then the temperature was a total of 1000 degrees above the base temperature for the entire period of record. For instance, on day 1 the temperature was 85 degrees Fahrenheit and on day 2, the temperature was 70 degrees Fahrenheit. Using a base temperature of 50 degrees, the total number of growing degree days for those 2 days would be 55 (growing degree days= 85-50 + 70-50).
Different base temperatures were chosen because they relate to the biological differences between plants. Listed below are crops and the base temperatures for which growing degree days are calculated.
|Base Temperature |Crops |
|32 |Wheat, Barley, Rye, Oats, Flax |
|40 |Wheat, Barley, Rye, Oats, Flax |
|45 |Sunflowers, Potatoes |
|50 |Corn, Soybeans |
Data Processing Notes:
These values are derived from individual station data modeled using inverse distance weighting to a 10 km grid. The data are then assigned to the matching 10km shape file.
The growing degree data set represents accumulated growing degrees by month using four separate base temperatures, 32, 40, 45, and 50 degrees. This data set was created by:
1. Querying the 30 daily climatological data set for each day in a single month.
2. Creating 4 fields, base_32, base_40, base_45, base_50. Each field was populated by subtracting the average temperature for the day from the base number.
3. Each station’s records were summed for the month to create a monthly total average growing degree day for each field (base number).
4. The resulting data set was modeled and assigned using the same process as the monthly climatology data set. Notes: Extensive quality control was implemented on the initial data set resulting in a significant loss of station density. Stations that did not meet quality standards were not used in developing growing degree day's.
Attribute Description:
Shape- polygon – ArcView shape category
Area- area of the cell in sq. meters
Perimeter- perimeter of the cell, in meters
Z0kmgrid_- internal ArcView code that uniquely identifies the grid cell
Jan_prcp- January total precipitation, in inches
Jan_tmax- January maximum temperature, in Fahrenheit
Jan_tmin- January minimum temperature, in Fahrenheit
Jan_tavg- January average temperature, in Fahrenheit
Feb_prcp- February total precipitation, in inches
Feb_tmax- February maximum temperature, in Fahrenheit
Feb_tmin- February minimum temperature, in Fahrenheit
Feb_tavg- February average temperature, in Fahrenheit
Mar_prcp- March total precipitation, in inches
Mar_tmax- March maximum temperature, in Fahrenheit
Mar_tmin- March minimum temperature, in Fahrenheit
Mar_tavg- March average temperature, in Fahrenheit
Apr_prcp- April total precipitation, in inches
Apr_tmax- April maximum temperature, in Fahrenheit
Apr_tmin- April minimum temperature, in Fahrenheit
Apr_tavg- April average temperature, in Fahrenheit
May_prcp- May total precipitation, in inches
May_tmax- May maximum temperature, in Fahrenheit
May_tmin- May minimum temperature, in Fahrenheit
May_tavg- May average temperature, in Fahrenheit
Jun_prcp- June total precipitation, in inches
Jun_tmax- June maximum temperature, in Fahrenheit
Jun_tmin- June minimum temperature, in Fahrenheit
Jun_tavg- June average temperature, in Fahrenheit
Jul_prcp- July total precipitation, in inches
Jul_tmax- July maximum temperature, in Fahrenheit
Jul_tmin- July minimum temperature, in Fahrenheit
Jul_tavg- July average temperature, in Fahrenheit
Aug_prcp- August total precipitation, in inches
Aug_tmax- August maximum temperature, in Fahrenheit
Aug_tmin- August minimum temperature, in Fahrenheit
Aug_tavg- August average temperature, in Fahrenheit
Sep_prcp- September total precipitation, in inches
Sep_tmax- September maximum temperature, in Fahrenheit
Sep_tmin- September minimum temperature, in Fahrenheit
Sep_tavg- September average temperature, in Fahrenheit
Oct_prcp- October total precipitation, in inches
Oct_tmax- October maximum temperature, in Fahrenheit
Oct_tmin- October minimum temperature, in Fahrenheit
Oct_tavg- October average temperature, in Fahrenheit
Nov_prcp- November total precipitation, in inches
Nov_tmax- November maximum temperature, in Fahrenheit
Nov_tmin- November minimum temperature, in Fahrenheit
Nov_tavg- November average temperature, in Fahrenheit
Dec_prcp- December total precipitation, in inches
Dec_tmax- December maximum temperature, in Fahrenheit
Dec_tmin- December minimum temperature, in Fahrenheit
Dec_tavg- December average temperature, in Fahrenheit
Ddmar_32- Number of degree days for March. Base temperature = 32
Ddmar_40- Number of degree days for March. Base temperature = 40
Ddmar_45- Number of degree days for March. Base temperature = 45
Ddmar_50- Number of degree days for March. Base temperature = 50
Ddapr_32- Number of degree days for April. Base temperature = 32
Ddapr_40- Number of degree days for April. Base temperature = 40
Ddapr_45- Number of degree days for April. Base temperature = 45
Ddapr_50- Number of degree days for April. Base temperature = 50
Ddmay_32- Number of degree days for May. Base temperature = 32
Ddmay_40- Number of degree days for May. Base temperature = 40
Ddmay_45- Number of degree days for May. Base temperature = 45
Ddmay_50- Number of degree days for May. Base temperature = 50
Ddjun_32- Number of degree days for June. Base temperature = 32
Ddjun_40- Number of degree days for June. Base temperature = 40
Ddjun_45- Number of degree days for June. Base temperature = 45
Ddjun_50- Number of degree days for June. Base temperature = 50
Ddjul_32- Number of degree days for July. Base temperature = 32
Ddjul_40- Number of degree days for July. Base temperature = 40
Ddjul_45- Number of degree days for July. Base temperature = 45
Ddjul_50- Number of degree days for July. Base temperature = 50
Ddaug_32- Number of degree days for August. Base temperature = 32
Ddaug_40- Number of degree days for August. Base temperature = 40
Ddaug_45- Number of degree days for August. Base temperature = 45
Ddaug_50- Number of degree days for August. Base temperature = 50
Ddsep_32- Number of degree days for September. Base temperature = 32
Ddsep_40- Number of degree days for September. Base temperature = 40
Ddsep_45- Number of degree days for September. Base temperature = 45
Ddsep_50- Number of degree days for September. Base temperature = 50
Ddoct_32- Number of degree days for October. Base temperature = 32
Ddoct_40- Number of degree days for October. Base temperature = 40
Ddoct_45- Number of degree days for October. Base temperature = 45
Ddoct_50- Number of degree days for October. Base temperature = 50
Coal Regions
Source: This data comes from a USGS digitized 1960 Coal Field of U.S. by Trumbell.
General Description: This theme shows generalized coal regions, and the type and quality of coal found in the area.
Attribute Description:
Shape- polygon – ArcView shape category
Acres- total acreage for each individual coal region
Explanation- description of the type of coal found in the area and its potential value
County Boundaries
Source: USGS Digital Line Graph 1:2,000,000
General Description: This theme shows county boundaries in ID, MT, ND, SD, WY
Attribute Description:
Shape- polygon – ArcView shape category
Name- name of the county
State_name- name of the state in which that county resides
State_fips- Federal Information Processing Standard code for state
Cnty_fips- Federal Information Processing Standard code for county
Area- area of the polygon, in sq. meters
Perimeter- perimeter of the polygon, in meters
Acres- number of acres in county
Continental Divide
Source: Nature Conservancy, ESRI (George Dailey)
General Description: This theme shows where the Continental Divide falls in the United States separating the Pacific and Atlantic watersheds.
Attribute Description:
Shape- polyline – ArcView shape category
State- state in which that section of the continental divide goes through
Record- number for that particular record
Name- Continental Divide
Demographic Data by Pop1990
Source: US Census Bureau “USA Counties 1996”
General Description: Several tables contain demographic information at the county level from the US Census Bureau. The demographic attributes in this table come from Summary Tape File-3B (STF-3B) data published by the U.S. Bureau of the Census based on the 1990 Census of Population.
Attribute Description:
|Shape |Polygon – ArcView shape category |
|Name |Name of the county |
|State_Name |Name of the state |
|Fips |Federal Information Processing Standard for state and county |
|State_fips |Federal Information Processing Standard for state |
|Cnty_fips |Federal Information Processing Standard for county |
|Pop1990 |The total 1990 population for a state (Number) |
|Pop90_sqmi |The 1990 population per square mile for a state (Number) |
|Households |Total number of households (Number) |
|Males |Number of males (Number) |
|Females |Number of females (Number) |
|White |Number of people identified as white (Number) |
|Black |Number of people identified as black |
|Ameri_es |Number of people identified as American Indian, Eskimo, or Aleut |
|Asian_pi |Number of people identified as Asian or Pacific Islander |
|Other |Number of people identified as belonging to a race other than white, black, American Indian, |
| |or Asian |
|Hispanic |Number of people of all races identified as being of Hispanic origin |
|Age_under5 |Number of people 0 to 4 years of age |
|Age_5_17 |Number of people 5 to 17 years of age |
|Age_18_29 |Number of people 18 to 29 years of age |
|Age_30_49 |Number of people 30 to 49 years of age |
|Age_50_64 |Number of people 50 to 64 years of age |
|Age_65_up |Number of people 65 years of age and over |
|Nevermarry |Number of people who have never been married |
|Married |Number of people who are married |
|Separated |Number of people who are separated from their spouse |
|Widowed |Number of people whose spouse died |
|Divorced |Number of people who are divorced |
|Hsehld_1_m |Number of single person male households |
|Hsehld_1_f |Number of single person female households |
|Marhh_chd |Number of households with a married couple and related children |
|Marhh_no_c |Number of households with a married couple and no related children |
|Mhh_child |Number of households with a man and children but no wife |
|Fhh_child |Number of households with a woman and children but no husband |
|Hse_units |Total number of housing units |
|Vacant |Number of housing units that are vacant |
|Owner_occ |Number of housing units that are occupied by the owner |
|Renter_occ |Number of housing units that are occupied by renters |
|Median_val |Median value of all housing units |
|Medianrent |Median rent charged for all housing units that are rented |
|Units_1det |Number of housing units with one detached unit in the structure |
|Units_1att |Number of housing units with one attached unit in the structure |
|Units2 |Number of housing units with two units in the structure |
|Units3_9 |Number of housing units with three to nine units in the structure |
|Units10_49 |Number of housing units with 10 to 49 units in the structure |
|Units50_up |Number of housing units with 50 or more units in the structure |
|Mobilehome |Number of mobile homes or trailers |
|No_farms87 |Number of farms in 1987 |
|Avg_size87 |Average size of farms, in acres, in 1987 |
|Crop_acr87 |Number of acres cropped in 1987 |
|Avg_sale87 |Average agricultural sales, in dollars, in 1987 |
Educate.dbf Attributes:
|St_Fips |Federal Information Processing Standard code for state |
|County_Fips |Federal Information Processing Standard code for county |
|Areaname |county name |
|Tot_enr80 |school enrollment - persons 3 yrs and over enrolled in school 1980 |
|Elem_enr80 |school enrollment - persons 3 yrs and over enrolled in kindergarten and elementary (1-8 yrs) |
| |school 1980 |
|Pri_elem_enr80 |school enrollment - persons 3 yrs and over enrolled in private kindergarten & elementary (1-8 |
| |yrs) school 1980 |
|High_enr80 |school enrollment - persons 3 years and over enrolled in high (1-4 yrs) school 1980 |
|Pri_high_enr80 |school enrollment - persons 3 years and over enrolled in private high (1-4 yrs) school 1980 |
|Tot_enr90 |school enrollment - persons 3 years and over enrolled in school 1990 |
|Elehigh_enr90 |school enrollment - persons 3 years and over enrolled in elementary or high school 1990 |
|College_enr90 |school enrollment - persons 3 years and over enrolled in college 1990 |
|Pop16_19 |persons 16 to 19 years 1990 (population used to calculate high school dropout rates) |
|Yrs_schl80 |yrs of school completed - median school years completed by persons 25 yrs and over 1980 |
|Pop25 |persons 25 years and over 1980 (population used to calculate educational attainment rates) |
|Ed_attain1 |educational attainment - persons 25 yrs and over completing 12 yrs or more of school 1990 |
|Ed_attain2 |educational attainment - persons 25 yrs and over completing less than 9th grade 1990 |
|Ed_attain3 |educational attainment - persons 25 yrs and over completing 9th to 12th grade, no diploma 1990|
Note: The attributes in this file are not included in the Demographic Data by Pop1990 theme. They can, however, be added to the demographic data theme table using the ArcView “link or “join” functions.
Earthquakes
Source: USGS
General Description: Major historical US earthquakes as recorded by the USGS. The theme presents data about the magnitude (Richter Scale), date, and depth.
Attribute Description:
Shape- point, ArcView shape category
Magnitude- magnitude of earthquake in Richter Scale units
Depth- underground depth of the earthquake, in kilometers
Year- year in which earthquake occurred
Month- month in which earthquake occurred
Day- day that earthquake occurred
Intensity- intensity of earthquake, on a scale of 1-10
Ecoregions
Source: USDA Forest Service, compiled by Robert G. Bailey, March 1995
General Description: This theme shows ecosystem geography of the nation as shown on the 1976 map "Ecoregions of the United States." It was first published as an unnumbered publication by the Intermountain Region, USDA Forest Service, Ogden, Utah. An explanation of the basis for the regions delineated on the map was presented elsewhere (Bailey 1983).
In 1993, as part of the Forest Service's National Hierarchical Framework of Ecological Units (ECOMAP 1993), ecoregions were adopted for use in ecosystem management. They will also be used in the proposed National Interagency Ecoregion-Based Ecological Assessments. For further descriptions of attributes, see the ecoregions.txt document in the metadata folder.
Attribute Descriptions:
Shape- polygon - ArcView shape category
Area- area of the polygon in sq. meters
Domain- broadest ecological division
Division- an ecological division subset within domain
Province- an ecological division subset within division
Section- an ecological division subset within province
Federal Lands
Source: USGS Digital Line Graph, 1:2,000,000.
General Description: This theme shows generalized federal land ownership for the five states, describing which federal agency is responsible for the land.
Attribute Description:
Shape- Polygon – ArcView shape category.
Federal Land Type - explains which government agency controls this land
Geology
Source: USGS Digital Data Series DDS-11, Geology of the Conterminous United States at 1:2,500,000 Scale—A Digital Representation of the 1974 P.B. King and H.M. Beikman Map
General Description: This theme shows generalized bedrock geology of the five-state region. Users of this geologic map should respect the intentions of the compilers of the map and some of its limitations. The Geologic Map of the United States (King and Beikman, 1974b) is intended to be used at a scale of 1:2,500,000; it is not intended to be used at a more detailed scale. For instance, Colorado is about 10 inches wide at the published scale of the King and Beikman map. Construction of a geologic map of an area as large and complex as the conterminous United States requires a great deal of generalization. Furthermore, the Geologic Map of the United States is primarily a bedrock map, which depicts geologic materials present beneath the soil or relatively thin mantles of surficial deposits, not necessarily the surficial materials themselves. For example, the map does not depict the glacial deposits in the Northern States, the widespread eolian deposits in the High Plains, and the high-level gravels that mantle older Tertiary and Pre-Tertiary units in much of the Atlantic and Gulf Coastal Plains.
| |Quaternary |2 |
|Cenozoic |Tertiary |66 |
| | | |
| |Cretaceous | |
|Mesozoic | |144 |
| |Jurassic |206 |
| |Triassic |246 |
| |Permian |286 |
| |Pennsylvanian |320 |
| | | |
| |Mississippian |360 |
| | | |
|Paleozoic |Devonian | |
| | |406 |
| |Silurian |438 |
| |Ordovician | |
| | |510 |
| |Cambrian |543 |
|Proterozoic |Veridian |563 |
|Archean |Precambrian |4.6 Billion |
Attribute Description:
Area- area of the polygon, in sq. meters
Perimeter- perimeter of the polygon, in meters
Order- geologic code for rock order
Unit- geologic code for rock type
Rock Description- geologic name for rock type
Acres- area of the geologic polygon in acres
Highways
Source: USGS Digital Line Graph, 1:2,000,000.
General Description: A map of major US highways
Attribute Description:
Shape- polyline – ArcView shape category
Road Types- access and usability of the road
Highway_nu- highway road number
Interstate Highways
Source: USGS Digital Line Graph, 1:2,000,000.
General Description: A map of interstate highways
Attribute Description:
Shape- polyline – ArcView shape category
Route- name of the highway
Country- country that the interstate highway is located in
Lakes
Source: USGS Digital Line Graphs, 1:2,000,000.
Attribute Description:
Shape- polygon – ArcView shape category
Area- area of the polygon, in decimal degrees
Perimeter- perimeter of the polygon, in decimal degrees
Feature- type of lake
Lewis and Clark Route and Camp Sites
Source: George Dailey, at ESRI
General Description: The route which Lewis and Clark followed in their historic exploration of the West (1804 – 1806) and the camp sites that they made
Key Passes Traversed by the Expedition
Attribute data:
Shape- point, ArcView shape category
Countyname- county where the pass is located
Elevation- elevation of site
Quadname- quadrangle map on which pass is located
Name- name of pass
Quadref- USGS quadrangle reference number for hot linking
State- state where the pass is located
Gnis_type- geographic names information system type
Latitude- latitude of site, in decimal degrees
Longitude- longitude of site, in decimal degrees
Louisiana Purchase
Attribute data:
Shape- polygon, ArcView shape category
Name- name given government-purchased land
Lewis and Clark Camp Sites
Attribute data:
Shape- point, ArcView shape category
Areaname- name of campsite
State- state where site located
Arclink- code for hot linking
Lat- latitude of site
Long- longitude of site
West_arr- date the westbound expedition arrived at site
West_dep- date the westbound expedition departed from site
East_arr- date the eastbound expedition arrived at site
East_dep- date the eastbound expedition departed from site
Site_num- numeric code of the site
Lewis and Clark Route
Attribute data:
Shape- polyline, ArcView shape category
Exped_num- numeric code for the expedition number
Exped_seg- descriptive name of segment of expedition
Westbound- segment used in westbound travel
West_da- dates of travel for westbound segment of expedition
West_xpl- explorers involved
Eastbound- segment used in eastbound travel
East_date- dates of travel for segment used in eastbound travel
East_xplor- explorers involved
Linkcity
Source: U.S. Census Bureau TIGER Files
General Description: A point coverage of capital cities in ND, SD, ID, MT, WY, used for hot linking the capital city quads
Attribute Description:
Shape- point- ArcView shape category
Area Name- name of the capital city quad
State- state that the city is in
Latitude and Longitude- latitude and longitude of the city
Huncnt100- number of houses within the city
Pop100- population of the city
Landsqkm- amount of land area covered by the city in square kilometers
Watrsqkm- amount of water within the city in square kilometers
Landsqmi- amount of land area covered by the city in square miles
Watrsqmi- amount of water within the city in square miles
Arclink- path to image location, for hot linking
Image- blank field for hot linking
Major Rivers, Creeks and Lakes
Source: EPA Basins
General Description: Rivers, creeks and lakes that flow year round
Attribute Data:
Shape – polyline – ArcView shape category
Type- code for type of water body: R (river), L (lake), or C (creek)
Rivrch- numeric code for river reach
Pname- common name of water body
State_name- state name that water body is in
State_fips- fips code for the state that the water body is in
Sub_region- region of the US that the water body is in
State_abbr- state abbreviation that water body is in
Mean Annual Temperature by Degrees Fahrenheit
Source: National Climatic Data Center
General Description: This is a map of climate divisions from the National Climatic Data Center. It was intended for displaying seasonal maps of temperature.
Attribute Description:
Shape- polygon – ArcView shape category
Name- name of the climate region
State- state that the climate region is in
Mean_prec- precipitation in inches averaged each year over a period of 30 (1950-1980)
Std_prec- standard deviation in inches from the normal precipitation for a climate region
Mean_temp- average annual temperature for each region in degrees Fahrenheit
Std_temp- standard deviation in degrees Fahrenheit from the mean annual temperature
Mean Annual Precipitation in Inches
Source: National Climatic Data Center
General Description: This is a map of climate divisions from the National Climatic Data Center. This coverage was intended for displaying seasonal maps of precipitation.
Attribute Description:
Shape- polygon – ArcView shape category
Name- name of the climate region
State- name of the state that the climate region is in
Mean_prec- precipitation in inches averaged each year over a period of 30 (1950-1980)
Std_prec- standard deviation in inches from the normal precipitation for a climate region
Mean_temp- average annual temperature for each region in degrees Fahrenheit
Std_temp- standard deviation in degrees Fahrenheit from the mean annual temperature
National Rivers
Source: USGS 1:2,000,000 Digital Line Graphs
General Description: A map of the largest rivers, in US, Mexico and Canada
Attribute Description:
Shape- polyline - ArcView shape category
Name- name of river
System- name of system to which river is tributary
Country- country where river occurs
Pollution Emissions
Source: NAPAP (National Acid Precipitation Assessment Program). NAPAP is a joint venture between the EPA, NOAA, DOE, DOA, and DOI.
General Description: This map displays pollution emission sites throughout the continental USA. It is a combination of the NAPAP (National Acid Precipitation Assessment Program) 1985 inventory and more recent data from 1990. Each point in this coverage represents a factory, power plant or other emission site located within the US. The first four listed pollutants VOC (Volatile Organic Compounds), NOX (Nitrogen Oxides), CO (Carbon Monoxide), and SO2 (Sulfur Dioxide) represent data from 1990. The remaining (pollutants SO4, TSP,..) dates from 1985. This information is reported in tons per year. A code of –99.99 is given where there are no data available.
Attribute Description:
Shape- point - ArcView shape category
State- state by number where the site is located
County- county by number where the site is located
Latitude- the latitudinal location of the emission’s source on the Earth's surface
Longitude- the longitudinal location of the emission’s source on the Earth's surface
Listed Pollutants and Potential Sources:
VOC = Volatile Organic Compounds: motor vehicles, stationary engines, industrial process
NOX = Nitrogen Oxides: motor vehicles, coal, oil, gas, power plants
CO = Carbon Monoxide: automobiles, any combustion
So2 = Sulfur Dioxide: fossil fuel combustion, fires
Tsp = Total Suspended Particulates (particles less than 65 micrometers): diesel engines, smelting, road dust
So4 = Sulfate: similar to sulfur dioxide (fossil fuel combustion, fires)
NH3 = Ammonia: wastewater treatment, ranching, fertilizer
Thc = Total hydro carbons:
Hcl = Hydrochloric Acid: industrial processes, leads to acid rain
Hf = Hydroflouric Acid: industrial processes, leads to acid rain
Name- site where the emissions are coming from
Public Land System Township Boundaries
Source: USGS 1:2,000,000 Digital Line Graphs
General Description: This map contains township and range boundaries for the five-state region (Public Land Survey System).
Attribute Description:
Shape -polyline - ArcView internal code
Major1- USGS code
Major2- USGS code
Minor1- township coordinate
Minor2- range coordinate
Major3- USGS code
Minor3- USGS code
Railroads
Source: USGS Digital Line Graph 1:2,000,000
Attribute Description:
Shape- polyline – ArcView shape category
Length- length of the line, in decimal degrees
Rivers
Source: USGS Digital Line Graph 1:2,000,000
General Description: This theme shows generalized streams, rivers, canals, and reservoirs.
Attribute Description:
Shape- polyline – ArcView shape category
Length- length of the river segment, in decimal degrees
Feature- provides a category for the stream as intermittent, shoreline, dam, canal, and reservoir.
Shaded Relief
Source: USGS
General Description: This image shows the relief in elevation using a shaded technique. The image is projected in Lambert Equal-Area Azimuthal. Central Meridian is -100, reference latitude is 45.
SIR C Shots – HOT!
(Note: Hot Links are available for this theme.)
Source: Spaceborne Imaging Radar CD-ROM
General Description: Spaceborne Imaging Radar-C/X Band Synthetic Aperture Radar (SIR-C/X-SAR) is a joint US-German-Italian project that uses a highly sophisticated imaging radar to capture images of earth that are useful to scientists across a great range of disciplines.
The CD was produced by Jet Propulsion Laboratory following successful flights of the SIR-C missions. It contains radar images from around the world as seen before and during the SIR-C missions.
Attribute Description:
Shape- point – ArcView internal category
Name- name of the SIR-C shot location
Latitude- latitudinal coordinates of the location
Longtitude- longitudinal coordinates of the location
State Boundaries
Source: USGS Digital Line Graph, 1:2,000,000.
General Description: map indicates state boundary lines
Attribute Description:
Shape- polygon – ArcView shape category
State Name- name of the state
State_fips- Federal Information Processing Standard for state
Sub Region- region in which the state falls into
State Abbreviation- shortened abbreviation for the state
Watersheds
Source: USGS, Digital Line Graph, 1:2,000,000
General Description: This theme shows Hydrologic Unit Categories (watersheds) for the five states.
Purpose: This data set will be used for showing drainage basins in various National Water Summary Water-Supply Papers. The primary use will be for regional and national data display rather than specific local data analysis due to the small scale of this coverage.
Attribute Description:
Shape- polygon – ArcView shape category
Area- area of the polygon, in sq. meters
Region- name of water resources region
Subregion- name of water resources subregion
Unit- name of water resources accounting unit
Acres- area for the watershed in acres
5.2 State Data for Idaho, Montana, North Dakota, South Dakota and Wyoming
Local Data in “State” folders
|Shapefile Name |Data Description |
|Agcrops.shp |Agriculture data from the 1992 Census |
|Aquifers.shp |Glacial Drift Aquifers data for North Dakota |
|Demograp.shp |Demographic data from the 1992 Census |
|Faults.shp |Geologic fault lines for Idaho |
|Landmark.shp |Landmark points |
|Livestoc.shp |Livestock data by county |
|NDVI |Normalized Difference Vegetation Index raster images (several .tif files)|
| | |
|Prec-ann.shp |Average annual precipitation contours |
|Rivers.shp |1:500,000 scale rivers data from the EPA Basins dataset |
|Soils.shp |Soil characteristics including clay content, organic matter, and hydric |
| |rating |
|St_bound.shp |State boundary for ID, MT, ND, SD, WY |
|(State abbreviation)_county.shp |County boundary for ID, MT, ND, SD, WY |
|(State abbreviation)_coal.shp |1:500,000 Coal Regions |
|(State abbreviation)_city.shp |City information from TIGER Data |
|(State abbreviation)_geol.shp |1:2,500,000 scale geology data |
|(State abbreviation)pod.shp |Species Point Observation Database (only available for Idaho and Montana)|
| |Individual species distribution maps for Wyoming |
|(Species).shp | |
|Watershe.shp |Watershed boundaries for ID, MT, ND, SD, WY |
Agricultural Crops
These data are the same as those used for the Prairie-Mountain States scale data. See “Agricultural Crops” and “Livestock” in the Prairie-Mountain States section.
Cities (Idaho, Montana, North Dakota and South Dakota)
State: Idaho, Montana, North Dakota, South Dakota
These data are the same as those used for the Prairie-Mountain States scale data. See “Cities” in the Prairie-Mountain States section.
Cities (Wyoming)
State: Wyoming
Source: US Census Bureau TIGER Data, updated and modified by the Wyoming Water Resources Center
General Description: These data show cities and towns in Wyoming.
Attribute Description:
Shape- point - ArcView internal field
Name- name of city
Arealand- area of city in sq. meters
Areawat- area of water in city in sq. meters
Housing- number of houses in the city
Population- population of the city
Longitude- longitude of the city
Latitude- latitude of the city
Coal Regions
These data are the same as those used for the Prairie-Mountain States scale data. See “Coal Regions” data in the Prairie-Mountain States section.
County Boundary
State: All
Source: US Census Bureau TIGER Line Files, 1:100,000.
Attribute Description:
Shape-Polygon – ArcView shape category
Name- name of the county
Demographic Data
These data are the same as those used for the Prairie-Mountain States scale data. See “Demographic Data by Pop1990” in the Prairie-Mountain States section.
Faults
State: Idaho
Source: Bond, J.G. and Wood, C.H., 1978, Geologic Map of Idaho: Idaho Department of Lands, Bureau of Mines and Geology, Scale 1:500,000. Point of contact: Idaho Department of Lands, Bureau of Mines and Geology. Telephone: 208-885-7991 Source material was paper.
General Description and Background: This is a data set showing geologic fault lines of Idaho. The starting point for the digital geology map of Idaho was a paper copy of the published geologic map (Bond and Wood, 1978). The map was processed in ARC/INFO and is considered an accurate geographic representation of the original map. These data are not in decimal degrees.
Source Projection:
Lambert, North American Datum 1927
Units are in meters
33 00 00 /* 1st Standard Parallel
45 00 00 /* 2nd Standard Parallel
-114 00 00 /* Central Meridian
0 0 0 /* Latitude of Projections Origin
0.0 /* False Easting
0.0 /* False Northing
Attribute Description:
Shape- polyline – ArcView shape category
Fault_type- type of fault
Accuracy- postional accuracy of the arcs
Length- length of the fault segment, in meters
Glacial Drift Aquifers
State: North Dakota
Source: North Dakota State Water Commission
General Description: This data set is an ARC/INFO coverage derived from a published map entitled: Map Showing Glacial Drift Aquifers in North Dakota and Estimated Potential Yields, 1986. The map was digitized using MapInfo. The aquifer map is not attributed because of the variability and difficulty associated with identifying individual boundaries between connected aquifer systems.
Coverage: North Dakota Major Glacial Drift Aquifers
Coverage Type: Primarily Regions (Polygons)
Creation Date: 9/1/94
Completed: 10/7/94
Base Map: NDSWC State Aquifer Map (mylar)
Scale: 1:500,000
Attribute Description:
Shape- polygon - ArcView shape category
Landmarks
State: All
Source: US Census Bureau Tiger Data
General Description: This is data showing most landmarks in the five states. Note: most of the specific names for the landmarks in this database are not listed.
Attribute Description:
Shape- point - ArcView shape category
Landmark- ArcView internal code
Landmark_i- ArcView internal code
Laname- name of landmark (Note: Most of these attributes are not available yet.)
Type- category of landmark
Livestock
These data are the same as those used for the Prairie-Mountain States scale data. This information is available under “Livestock” in the Prairie-Mountain States section.
NDVI (Normalized Difference Vegetation Index)
Note: There are several NDVI raster image files for each state. See “File Naming Convention” below.
State: All
Source: USGS, EROS Data Center
Projection/Coordinate System: Lambert Equal-Area Azimuthal
Projection Parameters:
Units of Measure meters
Radius of Sphere 6,370,997.0 meters
Longitude of Central Meridian 100 00 00 west
Latitude of Origin 45 00 00 north
False Easting 0
False Northing 0
Pixel Size 1,000 meters
File Naming Convention: ssndypxx.tif (image file) and ssndypxx.tfw (header file), where ss = state (ID, MT etc., or UM for all 5 UMAC states), nd = ndvi, y = year (6 for 1996, 7 for 1997, 8 for 1998), and pxx = time period
The time periods are as follows:
1996: Period 08 = April 12-25
Period 09 = April 26-May 9
...
Period 21 = October 11-24
1997: Period 16 = April 18-May 1
Period 18 = May 2-15
...
Period 40 = October 3-16
1998: Period 16 = April 17-30
Period 18 = May 1-14
...
Period 40 = October 2-15
The numbering scheme for the 1996 time period is different from that used for 1997 and 1998 because of different sources of data. The 1997 and 1998 data were downloaded from the UMAC website and the 1996 data were derived from EROS. The EROS data were loaded on the UMAC website and downloaded from there for processing. There are 14 dates for 1996 and only 13 for 1997/98.
Background Information on NDVI:
In May 1987, the U.S. Geological Survey's EROS Data Center (EDC) began real-time reception of Advanced Very High Resolution Radiometer (AVHRR) data from operational NOAA polar orbiting satellites. EDC receives AVHRR High Resolution Picture Transmission (HRPT) data for the entire conterminous United States, southern Canada, and northern Mexico. The AVHRR Data Acquisition and Processing System (ADAPS) includes a tracking antenna, a data receiving subsystem, and a minicomputer with associated peripherals for data processing.
Since the 1989 growing season, EDC has used the AVHRR (1 km resolution) daily observations to produce weekly and biweekly maximum Normalized Difference Vegetation Index (NDVI) composites of the conterminous United States.
What is the Advanced Very High Resolution Radiometer?
The Advanced Very High Resolution Radiometer (AVHRR) is an optical multispectral scanner flown aboard National Oceanic and Atmospheric Administration (NOAA) orbiting satellites. The instrument measures reflected sunlight and emitted radiation (heat) from Earth in the visible (Channel 1), near-infrared (Channel 2), and thermal infrared (Channels 3, 4, and 5) regions of the electromagnetic spectrum.
The image maps are produced from AVHRR data known as Local Area Coverage that are recorded onboard the satellite for subsequent transmission to a NOAA receiving station on Earth. These data have a resolution of 1 kilometer(km), which means that each image pixel represents a 1x1-km square on the ground. Before these data can be made into the image maps a considerable amount of image processing must be done. Digital processing includes radiometric calibration, atmospheric correction, computation of NDVI values, geometric registration to the Lambert Azimuthal Equal-Area map projection, and image map compositing. The results are the weekly 1-km AVHRR multispectral data sets and NDVI image maps of the conterminous United States. These steps are essential in the production and archiving of AVHRR data sets and images, and are particularly beneficial when these data are used for Geographic Information System (GIS) mapping and analysis.
What is NDVI?
The Normalized Difference Vegetation Index (NDVI) has been in use for many years to measure and monitor plant growth (vigor), vegetation cover, and biomass production from multispectral satellite data. The NDVI image maps shown here are prepared from 1-km AVHRR spectral data in the visible (Channel 1; 0.58-0.68 micrometers) and near infrared (Channel 2; 0.725-1.10 micrometers) regions of the electromagnetic spectrum. NDVI is calculated as follows:
NDVI = (Channel 2 - Channel 1) / (Channel 2 + Channel 1)
The principle behind NDVI is that Channel 1 is in the red-light region of the electromagnetic spectrum where chlorophyll causes considerable absorption of incoming sunlight, whereas Channel 2 is in the near infrared region of the spectrum where a plant's spongy mesophyll leaf structure creates considerable reflectance (Tucker 1979, Jackson et al.1983, Tucker et al. 1991). As a result, vigorously growing healthy vegetation has low red-light reflectance and high near-infrared reflectance, and hence, high NDVI values. This relatively simply algorithm produces output values in the range of -1.0 to 1.0. Increasing positive NDVI values, shown in increasing shades of green on the images, indicate increasing amounts of green vegetation. NDVI values near zero and decreasing negative values indicate non-vegetated features such as barren surfaces (rock and soil) and water, snow, ice, and clouds.
These images show a temporal representation of the growth of vegetation as it progresses week-to-week throughout the spring and summer months. Later in the year, these weekly images will also show the decline in vegetation growth (plant senescence) as fall and winter approach. It is this temporal characteristic that makes AVHRR data so valuable to studies of Prairie-Mountain States vegetation growth rates, vegetation cover, biomass production, and general rangeland health.
Annual Precipitation (Inches)
State: All
Source and General Description: This map was developed using the PRISM model, developed by Chris Daly of PRISM Services, Oregon State University. Data used for the mapping consisted of average values for the 1961-1990 period reported by NOAA Cooperative stations and USDA, NRCS, and SNOTEL sites. Care should be taken in estimating precipitation values at any single point on the map, since the data presented refer to average values over approximately a 3 by 4 km area.
Contact information: George H. Taylor, State Climatologist
Oregon Climate Service
541-737-5705
Attribute Description:
Shape- polygon - ArcView shape category
Range- range of average annual precipitation in inches
Edge- unknown code
Soil Properties
State: All
Source: National Resource Conservation Service, USDA. STATSGO database
General Description: Soil maps for the State Soil Geographic (STATSGO) Database are made by generalizing the detailed soil survey data. The mapping scale for the STATSGO map is 1:250,000. The level of mapping is designed for broad planning and management uses covering state, regional, and multi-state areas.
Discussion: Five mapping unit attributes were chosen for processing to characterize the soils in the UMAC states. These attributes are clay content, available water capacity, organic matter, drainage, and hydric soils. Because each STATSGO soil mapping unit is composed of several components and each component is composed of several layers, it was necessary to devise a methodology (or methodologies) to calculate a single value for each attribute and mapping unit. The Comp and Layer tables that accompany the STATSGO map files contain the data used for the calculations. The methodologies used to process the data are explained below.
Attribute Description:
Shape- polygon - ArcView internal category
MUID- unique identifier map unit
Claywa- clay content (units = % of material < 2mm in size)
Claylow- lowest value of clay content (units = % of material < 2mm in size)
Clayhigh- highest value of clay content (units = % of material < 2mm in size)
Awcwa- available water capacity (units = inches/inch)
Awclow- lowest value for available water capacity (units = inches/inch)
Awchigh- highest value for available water capacity (units = inches/inch)
Omwa- organic matter, weighted average of all units (units = % by weight)
Omtops- average organic matter on the surface
Drainage- code identifying the natural drainage condition of the soil
Drainpct- the percent of the soil component that represents the drainage soil rating given above
Hydric- hydric soil rating (Y or N)
Hydricpct- the percent of the soil component which represents the hydric soil rating given above.
Clay Content (units = % of material < 2mm in size)
♦ Weighted Average (attribute = claywa)
For each component:
1. Average the low and high values in each layer
2. Multiply by the layer thickness
3. Add the computed values for all of the layers
4. Divide by the total thickness
For each mapping unit:
5. Calculate the weighted average of the component values
Example: component 1, 30% of mapping unit – calculated value = 25.7
component 2, 50% of mapping unit – calculated value = 20.4
component 3, 20% of mapping unit – calculated value = 18.8
weighted average = (25.7 x .3) + (20.4 x .5) + (18.8 x .2) = 21.7
♦ Low and High Values (attributes = claylow and clayhigh)
Find the overall low and high values among all of the components and layers within components
Available Water Capacity (units = inches/inch)
♦ Weighted Average (attribute = awcwa)
For each component:
1. Average the low and high values in each layer
2. Multiply by the layer thickness
3. Add the computed values for all of the layers
4. Divide by the total thickness
For each mapping unit:
5. Calculate the weighted average of the component values
♦ Low and High Values (attributes = awclow and awchigh)
Find the overall low and high values among all of the components and layers within components
Organic Matter (units = percent by weight)
♦ Weighted Average (attribute = omwa)
For each component:
1. Average the low and high values in each layer
2. Multiply by the layer thickness
3. Add the computed values for all of the layers
4. Divide by the total thickness
For each mapping unit:
5. Calculate the weighted average of the component values
♦ Surface Layer Average (attribute = omtops)
7. Average the low and high values for the surface layer of each component
8. Calculate the weighted average of the component values
Drainage (code identifying the natural drainage condition of the soil)
♦ Most Frequently Occurring Code (attributes = drainage and drainpct)
Find the drainage code that occurs most frequently. Report both the code and its frequency of occurrence. Drainage codes exist only by component, not by layer.
Examples: component 1, 30% of mapping unit – W (well drained)
component 2, 45% of mapping unit – MW (moderately well drained)
component 3, 25% of mapping unit – W (well drained)
resulting values: W, 55%
component 1, 20% of mapping unit – SE (somewhat excessively)
component 2, 40% of mapping unit – E (excessively)
component 3, 20% of mapping unit – MW (moderately well)
component 4, 20% of mapping unit – SE (somewhat excessively)
resulting values: SE/E, 40%
Drainage codes: E = excessively drained
SE = somewhat excessively drained
W = well drained
MW = moderately well drained
SP = somewhat poorly drained
P = poorly drained
Code combinations, e.g.,W,MW = well to moderately well
NULL = no code listed
Hydric (hydric soil rating: Y or N)
♦ Most Frequently Occurring Code (attributes = hydric and hydricpct)
Find the hydric code that occurs most frequently. Report both the code and its frequency of occurrence. Hydric codes exist only by component, not by layer.
Examples: component 1, 30% of mapping unit – Y (yes)
component 2, 45% of mapping unit – N (no)
component 3, 25% of mapping unit – Y (yes)
resulting values: Y, 55%
component 1, 14% of mapping unit – Y (yes)
component 2, 29% of mapping unit – N (no)
component 3, 36% of mapping unit – Y (yes)
component 4, 21% of mapping unit – N (no)
resulting values: Y, 50% (Y/N = Y for all percentages GE 50%, N for LT 50%)
Species Data
State: Idaho
Source: Idaho Conservation Data Center, Idaho Fish and Game. For more information about these data, contact the Idaho Conservation Data Center at 208-334-3402.
General: The Idaho Point Observation Database (POD) is intended strictly for educational purposes only and it should not be interpreted as the final word on distribution of these species in Idaho. It is a limited data set that by no means represents the species in Idaho. It is provided for demonstration purposes only and no other purpose. Users should also recognize that many of the point observations are old and historic and therefore may provide inaccurate information.
Attribute Description:
Shape- point - ArcView shape category
Point_no- internal GIS record of the point
Source- code representing the data source
Scomname- species common name
Sname- species name
Elcode- element code (see description in Montana POD)
Year- year the sample was recorded
Month- month the sample was recorded
Day- day the sample was recorded
County- county where the species was found
Lat- latitude where the species was found
Long- longitude where the species was found
Townrange- township and range where the species was found
Section- section where the species was found
Location- descriptive location where the species was found
Elev- elevation where the species was found
Institute- agency collecting the information
Observer- name of the individual or agency recording the information
Comments- refers to the parts of the species found
Data_type- code for what was actually observed (see Montana POD description)
Adult_male- code for the number of males observed
Adult_female- code for the number of females observed
State: Montana
Source: Montana Natural Heritage Program
General Description: The Montana Point Observation Database (POD)
Attribute Description:
|BASIS (USER) |The concatenation of these three fields constitutes the |
|SUBSET |unique record key for each POD record. In addition, |
|POINT |the field 'basis' (or 'user') indicates how or by whom |
| |the point feature was generated. |
|GIS_PT |Indicates how the point feature was generated: |
| |d = digitized from a mylar map overlay |
| |g = generated from lat/long coordinates |
| |o = digitized on-screen using background layers |
| |other than the PLSS |
| |t = digitized on-screen using the PLSS |
| |u = generated from UTM coordinates |
|SOURCE |A code for records in the MTNHP bibliographic database, or |
| |for general source types |
| |byte 1 = source type (see below) |
| |bytes 2,3 = year of source (e.g., publish date) |
| |Note: 'ND'= no date |
| |bytes 4-6 = first three letters of author's (person's) last name |
| |bytes 7,8 = counter (tie-breaker) |
| |bytes 9-12 = state & country of source-record origin |
| |Source types are: |
| |A = published article |
| |B = published book |
| |D = digital database |
| |F = field survey form |
| |P = person |
| |S = museum specimen |
| |U = unpublished document (thesis, report, EIS, etc.) |
|ELCODE |A 10-byte alpha-numeric code for the species. ELCODEs are |
|(element code) |based on taxonomic ordering of species, and can change. |
| |The first byte gives the basic group: 'A' = vertebrate, 'I' |
| |= invertebrate, 'P' = vascular plant, 'N' = non-vascular |
| |plant, 'C' = plant community, 'O' = other non-species |
| |elements. Bytes 2-5 typically indicate the taxonomic |
| |class and/or family; bytes 6-7 the genus; bytes 8-9 the |
| |species; and byte 10 the subspecies or variety. |
| | |
|EONUM |A counter for 'element occurrences' of species tracked by |
| |the MTNHP. An element occurrence is the habitat necessary |
| |to support and sustain a population of the element. From |
| |one to many POD records may document a single element |
| |occurrence. |
|DATA_TYPE |A code for what was actually observed: |
| |SS Museum specimen |
| |S? Specimen reported |
| |PP Photograph |
| |P? Photo Reported |
| |O Observation |
| |HH Taped call |
| |H? Call heard only |
| |TT Track: cast or photograph |
| |T? Track observed |
| |DD Scat: collected or photograph |
| |D? Scat observed |
| |NN Nest/den: photograph or collected |
| |N? Nest/den observed |
| |M Other types of data |
|BREED |= B for breeding confirmed, = P for breeding probable |
| |= T for 'transient' |
|COLLECTOR |The name of the observer ('collector' for a specimen record) |
|UPDATE |Date the record was entered or last edited |
|SURVEY_ID |Record key for a record in the associated 'surveys' database, |
| |for observations made during a survey (as opposed to |
| |incidental observations) |
|MALES, etc |Numbers of individuals observed of that age/sex |
|EGG_OUT |Number of bird eggs in the nest, amphibian egg masses, ... |
|EGG_IN |For specimens, eggs present in oviduct, or fetus present |
State: Wyoming
Source: Wyoming GAP Database, Wyoming Water Resources Center
General Description:
The species distribution maps contain the predicted distributions of species.
How the species distribution maps were created: The vertebrate species distribution maps were predicted using a computer model, incorporating existing information on point locality records, range maps, and habitat conditions for each species. The modeling approach used includes four steps:
1. The distributional limits of each species were defined by recording the species' presence or absence within a grid of hexagon-shaped cells (635 km2 in size) encompassing the state, based on point locality records and range maps.
2. A Wildlife-Habitat Relationships (WHR) database was developed, recording the association of terrestrial vertebrate species to features that had been digitally mapped within the State of Wyoming, including land cover (vegetation) types, riparian/aquatic habitats, and elevation.
3. The hexagon and WHR databases were combined by the use of a GIS in a spatial overlay process. Species distributions in the state were predicted on existence of associated habitat within hexagon cells where species are known or expected to occur.
4. Hardcopy maps of predicted species distributions were reviewed by over 60 acknowledged experts including state and federal biologists, university professors, and Audubon Society members, resulting in the final version of the maps included in this atlas.
For more details on the procedures used to collect and process information in the creation of the predicted species distributions, please refer to:
Merrill, E. H., T. W. Kohley, M. E. Herdendorf, W.A. Reiners, K.L. Driese, R.W. Marrs, S.H. Anderson. 1996. Wyoming Gap Analysis: A Geographic Analysis of Biodiversity. Final Report, WY. Coop. Fish Wildl. Unit, Univ. WY., Laramie, WY.
Official Disclaimer for GAP data:
Although these data have been processed successfully on a computer system at the USGS Biological Resources Division, no warranty expressed or implied is made regarding the accuracy or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. This disclaimer applies both to individual use of the data and aggregate use with other data. The USGS Biological Resources Division shall not be held liable for improper or incorrect use of the data described and/or contained herein.
These data were compiled with regard to the following standards. Please be aware of the limitations of the data. These data are meant to be used at a scale of 1:100,000 or smaller (such as 1:250,000 or 1:500,000) for the purpose of assessing the conservation status of vertebrate species and vegetation cover types over large geographic regions. The data may or may not have been assessed for statistical accuracy. Data evaluation and improvement may be ongoing. The USGS Biological Resources Division makes no claim as to the data's suitability for other purposes.
Attribute Description:
Shape: polygon – ArcView shape category
Species: indicates which land cover type the species is associated with
1) predicted presence of the species based on the primary land cover type (i.e., land cover occupying the largest proportion of the area of each polygon) of the habitat polygon.
2) predicted presence of the species based on the secondary land cover (i.e., land cover occupying the second largest proportion of the area of each polygon).
Note: Species data clipped to the county extent exist for four species and can be found in the county folders. Not all counties have all of these species. These are:
Moose
Red-Tailed Hawk
Spotted Bat
Ring-Necked Duck
Codes to Wyoming Species data:
Ambison = American Bison
Baldeagl = Bald Eagle
Bferret = Black Footed Ferret
Canmouse = Canyon Mouse
Greyowl = Great Grey Owl
Greywolf = Grey Wolf
Mrattle = Midget Faded Rattlesnake
Mtngoat = Mountain Goat
Mtnplover = Mountain Plover
Nplizard = Northern Prairie Lizard
Pmouse = Prairie Mouse
Prebles = Prebles Meadow Jumping Mouse
Rduck = Ring-Necked Duck
Sbat = Spotted Bat
Woodfrog = Wood Frog
Wyotoad = Wyoming Toad
Additional Data Note: The Prebles Meadow Jumping Mouse data included on this CDROM is now known to not be a good predictor of this species habitat.
Streams/Rivers
State: All
Source: EPA Basins project, 1:500,000
General Description: Hydrographic database representing surface waters of the continental U.S.
Accuracy of Data: Source graphics are initially compiled to meet National Map Accuracy Standards, where 90% of well-defined features are to be within .02 inches of true mapped position. Positional error of less than or equal to .0003 inches or .076 mm RMSE relative to the source it was digitized from.
Glossary: Reach- a section of a stream with similar characteristics
CFS- cubic ft per second
Order- a hierarchy to stream classification…sections of river are classified by order, depending on similar characteristics
Mean- average
Attribute Description:
Shape- polyline- ArcView internal field
SEGL- length of the reach in miles
LEV- reach level order
PMILE- path mile
PNAME- primary reach name
OWNAME- open water name
MNFLOW- mean flow in the reach in CFS
MNVELO- stream velocity in the reach at mean flow
MDLAT- midpoint (of the reach) latitude
MDLONG- midpoint (of the reach) longitude
PLOWFL- stream-only low flow
PMEANFL- stream-only mean flow
PTOPELE- top of reach elevation
PBOTELE- bottom of reach elevation
PSLOPE- slope: not derived from elevation
PDEPTH- mean depth (ft) of the reach
PWIDTH- mean width (ft) of the reach
PTEMP- mean temperature of the water in the reach
PPH- mean pH (acidity)
PLOWVEL- total low-flow velocity
PK1- CBOD decay rate constant (if known)
PK3- NH3 decay rate constant (if known)
PSOD- sediment oxygen demand
PBGDO- background Dissolved Oxygen (DO). This is the amount of oxygen available in the water for animal and plant life. Pollution tends to lower amounts of dissolved oxygen in the water. 9.2 mg/liter is the saturation amount of dissolved oxygen in the water.
PBGNH3- background Ammonia (NH3). This the amount of ammonia in the water and is broken down by oxygen in the water. The more ammonia in the water, the less oxygen available for animal and plant life.
PBGBOD5- background Carbonaceous Biochemical Oxygen Demand (CBOD). The amount of oxygen that is required to break down carbon based chemicals into carbon dioxide. This reduces dissolved oxygen in the water available for animal and plant life.
PBGNBOD- background Nitrogenous Biochemical Oxygen Demand (NBOD). This is the same as CBOD except that it is the amount of oxygen required to break down the nitrogen based chemicals. This reduces dissolved oxygen in the water available for animal and plant life.
Watersheds
This information is available under Watersheds in the Prairie-Mountain States section.
5.3 County Data for Idaho, Montana, North Dakota, South Dakota and Wyoming
Local Data in “County” folders
|Shapefile Name |Data Description |
|Boundary.shp |1:100,000 scale county boundaries |
|Contour.shp |Elevation contours (200 ft) |
|Geology.shp |Geology data (available for ND,ID,WY) |
|Landcov.shp |1:100,000 scale land cover data |
|Landown.shp |Land ownership data |
|Roads.shp |1:100,000 scale transportation files |
County Boundary
State: All
Source: US Census Bureau TIGER Line Files, 1:100,000
General Description: These data show county boundaries.
Attribute Description:
Shape- polyline – ArcView shape category
Name- county name
Elevation Contours
State: All
Source: USGS Digital Elevation Model, 1:250,000.
General Description: Contours are isolines representing equal lines of elevation. County elevation contours are every 200 ft for MT, ID, WY & every 100 ft for ND and SD. Data was created by converting USGS digital elevation models into contour maps using ARC/INFO interpolation commands.
Attribute Description:
Shape- polyline - ArcView shape category
Contour- isoline elevation above sea level. Contours are every 200 ft for Montana, Idaho, Wyoming. Contours are every 100 ft for North and South Dakota.
Geology
State: Idaho
Source: Digital Representation of the Idaho State Geologic Map: A Contribution to the Interior Columbia River Basin Ecosystem Management Project, by Bruce R. Johnson and Gary L. Raines, 1:500,000.
General Description and Background: The starting point for the digital geology map of Idaho was a paper copy of the published geologic map (Bond and Wood, 1978). The map was processed using ARC/INFO and is considered an accurate geographic representation of the original map.
Attribute Description:
Shape- polygon – ArcView shape category
Formation- the map unit symbol used on the published map. This is the item that is related to the map coverage. This is not necessarily a formation in the normal usage. It is a map unit.
Unit_name- the map unit name from the map explanation.
Rock_type- the general rock category from the map explanation. Generally this is something like sedimentary, igneous, or metamorphic.
Era- the era age of the rock, based on the geologic time scale
System- the period age of the rock, based on the geologic time scale
Series- the epoch age of the rock, based on the geologic time scale
Lith1- first lithology from the map explanation
Lith2- second lithology from the map explanation
Lith3- third lithology from the map explanation
Litha- Lithology from the map explanation
Lith_form- Lithology from the map explanation
State: Montana
These data are the same as those used for the Prairie-Mountain States scale data. This information is available under Geology data in the Prairie-Mountain States section.
State: South Dakota
Source: SD Geological Survey, 1:2,534,400
General Description: Geology of South Dakota
Attribute Description:
Shape- polygon - ArcView shape category
Descriptio- name of geologic rock type
State: North Dakota
Source: ND Geological Survey, 1:500,000
General Description: Geology of North Dakota. Note: some of the geologic polygons may lack information. In these cases, the polygons are simply shaded transparent (no color).
Attribute Description:
Shape- polygon - ArcView shape category
Period- date of rock/sediment based on geologic type scale
Abbrev- abbreviation of geologic type
Thickness- thickness of geologic layer
Sediment_1- primary sediment layer
Sediment_2- secondary sediment layer
Epoch- the geologic epoch when the rock originated
Other_epoc- secondary geologic epoch when the rock originated
Main_genes- depositional environment of rock
Minor_gene- minor/secondary depositional environment of rock
Max_slope- maximum percent slope
Formation- name of formation
Sediment_3- third sediment layer
Sediment_4- fourth sediment layer
Acres- area in acres of polygon
State: Wyoming
Source: Wyoming Spatial Data Visualization Center Clearinghouse (sdvc.uwyo.edu)
General Description: Bedrock Geology of Wyoming. The geologic map was digitized from original scribe sheets used to prepare the published Geologic Map of Wyoming (Love and Christiansen, 1985), consequently at a 1:500,000 scale. The data set has both polygon and line features (faults), with attributes derived from the 1985 map.
Attribute Description:
Shape- polygon - ArcView internal field
Name- geologic code name of feature
Detail- detailed geologic name of feature
Acres- number of acres
Land Cover
State: Idaho
Source: GAP Analysis of Biodiversity in Idaho, National Biological Service. Primary Contact Person: Troy Merrill, Landscape Dynamics Lab, 208-885-5788.
General Description: This is a coverage of the actual vegetation types of Idaho, compliant with Steve Caicco. It includes three levels of vegetation classification from coarse to fine. Scale: 1:500,000. Source date: 1989.
Attribute Description:
Shape- polygon – ArcView shape category
Area- area of land cover polygons in sq. meters.
Perimeter- perimeter of land cover polygons in meters.
Veg1name- names of veg1 classification – the finest level of classification.
Veg2name- names of veg2 classification
Veg4name- names of veg4 classification – the coarsest level of classification.
Acres- number of acres of land in the vegetation polygon
State: North Dakota, South Dakota, Montana
Source: USGS Land Use Land Cover Data, 1:250,000; land use types from 1976 remotely sensed data.
General Description: The Land Use and Land Cover (LULC) data files describe the vegetation, water, natural surface, and cultural features on the land surface. The United States Geological Survey (USGS) provides these data sets and associated maps as a part of its National Mapping Program. The LULC mapping program is designed so that standard topographic maps of a scale of 1:250,000 can be used for compilation and organization of the land use and land cover data. Note: some data are missing for Montana, North Dakota and South Dakota. These areas are denoted by lucode = 0.
Further Description of the Land Use and Land Cover Data: Land Use and Land Cover maps provide data to be used either by themselves or in combination with the other data sets produced in the program. The basic sources of land use compilation data are NASA High-Altitude aerial photographs, and National High-Altitude Photography (NHAP) program photographs, usually at scales smaller than l:60,000. The l:250,000-scale topographic map series is generally used as the base map for the compilation of the Land Use and Land Cover maps and the associated overlays. 1:100,000-scale topographic map bases have been used on rare occasions. Although compilation of Land Use and Land Cover data is performed on a film-positive base usually enlarged to a scale of approximately l:l25,000, the associated overlays are both compiled and digitized at a scale of l:250,000.
All features are delineated by curved or straight lines, which depict the actual boundaries of the areas (polygons) being described. The minimum size of polygons depicting all Urban or Built-up Land (categories 11-17), Water (51-54), Confined Feeding Operations (23), Other Agricultural Land (24), Strip Mines, Quarries, and Gravel Pits (75) and Urban Transitional areas (76), is 4 hectares (ha). All other categories of Land Use and Land Cover have a minimum polygon size of 16 ha. (Those sizes also are considered the minimum sizes to which polygons are digitized.) In the Urban or Built-up Land and Water categories, the minimum width of a feature to be shown is 200 m; (that is, if a square with sides 200 m in length is delineated, the area will be 4 ha). Although the minimum-width consideration precludes the delineation of very narrow and very long 4 ha polygons, triangles or other polygons are acceptable if the base of the triangle or minimum width of the polygon is 200 m in length and if the area of the polygon is 4 ha. Exceptions to this specification are limited access highways (14) and all double line rivers (51) on the 1:250,000-scale base which have a minimum width of 92 m. For categories other than Urban or Built-up Land and Water, the 16 ha minimum size for delineation requires a minimum-width polygon of 400 m.
Attribute Description:
Shape- polygon – ArcView shape category
Area- area of land cover polygon in sq. meters
Perimeter- perimeter of the polygon, in decimal degrees
Lucode- land cover code
Level2- land cover polygon name
Known Bugs in Land Cover:
Montana counties
Hill county - landcov.shp missing an east central section
Lincoln county - landown.shp missing a section down middle
Powder River - landcov.shp missing strip in SE
Roosevelt - landcov.shp west has no polygons within it
Stillwater - landcov.shp missing part in NE
Yellowstone - landcov.shp missing section in NW
North Dakota counties
Benson - geology.shp missing SE section
Bowman - landcov.shp missing SW section
Grant - landcov.shp missing SE section
Kidder - landcov.shp missing sections in NE and NW
Morton - landcov.shp missing SE section
Stutsman - landcov.shp missing NE section
Wells - landcov.shp missing SW section
South Dakota counties
Hand - landcov.shp missing NW corner
Harding - landcov.shp missing western section
Hughes - landcov.shp missing eastern section
State: Wyoming
Source: Wyoming GAP Analysis, 1:100,000
General Description: Vegetation patterns are an integrated reflection of the physical, chemical, and biotic factors that shape the environment of a given land area (Whittaker 1965). As such, gap analysis relies on maps of dominant land cover types as the most fundamental spatial component for the analysis of terrestrial environments (Scott et al. 1993). The mapped extent and distribution of existing land cover is used in gap analysis to evaluate the management status of natural land cover types in Wyoming, to provide a spatial database for modeling wildlife habitat and vertebrate distributions across Wyoming, and to establish a single temporal data set of current land cover patterns in Wyoming for future reference (Stoms 1994). Because gap analysis was conceived to provide conservation assessment of large areas, Landsat Thematic Mapper (TM) data were chosen as the basis for mapping land cover. TM data provide sufficient spectral and spatial resolution for land cover discrimination and are available for the entire United States, providing a consistent base for the National GAP (Scott and Jennings 1994).
Attribute Description:
Shape- polygon- ArcView shape category
Primary- land cover type code occupying the largest area within the polygon
Cover Name- name of the land cover type within that polygon
Acres- total number of acres within the land cover polygon
Land Ownership
State: Idaho
Source: GAP Analysis of Biodiversity in Idaho, National Biological Service, Landscape Dynamics Lab, Moscow, Idaho. The digital maps were compiled from USGS-BLM Surface Land Management Status maps. 1:100,000.
General Description: This theme shows ownership of Idaho lands (1990).
Attribute Description:
Shape- polygon- ArcView shape category
Name- name of the land owners
Acres- total acreage of the polygon
State: Montana
Source: Montana Public Lands from 1:100,000 scale BLM quadrangles
General Description: Montana land ownership by federal and state agencies of parcels of at least 40 acres. Purpose: for display of land ownership data.
Attribute Description:
Shape- polygon- ArcView shape category
Area- area of the polygon in decimal degrees
Perimeter- perimeter of the polygon in decimal degrees
Descriptio- name of the land owner
Acres- total acreage of the polygon in acres
State: North Dakota, South Dakota
Source: Managed Area Database, University of Santa Barbara, 1:2,000,000
General Description: Generalized land ownership of North and South Dakota
Attribute Description:
Shape- polygon - ArcView shape category
Area- area of the polygon in decimal degrees
Perimeter- perimeter of the polygon in decimal degrees
Owner_nd_ - internal ArcView code
Owner_nd_i – internal ArcView code
Areaname- federal land name
Descriptio- name of the land owner
Acres – total of polygon in acres
State: Wyoming
Source: Wyoming GAP Analysis, 1:100,000
General Description: Information on Wyoming's land ownership was derived from two sources: (1) digital land ownership files provided by the BLM State Office in Wyoming, and (2) BLM surface management status maps. The BLM State Office provided the WY-GAP with digital copies of land ownership for approximately 35% of Wyoming. This data was digitized by BLM personnel from 1:24,000 scale mylar overlays drafted from master titles, survey plats, and supplemental index plats.
The remaining 65% of the land ownership layer was digitized by WY-GAP using 1:100,000-scale Surface Management Status maps produced by the BLM. Mylar copies of the Surface Management Status maps were not accessible to us at the beginning of the project, so paper maps were used for digitizing. Despite efforts to digitize land ownership information from the most recently edited paper maps, maps ranged from recent versions edited in 1992, in excellent condition, to others edited in 1972, which had been folded. Land ownership polygons digitized by WY-GAP were then edge-matched with the ownership polygons digitized by BLM. In most cases, there was a close match along the edges, requiring only minor shifts in lines. Larger discrepancies (usually the result of differences in scale of the data sources) were closed off without an attempt to force a match. The Surface Management Status Maps from which the ownership was digitized have an accuracy of plus or minus 120 ft according to USGS standards, and each 1:100,000-scale quadrangle was digitized with a maximum root mean square (RMS) error tolerance of 0.006 digitizing inches (15.24 meters). Because some of the ownership was digitized from folded maps, the accuracy is probably closer to plus or minus 300 ft.
Selected water features from USGS 1:100,000-scale digital line graphs (DLGs) were included in the digital land ownership layer. Lakes and reservoirs of 5 ha and major rivers were selected from the DLGs and edgematched to existing land ownership polygons. These water polygons do not reflect surface or subsurface ownership in this layer, and are not coded with any ownership designation. The digital files provided by the BLM also included some water features that were retained and supplemented with water features from the DLGs.
To update the digitized land ownership through 1994, maps and legal descriptions of recent land acquisitions or releases of 640 acres were requested from federal and state agencies and, in most cases, incorporated into the database. Some purchases/exchanges could not be included because the complete legal description (subdivision descriptions by meters and bounds) could not be interpreted accurately to 1:100,000 maps by township, range and section.
Attribute Description:
Shape- polygon - ArcView shape category
Display- code for land owner type
Owner Name- name of the owners of the land
Type- type of ownership of the land
National Forest- name of the national forest within that polygon
Acres- acreage of the land ownership polygons
Park Name- name of the park
Park Type- type of park
Total Acres- total acreage of the national forest or national park identified
Shaded Relief
State: All
Source: U.S. Digital Topography for GIS. Chalk Butte, Inc. Boulder, WY
General Description: This shows the relief in elevation using a shaded technique. Map units are in decimal degrees and the projection is geographic. These images are projected into Lambert Equal-Area Azimuthal (-100.00, 45.00), for conformity with UMAC standards.
Transportation
State: All
Source: US Census Bureau TIGER Line Files, 1:100,000
General Description: These data show transportation features including: roads, pipelines, and railroads.
Attribute Description:
Shape- polyline – ArcView shape category
Name- name of the transportation feature
Type- for street names only, designates Ave., Rd., Ct., etc…
Category- type of transportation feature e.g., primary road, secondary road, pipeline, railroad, power line
Appendix A: Contact Information
For further technical assistance in using these data or loading the ArcView projects feel free to contact us. Our website has the latest information on downloads, known bugs, and technical assistance contacts.
Contacts:
Patricia McClurg, Director
EdPARC
PO Box 3992
Laramie, WY 82071
patmc@uwyo.edu
Appendix B: Data Distribution and Use Statement
These GIS data sets are intended for educational purposes only. If you would like to use the data in any manner other than for educational purposes, we strongly recommend that you obtain the data directly from their original sources complete with full metadata documentation. These data may not be sold or used for any commercial purposes, in accordance with the agreements that we have made with the original distributors of the data.
Although these data have been processed successfully on a computer system, no warranty expressed or implied is made regarding the accuracy or utility of the data on any other system or for general or scientific purposes, nor shall the act of distribution constitute any such warranty. This disclaimer applies both to individual use of the data and aggregate use with other data. We shall not be held liable for improper or incorrect use of the data described and/or contained herein.
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