Metadata for Central and Southwest Montana Land Cover Classification, 1994-2001 Metadata for Central and Southwest Montana Land Cover Classification, 1994-2001

Download full XML Metadata

Identification Information:

Citation:

Originator: Wildlife Spatial Analysis Lab, The University of Montana
Publication date: 06/30/2001
Title:: Central and Southwest Montana Land Cover Classification, 1994-2001

Browse graphic file name: http://docs.msl.mt.gov/geoinfo/Images/Metadata/silc3regionz.gif

Abstract:

SILC3REGIONZ is an ArcInfo 30 meter region grouped grid (raster file) of ground feature polygons derived from nine Landsat Thematic Mapper (TM) images across west-central Montana. Each of the nine Landsat TM images were processed separately and were then edgematched together to form one GIS region database.

First, each Landsat image was delineated into regions in an unsupervised classification. Second, each region was assigned a land cover type label in a supervised classification. Regions classified as conifer cover types were also assigned labels for tree size class and canopy cover. A total of 31 land cover type classes, 5 tree size classes, and 5 conifer canopy cover classes were labeled across the nine scene area. Accuracies were estimated for the land cover type and tree size classifications of each Landsat image. Third, the regions from all nine Landsat images were edgematched together into the SILC3REGIONZ database. Below is a description of how the original Landsat images were delineated into ground feature regions, how the regions were labeled to land cover type, tree size, and tree canopy, and how the nine Landsat images were edgematched into one database.

Image Landsat Image-Date Covertype-Acc Treesize-Acc SCENEPOLY-ID
--------------------------------------------------------------------------
P40R27 7 7/27/99 69.8% 64.0% 49000001 ..
P40R28 5 7/26/96 69.0% 57.1% 50000001 ..
P39R27 5 7/01/95 73.5% 61.8% 51000001 ..
P39R28 5 6/28/94 74.7% 69.6% 52000001 ..
P39R29 5 6/28/94 75.7% 54.7% 53000001 ..
P38R27 5 7/12/96 75.9% 55.9% 54000001 ..
P38R28 5 7/12/96 74.6% 64.5% 55000001 ..
P38R29 5 7/12/96 66.0% 57.9% 56000001 ..
P37R29 5 7/24/00 64.9% 66.9% 57000001 ..

Each image was run through an unsupervised classification to classify the approximately 56 million pixels into 130-150 spectral classes. A potential natural vegetation (PVT) classification provided by Region One of the USDA Forest Service was included as a seed source in the unsupervised classification. Using an iterative classification process with spectral signature files and PVT seed, each pixel was assigned to a spectral class. The pixels were then merged into regions (raster polygons) through a multi-stage merge algorithm using a variable minimum map unit based on heterogeneity of the surrounding pixels. Regions larger than 202.4 hectares were divided until all regions in the grid were less than 202.4 hectares (500 acres). The final unsupervised classification resulted in the creation of regions ranging in size from 0.1 hectare to 202.2 hectares. Each region was assigned a set of attributes for TM channels 1-7 and panchromatic from the imagery, along with elevation, aspect, and slope from the 30 meter digital elevation model (DEM); these attribute values were calculated based on the mean values of the 30 meter pixels within each region.

Vegetation overstory (land cover type) was labeled using a supervised classification. The land cover type supervised classification was performed using a combination of manual and training data classifications. The following classes were manually labeled: urban, irrigated and non-irrigated agriculture, recently burned areas, water, mines, snow, and clouds. The other land cover types were labeled using training data and spatial classifiers. The training data were screened for data attribute accuracy, positional accuracy, and agreement with the imagery. The land cover type labels were filled into the COVERTYPE field of each scenes region grid.

COVERTYPE DESCRIPTION
------------------------------------------------
1100 Urban or Developed Lands
2010 Agricultural - Dry
2020 Agricultural - Irrigated
3130 Very Low Cover Grasslands
3150 Low / Moderate Cover Grasslands
3170 Moderate / High Cover Grasslands
3610 Mesic Shrublands
3625 Sagebrush / Xeric Shrublands
4101 Aspen
4150 Mixed Broadleaf / Cottonwood Forest
4203 Lodgepole Pine
4204 Whitebark Pine
4205 Limber Pine
4206 Ponderosa Pine
4212 Douglas-fir
4214 Rocky Moutain Juniper
4215 Western Larch
4216 Utah Juniper
4223 Douglas-fir/Lodgepole Pine
4230 Douglas-fir/Ponderosa Pine
4237 Subalpine Fir/Spruce
4241 Mixed Upper Subalpine Conifer Forest
4242 Mixed Lower Subalpine Conifer Forest
4244 Mixed Xeric Conifer Forest
4400 Burns
5000 Water
7300 Rock
7500 Mines/Quarries
9100 Snow
9800 Cloud
9900 Cloud Shadow

Conifer tree size and canopy cover labels were assigned using a training data classification. The training data were screened for data attribute accuracy, positional accuracy, and agreement with the imagery. Due to a high level of disagreement between the training data tree canopy call (see accuracy assessment), and the imagery, the tree canopy data was recoded based on MNDVI splits. The tree size labels were filled into the TREESIZE field and the tree canopy cover labels were filled into the TREECANOPY field of each scenes region grid.

TREESIZE DESCRIPTION
-------------------------------------
1 Sapling 1.0-4.9" DBH
2 Pole 5.0-8.9" DBH
3 Medium 9.0-14.9" DBH
4 Large 15.0-20.9" DBH
5 Very Large 21.0-99.0" DBH

TREECANOPY DESCRIPTION
-------------------------------------
1 1-9% Cover
2 10-24% Cover
3 25-44% Cover
4 45-64% Cover
5 65-100% Cover

A cross validation (leave-one-out), accuracy assessment for land cover type and tree size of each scene was performed using the entire training data set. No estimate of accuracy was performed on the manually classified land cover types.

Edgematching was done by selecting regions from only one of the scenes in overlap areas. First, the imagery was visually analyzed to select cloud free or snow free areas in overlap zones. Next, the images were ranked based on overall image quality. Finally, after the land cover type classification, regions were selected that created a consistant covertype pattern across the transition zone from one scene to another. The end result was a region grid with 4,820,703 regions.

Image Landsat Date Priority Number of Regions Used
-------------------------------------------------------------
P40R27 7 07/27/99 1 754,813
P40R28 5 07/26/96 2 580,429
P39R27 5 07/01/95 3 290,811
P39R28 5 06/28/94 4 315,795
P39R29 5 06/28/94 5 472,441
P37R29 7 07/24/00 6 684,885
P38R27 5 07/12/96 7 683,615
P38R28 5 07/12/96 8 628,551
P38R29 5 07/12/96 9 409,363
-------------------------------------------------------------
Total Regions in Database 4,820,703

To help track similarities and differences in map legends between this classification and previous ones (SILC1 and MT-GAP) cover type names and codes numbers were not changed if the actual types were mapped using similar training data. Please see the individual scene report documents for further details.

Purpose:

This land cover classification from the nine Landsat TM scenes was prepared for the Eastside Assessment Area under contract to the USDA Forest Service. These data were produced to delineate ground features and map existing land cover in a standardized, consistent manner across the project area. This land cover grid is suited for analysis at the regional, sub-regional, and landscape levels; it can also provide support for many management disciplines, including timber, wildlife, fisheries, and recreation.

Time period of content:

Beginning date: 06/28/1994
Ending date: 07/24/2001
Currentness reference: ground condition

Access constraints:

This data set is in the public domain, and the recipient may not assert any proprietary rights thereto nor represent it to anyone as other than a data set produced by the USDA Forest Service and the Wildlife Spatial Analysis Lab at the University of Montana.

Use constraints:

The Montana State Library Geographic Information Services provides this product/service for informational purposes only. The Library did not produce it for, nor is it suitable for legal, engineering, or surveying purposes. Consumers of this information should review or consult the primary data and information sources to ascertain the viability of the information for their purposes. The Library provides these data in good faith but does not represent or warrant its accuracy, adequacy, or completeness. In no event shall the Library be liable for any incorrect results or analysis; any direct, indirect, special, or consequential damages to any party; or any lost profits arising out of or in connection with the use or the inability to use the data or the services provided. The Library makes these data and services available as a convenience to the public, and for no other purpose. The Library reserves the right to change or revise published data and/or services at any time.

This data set is provided "as-is" without warranty of any kind, including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose. The user assumes all responsibility for the accuracy and suitability of this data set for a specific application. In no event will the creators, the University of Montana, or the USDA Forest Service, be liable for any damages, including lost profits, lost savings, or other incidental or consequential damages arising from the use of or inability to use this data set. Use of these data requires the ability to read ArcInfo Grid data sets. Users must assume responsibility for determining the suitability of these data for their purposes. Not for use at scales greater than 1:100000.

Point of contact:

Roland L. Redmond
Principal Investigator
Wildlife Spatial Analysis Lab, The University of Montana
Wildlife Spatial Analysis Lab, The University of Montana
Missoula, MT 59812-1063
Telephone: 406 243 5208 (email preferred)
Fax: 406 243 6064
E-Mail: red@wru.umt.edu

Data set credit:

The Wildlife Spatial Analysis Lab for creation of the geospatial data set.

Data Quality Information:

Attribute accuracy report:

Thematic accuracy of the land cover type and conifer tree size cover labels were assessed using a leave-one-out cross-validation. The cross-validation involved removing the first training observation from the training set and constructing a new classification rule from the reduced training set. This new rule was then used to classify the polygon containing the left-out training observation. The process was repeated until all observations were held out once and used as a singleton test set. The estimated accuracy rate was the percentage of (held-out) observations correctly classified. The manually classified land cover types did not have an accuracy assessment performed. The Mixed Conifer Forest types were classified as one group (4240 Mixed Conifer), and were then recoded into 3 types; 4241 Mixed Upper Subalpine Conifer Forest, 4242 Mixed Lower Subalpine Conifer Forest, 4244 Mixed Xeric Conifer Forest. The accuracy of 4240 Mixed Conifer type was used to report accuracies for the 3 recoded Mixed Conifer types.

Users accuracies of land cover types were:
COVERTYPE P40R27 P39R27 P38R27 P40R28 P39R28 P38R28 P39R29 P38R29 P37R29
------------------------------------------------------------------------
3130 80.4 71.4 71.0 62.9 90.4 66.7 77.2 59.0 74.4
3150 81.2 82.6 93.6 77.3 84.1 87.6 90.4 81.0 80.3
3170 65.4 68.3 49.1 79.3 82.1 76.9 92.4 71.0 79.0
3610 69.9 42.7 66.8 62.3 61.2 68.3 72.4 67.3 69.8
3625 54.4 86.0 80.7 75.5 57.4 69.3 80.7 74.8 50.5
4101 68.3 75.9 46.3 68.9 68.2 68.5 71.9 76.0 57.9
4150 88.1 81.3 91.2 78.3 80.5 90.6 98.6 45.1 67.0
4203 67.6 80.6 67.7 70.3 65.9 70.1 67.6 72.5 46.8
4204 54.5 43.8 61.8 74.0 90.5 59.6 75.0 52.2 60.8
4205 88.9 46.7 66.7 NA 78.3 55.9 NA 85.7 63.6
4206 58.0 43.2 93.0 59.6 52.0 74.4 NA 75.0 51.5
4212 77.9 75.6 69.7 71.7 83.9 79.3 79.3 63.4 70.8
4214 NA NA NA NA 62.9 NA NA NA NA
4215 48.0 NA NA NA NA NA NA NA NA
4216 NA NA NA NA NA NA NA NA 45.2
4223 48.0 74.8 43.4 48.8 67.3 44.7 44.4 48.4 36.1
4230 57.1 41.3 34.6 50.5 68.1 41.2 NA NA NA
4237 57.1 26.7 37.4 49.3 65.0 50.4 41.7 57.6 48.9
4240 49.8 34.7 30.0 47.8 68.2 49.3 30.8 57.6 44.3
7300 94.6 92.6 95.3 99.1 96.0 99.4 99.4 97.8 92.9
------------------------------------------------------------------------
Overall 69.8 73.5 75.9 69.0 74.7 74.6 75.7 66.0 64.9

Users accuracies of conifer tree size classes were:
TREESIZE P40R27 P39R27 P38R27 P40R28 P39R28 P38R28 P39R29 P38R29 P37R29
------------------------------------------------------------------------
1 Sapling 64.7 61.4 55.5 46.3 17.9 57.0 47.1 57.9 58.0
2 Pole 50.4 60.2 58.4 60.6 82.3 65.2 54.2 59.8 68.4
3 Medium 59.4 64.6 51.3 65.1 79.1 67.5 60.1 60.3 67.7
4 Large 70.2 40.7 72.7 51.1 25.7 42.1 23.5 41.9 0.0
5 VLarge 46.5 13.3 10.0 13.8 12.1 18.2 28.6 12.5 NA
------------------------------------------------------------------------
Overall 64.0 61.8 55.9 57.1 69.6 64.5 54.7 57.9 66.9

Logical consistency report:

All grid attributes were checked for consistency of appropriate range values.

Completeness report:

All areas within the SILC3REGOINZ TM scene boundary have attributed regions.

Horizontal Positional Accuracy Report:

Claimed root-mean square error for horizontal position of the terrain-corrected Landsat TM images is 18 meters in the x direction (WNW-ESE) and 30 meters in the y direction (NNE-SSW).

Vertical positional accuracy report:

Each region has a mean elevation in meters determined from Digital Elevation Models whose Root Mean Square accuracy varies from 7 meters to approximately 30 meters.

Lineage:

Source information:

Originator: Multi-Resolution Land Cover Consortium (MRLC)
Publication date: 1994, 1996
Title:: Terrain-corrected Landsat 5 Thematic Mapper Images P38/R27, P38/R28, P38/R29, P39/R27, P39/R28, P39/R29, P40/R28
Source scale denominator: 60000
Source contribution:: Provided base imagery for classification of Eastside Assessment Area.
Calendar date: 08/29/1994
Calendar date: 07/21/1996

Source information:

Originator: USGS EROS Data Center
Publication date: 1999, 2000
Title:: Terrain-corrected Landsat 7 Thematic Mapper Images P37/R29 and P40/R27
Source scale denominator: 60000
Source contribution:: Provided base imagery for classification of Eastside Assessment Area.
Calendar date: 07/27/1999
Calendar date: 07/24/2000

Source information:

Originator: USDA Forest Service, Region 1
Publication date: 04/1995
Title: Potential natural vegetation (PVT) classification
Source scale denominator: 100000
Source contribution:: Provided PVT seed for unsupervised classification of image pixels.
Calendar date: 08/1998
Calendar date: 04/1999

Source information:

Originator: USDA Forest Service, Region 1
Publication date: 04/1995
Title: Existing Ground-Truth Databases and TSMRS Databases
Source scale denominator: 24000
Source contribution:: Provided training data and TSMRS data for assigning cover type labels.
Calendar date: 04/1995
Calendar date: 10/1995
Calendar date: 12/1999

Source information:

Originator: USDA Forest Service, Region 4
Publication date: 04/1995
Title: Existing Ground-Truth Databases
Source scale denominator: 24000
Source contribution: Provided training data for assigning cover type labels.
Calendar date: 09/1996
Calendar date: 05/1997

Source information:

Originator: U.S. Bureau of Land Management
Publication date: 04/1997
Title: Existing Ground-Truth Databases
Source scale denominator: 60000
Source contribution: Provided training data for assigning cover type labels.
Calendar date: 04/1997

Source information:

Originator: Natural Resource Conservation Service
Publication date: 06/1997
Title: Existing Ground-Truth Soil Survey Databases
Source scale denominator: 24000
Source contribution:: Provided training data for assigning cover type labels. To protect private landowners, NRCS overlaid WSAL polygons with their points and identified polygons containing ground truth plots; source scale is 1:24,000 or finer.
Calendar date: 06/1997

Source information:

Originator: U.S. Bureau of Indian Affairs
Publication date: 06/1997
Title: Existing Ground-Truth Databases
Source scale denominator: 24000
Source contribution: Provided training data for assigning cover type labels.
Calendar date: 06/1997

Source information:

Originator: U.S. Geological Survey
Publication date: 03/1996
Title: 1:100,000-scale Digital Line Graphs
Source scale denominator: 100000
Source contribution: Provided hydrography layer.
Calendar date: 03/1996
Calendar date: 04/1997

Source information:

Originator: U.S. Geological Survey
Publication date: 07/1995
Title: 7.5-minute Digital Elevation Models
Source scale denominator: 24000
Source contribution: Provided majority of topography layer.
Calendar date: 07/1995
Calendar date: 09/1996

Source information:

Originator: Defense Mapping Agency
Publication date: 07/1995
Title: 1-degree Digital Elevation Models
Source scale denominator: 250000
Source contribution:: Provided topography layer where 7.5-minute DEM data were unavailable.
Calendar date: 07/1995
Calendar date: 09/1996

Process step:

CLASSIFY: unsupervised classification of input image pixels into 130-150 spectral classes using PVT seed and nearest member group algorithm. Using an iterative stage classification with PVT seed and spectral class signatures, each pixel was assigned to a spectral class.


Process date: 06/01/1999

Process step:

MERGE: using customized software, merged all classified pixels using a variable minimum map unit into regions ranging from 0.1 ha to 500.0 ha. Variable minimum map unit was based on a moving window algorithm comparing surrounding pixel heterogeneity; pixels under the minimum map unit were merged with the most similar neighbors. Regions larger than 202.4 ha were manually split until all regions were less than 202.4 ha (500 acres).

MAKE_DEM: extracted a digital elevation model (DEM) from the WSAL database for use during labeling.
MAKE_HYDROGRAPHY: extracted a hydrography coverage from the WSAL hydrography database for use during labeling.
BUILD_VAT: built an ArcInfo value attribute table (VAT) to hold all items (fields) for which descriptive data could be developed for each region. Filled in VALUE, COUNT, LINK, HECTARES, PERIMETER, TM1, TM2, TM3, TM4, TM5, TM6, TM7, PAN, TM1STD, TM2STD, TM3STD, TM4STD, TM5STD, TM6STD, TM7STD, PANSTD, MNDVI, ELE, SLP, ASP, and SLPASP fields.


Process date: 08/01/1999

Process step:

LABEL_MANUALLY: manually labeled urban, agriculture, water, recent burns, mines, snow, mountain shadow, and clouds. Filled in the MANLABEL field with the manual classification results.


Process date: 2000

Process step:

PROCESS_GT: filled in spectral, topographic, and hydrologic information in ground-truth training data for use in supervised classification.


Process date: 02/01/2000

Process step:

LABEL_COVERTYPE: performed supervised classification, assigning each region a land cover type label. The training data were analyzed for data attribute accuracy, positional accuracy, and agreement with the imagery. Training data and spatial classifiers were used to classify land cover types. Land cover types were classified using variables: TM1, TM2, TM3, TM4, TM5, TM7, MNDVI, ELEV (scaled elevation ELE / 25), SLP, and SLPASP; a Dudani distance-weighted classifier with a nearest neighborhood size of 10-15, and a mid inverser distance spatial classifer. The results of the classification were filled into the COV_CODE_1, COV_CODE_2, and COV_CODE_3 fields. The final land cover type label was filled into the COVERTYPE field from the MANLABEL field if it was > -1 or from the COV_CODE_1 field. The Mixed Conifer type 4240 was recoded to 3 types using an aml based on the PVTCODE and ELEVATION for the region.

The 3 types are:
4241 Mixed Upper Subalpine Conifer Forest
4242 Mixed Lower Subalpine Conifer Forest
4244 Mixed Xeric Conifer Forest


Process date: 05/01/2000

Process step:

RECODE_CANOPY_DATA: conifer canopy training data were recoded based on MNDVI values:
1 very low cover 0-9% MNDVI < 10
2 low cover 10-24% MNDVI >= 10 and MNDVI < 50
3 low/mod cover 24-44% MNDVI >= 50 and MNDVI < 85
4 mod/high cover 44-64% MNDVI >= 85 and MNDVI < 125
5 high cover 64-100% MNDVI >= 125
CREATE CAN-SIZE CODE: A combined conifer canopy/sizeclass code was developed by multiplying the conifer canopy code by 100 and then adding the conifer sizeclass code. Thus for a plot with conifer canopy 2 (low cover - from above recode) and conifer sizeclass 3 (medium) the combined code would be: (2 * 100) + 3 = 203

A total of 25 different conifer canopy/sizeclass codes were developed.


Process date: 05/15/2000

Process step:

LABEL_CONIFER_CANOPY_SIZE: performed supervised classification, labeled conifer regions classified in the LABEL_COVERTYPE process with a tree size class and tree canopy cover label. The classification used a Dudani distance-weighted classifier with a nearest neighborhood size of 10-15, and a mid inverse distance spatial classifier. The results of the classification were filled into the TREESIZE, TREE_SIZE_1, and TREECANOPY, TREE_CANOPY_1 fields.


Process date: 05/30/2000

Process step:

ACCURACY_ASSESS: performed accuracy assessment of the land cover type and conifer tree size using a leave-one-out cross-validation. The cross-validation involved removing the first training observation from the training set and constructing a new classification rule from the reduced training set. This new rule was then used to classify the polygon containing the left-out training observation. The process was repeated until all observations were held out once and used as a singleton test set.


Process date: 05/30/2000

Process step:

EDGEMATCH: for each scene, identified and labeled regions (KEEP = 1) to be retained where overlap occurs among scenes to make a seamless image for the entire project area. The SILC3REGIONZ region grid was created using a merge of the nine scene region grids. A value attribute table was then created and filled in from the scene region grids using the SCENEPOLY_ID attribute.


Process date: 06/15/2000

Process step: VALIDATE: validation was performed for all items in the VAT.


Process date: 05/15/2000

Spatial Data Organization Information:

Raster object information:

Raster object type: Grid cell
Row count: 17831
Column count: 17846

Spatial Reference Information:

Horizontal coordinate system definition:

Grid coordinate system name: State Plane Coordinate System 1983

SPCS zone identifier: 2500

Lambert conformal conic:

Standard parallel: 45
Standard parallel: 49
Longitude of central meridian: -109.5
Latitude of projection origin: 44.25
False easting: 600000.00000
False northing: 0.00000

Planar distance units: meters

Geodetic model:

Horizontal datum name: North American Datum of 1983
Ellipsoid name: Geodetic Reference System 80
Semi-major axis: 6378137.0
Denominator of flattening ratio: 298.257

Altitude system definition:

Altitude datum name: National Geodetic Vertical Datum of 1929
Altitude resolution: 1.0
Altitude distance units: meters
Altitude encoding method: Implicit coordinate

Entity and Attribute Information:

Entity type label: SILC3REGIONZ.VAT

Entity type definition: Value attribute table for grid

Attribute label: COVERTYPE

Attribute definition:: Final land cover type class assigned after training data and manual classifications.

Attribute label: TREESIZE

Attribute definition:: Conifer tree size filled in from TREE_SIZE_1 for all regions where the COVERTYPE field is between 4203 and 4244.

Attribute label: TREECANOPY

Attribute definition:: Conifer tree canopy filled in from TREE_CANOPY_1 for all regions where the COVERTYPE field is between 4203 and 4244.

Distribution Information:

Distributor:

Montana State Library
PO Box 201800
Helena, MT 59620-1800
Telephone: 406-444-5354
Telephone: 406-444-5354
TDD/TTY telephone: Montana Relay 711
Fax: 406-444-0266
E-Mail: geoinfo@mt.gov
E-Mail: geoinfo@mt.gov

Resource description: Offline Data

Distribution liability:

Metadata Reference Information:

Metadata date: 04/19/2013

Metadata review date: 09/29/2004

Metadata review date: 15/15/2000

Metadata contact:

Chip Fisher
Image Analyst
Wildlife Spatial Analysis Lab
Wildlife Spatial Analysis Lab, The University of Montana
Missoula, Montana 59812-1063
Telephone: 406 243 5208 (email preferred)
Fax: 406 243 6064
E-Mail: cfisher@wru.umt.edu