Metadata for National Land Cover Dataset for Montana
Table of Contents
Citation:
Originator: U.S. Geological Survey
Publication_Date: 2000
Title: National Land Cover Data for Montana
Online_Linkage: http://nris.mt.gov/nsdi/nris/nlcd/nlcdgrid.html
Online_Linkage: http://landcover.usgs.gov/natllandcover.html
Description:
Abstract:
This is the 1992 National Land Cover Data Set for Montana, projected to
Montana State Plane Coordinates, converted to ESRI GRIDASCII format, and
divided into 39 regions to create downloadable files of manageable size.
The National Land Cover Data Set was produced as part of a cooperative
project between the U.S. Geological Survey (USGS) and the U.S.
Environmental Protection Agency (USEPA) to produce a consistent, land
cover data layer for the conterminous U.S. based on 30-meter Landsat
thematic mapper (TM) data. National Land Cover Data (NLCD) was
developed from TM data acquired by the Multi-resoultion Land
Characterization (MRLC) Consortium. The MRLC Consortium is a
partnership of federal agencies that produce or use land cover data.
Partners include the USGS (National Mapping, Biological Resources, and
Water Resources Divisions), USEPA, the U.S. Forest Service, and the
National Oceanic and Atmospheric Administration.
The Montana NLCD set was produced as part of a project area
encompassing portions of Federal Regions 8 and 10. This data set was
produced under the direction of the MRLC Regional Land Cover
Characterization Project of the USGS EROS Data Center (EDC), Sioux Falls,
SD. Questions about the data set can be directed to the MRLC
Regional Team at (605) 594-6114 or mrlc@edcmail.cr.usgs.gov.
This data set was extracted from the larger regional data set. State
boundaries from the USGS 1:100,000 Digital Line Graph (DLG) series were
used as the basis for extracting the state data. In many instances,
the precision of the boundaries in the 1:100,000 DLG data does not
match the spatial precision of the Landsat TM data. To overcome the
possibility of data being lost in the extraction process, a 300 meter
(10 pixel) buffer was added to the state boundary used to extract the
state data.
The base data set for this project was leaves-off Landsat TM data,
nominal-1992 acquisitions. Other ancillary data layers included
leaves-on TM, USGS 3-arc second Digital Terrain Elevation Data (DTED)
and derived slope, aspect and shaded relief, Bureau of the Census
population and housing density data, USGS land use and land cover (LUDA),
and National Wetlands Inventory (NWI) data if available.
Caveats and Concerns:
Both irrigated and dryland agriculture are practiced in this region.
In the dryland areas small grains predominate; fields are classified as
fallow when there is no evidence of visible vegetation indicating a
prescribed alternation between cropping and tillage. Crop types in the
irrigated areas were difficult to reliably distinguish; row crops are
likely to be under represented where no field observations or other
ancillary information was incorporated.
Purpose:
Many federal agencies, including the U.S. Geological Survey, the U.S.
Environmental Protection Agency, the U.S. Forest Service, the National
Oceanic and Atmospheric Administration, state goverments, and various
environmental groups need up-to-date intermediate scale land cover data.
The most recent intermediate scale land cover data set generated for
the conterminous United States was developed by the USGS in the 1970's.
Although this data set is probably still adequate for some applications,
many land cover changes have occurred since the data set was compiled.
The main objective of this project is to generate a relatively current,
consistent, seamless, and accurate land cover data set for the
conterminous United States.
Potential uses of land cover data are many and varied, and include
assessing ecosystem status and health, modeling nutrient and pesticide
runoff, understanding spatial patterns of biodiversity, land use
planning, deriving landscape pattern metrics, and developing land
management policy.
Time_Period_of_Content:
Beginning_Date: 5/26/1985
Ending_Date: 6/19/1995
Use_Constraints:
This data set is provided "as-is" without warranty of any kind, including,
but not limited to, the implied warranties of fitness for a particular
purpose. The user assumes all responsibility for the accuracy and
suitability of this data set for a specific application. This data is
not intended for use a scales greater than 1:60,000.
The user must have a firm understanding of how the datasets were compiled
and the resulting limitations of these data. The National Land Cover
Dataset was compiled from Landsat satellite TM imagery (circa 1992) with a
spatial resolution of 30 meters and supplemented by various ancillary data
(where available). The analysis and interpretation of the satellite imagery
was conducted using very large, sometimes multi-state image mosaics (i.e.
up to 18 Landsat scenes). Using a relatively small number of aerial
photographs for 'ground truth', the thematic interpretations were
necessarily conducted from a spatially-broad perspective. Thus, the
reliability of the data is greatest at the state or multi-state level.
Important Caution Advisory
With this in mind, users are cautioned to carefully scrutinize the data to
see if they are of sufficient reliability before attempting to use the
dataset for larger-scale or local analyses. This evaluation must be made
remembering that the NLCD represents conditions in the early 1990s.
Attribute_Accuracy_Report:
The accuracy of this data has not been assesed for Montana. See
http://landcover.usgs.gov/accuracy/ for the status of accuracy assement
of the NLCD.
The MRLC's general discussion of the accuracy of the NLCD follows:
While we believe that the approach taken has yielded a very good
general land cover classification product for a large region, it is
important to indicate to the user where there might be some potential
problems. The biggest concerns are listed below:
1) Some of the TM data sets are not temporally ideal. Leaves-off data
sets are heavily relied upon for discriminating between hay/pasture and
row crop, and also for discriminating between forest classes. The
success of discriminating between these classes using leaves-off data
sets hinges on the time of data acquisition. When hay/pasture areas
are non-green, they are not easily distinguishable from other
agricultural areas using remotely sensed data. However, there is a
temporal window during which hay and pasture areas green upbefore most
other vegetation (excluding evergreens, which have different spectral
properties); during this window these areas are easily distinguishable
from other crop areas. The discrimination between hay/pasture and
deciduous forest is likewise optimized by selecting data in a temporal
window where deciduous vegetation has yet to leaf out. It is difficult
to acquire a single-date of imagery (leaves-on or leaves-off) that
adequately differentiates between both deciduous/hay and pasture and
hay-pasture/row crop.
2) The data sets used cover a range of years (see data sources), and
changes that have taken place across the landscape over the time period
may not have been captured. While this is not viewed as a major
problem for most classes, it is possible that some land cover features
change more rapidly than might be expected (e.g. hay one year, row crop
the next).
3) Wetlands classes are extremely difficult to extract from Landsat TM
spectral information alone. The use of ancillary information such as
National Wetlands Inventory (NWI) data is highly desirable. We relied
on GAP, LUDA, or proximity to streams and rivers as well as spectral
data to delineate wetlands in areas without NWI data.
4) Separation of natural grass and shrub is problematic. Areas observed
on the ground to be shrub or grass are not always distinguishable
spectrally. Likewise, there was often disagreement between LUDA and
GAP on these classes.
Horizontal_Positional_Accuracy_Report:
Each Landsat Thematic Mapper image used to create the NLCD was
precision terrain-corrected using 3-arc-second digital terrain
elevation data (DTED), and georegistered using ground control
points. This resulted in a root mean square registration error
of less than 1 pixel (30 meters).
Lineage:
Source_Information:
Originator: U.S. Geological Survey
Publication_Date: 2000
Title: National Land Cover Data Set, Montana
Edition: 2000-05
Source_Time_Period_of_Content:
Beginning_Date: 5/26/1985
Ending_Date: 6/19/1995
Source_Contribution:
The data set is a re-formatted version of this source. The dates of
the source LandSat scenes follows:
LEAF OFF:
Path Row Date Path Row Date
034 028 19 Jun 89 034 029 19 Jun 89
035 026 19 Jun 95 035 027 10 Jun 92
035 028 10 Jun 92 035 029 10 Jun 92
036 026 15 Jun 91 036 027 06 Jun 88
036 028 09 Jun 89 036 029 15 Jun 91
037 026 11 Jun 87 037 027 10 May 93
037 028 10 May 93 037 029 28 May 88
038 026 27 Jun 88 038 027 26 May 88
038 028 30 Jun 89 038 029 30 May 86
039 026 04 Jun 88 039 027 04 Jun 88
039 028 04 Jun 88 039 029 05 May 92
040 026 28 May 86 040 027 28 May 86
040 028 28 May 86 040 029 13 Jun 86
041 026 09 Jun 86 041 027 03 May 92
041 028 24 May 88 042 026 16 Jun 88
042 027 26 May 86
LEAF ON:
Path Row Date Path Row Date
034 028 09 Aug 93 034 029 09 Aug 93
035 026 16 Aug 93 035 027 16 Aug 93
035 028 16 Aug 93 035 029 16 Aug 93
036 026 07 Aug 93 036 027 07 Aug 93
036 028 07 Aug 93 036 029 04 Aug 92
037 026 14 Aug 93 037 027 14 Aug 93
037 028 14 Aug 93 037 029 28 Sep 92
038 026 22 Sep 93 038 027 22 Sep 93
038 028 22 Sep 93 038 029 22 Sep 93
039 026 10 Sep 92 039 027 09 Aug 92
039 028 09 Aug 92 039 029 09 Aug 92
040 026 19 Aug 93 040 027 20 Jul 88
040 028 19 Aug 93 040 029 13 Jul 92
041 026 28 Aug 88 041 027 21 Aug 91
041 028 21 Aug 91 042 026 14 Aug 92
042 027 14 Aug 92
Process_Step:
Process_Description:
This is the MRLC's description of some of the methods used to create
the NLCD:
The project is being carried out on the basis of 10 Federal Regions
that make up the conterminous United States; each region is comprized
of multiple states; each region is processed in subregional units
that are limited to the area covered by no more than 18 Landsat TM
scenes. The general NLCD procedure is to: (1) mosaic subregional TM
scenes and classify them using an unsupervised clustering algorithm,
(2) interpret and label the clusters/classes using aerial photographs
as reference data, (3) resolve the labeling of confused
clusters/classes using the appropriate ancillary data source(s), and
(4) incorporate land cover information from other data sets and
perform manual edits to augment and refine the "basic" classification
developed above.
Two seasonally distinct TM mosaics are produced, a leaves-on version
(summer) and a leaves-off (spring/fall) version. TM bands 3 4 5 and
7 are mosaicked for both the leaves-on and leaves-off versions. For
mosaicking purposes, a base scene is selected for each mosaic and the
other scenes are adjusted to mimic spectral properties of the base
scene using histogram matching in regions of spatial overlap.
Following mosaicking, either the leaves-off version or leaves-on
version is selected to be the "base" for the land cover mapping
process. The 4 TM bands of the "base" mosaic are clustered to
produce a single 100-class image using an unspervised clustering
algorithm. Each of the spectrally distinct clusters/classes is then
assigned to one or more Anderson level 1 and 2 land cover classes
using National High Altitude Photography program (NHAP) and National
Aeria l Photography program (NAPP) aerial photographs as a reference.
Almost invariably, individual spectral clusters/classes are confused
between two or more land cover classes.
Separation of the confused spectral clusters/classes into appropriate
NLCD class is accomplished using ancillary data layers. Standard
ancillary data layers include: the "non-base" mosaic TM bands and
100-class cluster image; derived TM normalized vegetation index (NDVI),
various TM band ratios, TM date bands; 3-arc second Digital Terrain
Elevation Data (DTED) and derived slope, aspect and shaded relief;
population and housing density data; USGS land use and land cover
(LUDA); and National Wetlands Inventory (NWI) data if available.
Other ancillary data sources may include soils data, unique state or
regional land cover data sets, or data from other federal programs
such as the National Gap Analysis Program (GAP) of the USGS
Biological Resources Division (BRD). For a given confused spectral
cluster/class, digital values of the various ancillary data layers
are compared to determine: (1) which data layers are the most
effective for splitting the confused cluster/class into the
appropriate NLCD class, and (2) the appropriate layer thresholds for
making the split(s). Models are then developed using one to several
ancillary data layers to split the confused cluster/class into the
NLCD class. For example, a population density threshold is used to
separate high-intensity residential areas from commercial/industrial
/transportation. Or a cluster/class might be confused between row
crop and grasslands. To split this particular cluster/class, a TM
NDVI threshold might be identified and used with an elevation
threshold in a class-spliting model to make the appropriate NLCD
class assignments. A purely spectral example is using the temporally
opposite TM layers to discriminate confused cluster/classes such as
hay pasture vs. row crops and deciduous forests vs. evergreen forests;
simple thresholds that contrast the seasonal differences in
vegetation between leaves-on vs. leaves-off.
Not all cluster/class confusion can be successfully modeled out.
Certain classes such as urban/recreational grasses or quarries/strip
mines/gravel pits that are not spectrally unique require manual
editing. These class features are typically visually identified and
then reclassified using on-screen digitizing and recoding. Other
classes such as wetlands require the use of specific data sets such
as NWI to provide the most accurate classification. Areas lacking
NWI data are typically subset out and modeling is used to estimate
wetlands in these localized areas. The final NLCD product results
from the classification (interpretation and labeling) of the
100-class "base"cluster mosaic using both automated and manual
processes, incorporating both spectral and conditional data layers.
Process_Date: 2000
Process_Step:
Process_Description:
Convert the downloaded National Land Cover data file into ESRI GRID
format and project the data to Montana State Plane Coordinates.
Process_Date: 2000
Process_Step:
Process_Description:
Convert 39 regions from the ESRI GRID version of the NLCD to ESRI
GRIDASCII format.
Process_Date: 2003
Direct_Spatial_Reference_Method: Raster
Number of Rows: 17696
Number of Columns: 3068
Horizontal_Coordinate_System_Definition:
Grid_Coordinate_System
Grid_Coordinate_System_Name: State Plane Coordinate System 1983
SPCS_Zone_Identifier: 2500
Map_Projection_Name: 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
Coordinate_Representation
Abscissa_Resolution: 30
Ordinate_Resolution: 30
Planar_Distance_Units: meters
Geodetic_Model
Horizontal_Datum_Name: North American Datum of 1983
Entity_and_Attribute_Information:
Detailed_Description
Attribute
Attribute_Label: VALUE
Attribute_Definition: Land Cover Code
Enumerated_Domain_Value Enumerated_Domain_Value_Definition
----------------------- ----------------------------------
11 Open Water
12 Perennial Ice/Snow
21 Low Intensity Residential
22 High Intensity Residential
23 Commercial/Industrial/Transportation
31 Bare Rock/Sand/Clay
32 Quarries/Strip Mines/Gravel Pits
33 Transitional
41 Deciduous Forest
42 Evergreen Forest
43 Mixed Forest
51 Shrubland
61 Orchards/Vineyards/Other
71 Grasslands/Herbaceous
81 Pasture/Hay
82 Row Crops
83 Small Grains
84 Fallow
85 Urban/Recreational Grasses
91 Woody Wetlands
92 Emergent Herbaceous Wetlands
Entity_and_Attribute_Overview
NLCD Land Cover Classification System Land Cover Class Definitions
Water - All areas of open water or permanent ice/snow cover.
11. Open Water - All areas of open water; typically 25 percent or
greater cover of water (per pixel).
12. Perennial Ice/Snow - All areas characterized by year-long cover of
ice and/or snow.
Developed - Areas characterized by a high percentage (30 percent or
greater) of constructed materials (e.g. asphalt, concrete, buildings,
etc).
21. Low Intensity Residential - Includes areas with a mixture of
constructed materials and vegetation. Constructed materials account
for 30-80 percent of the cover. Vegetation may account for 20 to 70
percent of the cover. These areas most commonly include single-family
housing units. Population densities will be lower than in high
intensity residential areas.
22. High Intensity Residential - Includes highly developed areas where
people reside in high numbers. Examples include apartment complexes
and row houses. Vegetation accounts for less than 20 percent of the
cover. Constructed materials account for 80 to100 percent of the
cover.
23. Commercial/Industrial/Transportation - Includes infrastructure
(e.g. roads, railroads, etc.) and all highly developed areas not
classified as High Intensity Residential.
Barren - Areas characterized by bare rock, gravel, sand, silt, clay, or
other earthen material, with little or no "green" vegetation present
regardless of its inherent ability to support life. Vegetation, if
present, is more widely spaced and scrubby than that in the "green"
vegetated categories; lichen cover may be extensive.
31. Bare Rock/Sand/Clay - Prennially barren areas of bedrock, desert
pavement, scarps, talus, slides, volcanic material, glacial debris,
beaches, and other accumulations of earthen material.
32. Quarries/Strip Mines/Gravel Pits - Areas of extractive mining
activities with significant surface expression.
33. Transitional - Areas of sparse vegetative cover (less than 25
percent of cover) that are dynamically changing from one land cover to
another, often because of land use activities. Examples include forest
clearcuts, a transition phase between forest and agricultural land, the
temporary clearing of vegetation, and changes due to natural causes
(e.g. fire, flood, etc.).
Forested Upland - Areas characterized by tree cover (natural or
semi-natural woody vegetation, generally greater than 6 meters tall);
tree canopy accounts for 25-100 percent of the cover.
41. Deciduous Forest - Areas dominated by trees where 75 percent or
more of the tree species shed foliage simultaneously in response to
seasonal change.
42. Evergreen Forest - Areas dominated by trees where 75 percent or
more of the tree species maintain their leaves all year. Canopy is
never without green foliage.
43. Mixed Forest - Areas dominated by trees where neither deciduous
nor evergreen species represent more than 75 percent of the cover present.
Shrubland - Areas characterized by natural or semi-natural woody
vegetation with aerial stems, generally less than 6 meters tall, with
individuals or clumps not touching to interlocking. Both evergreen
and deciduous species of true shrubs, young trees, and trees or
shrubs that are small or stunted because of environmental conditions
are included.
51. Shrubland - Areas dominated by shrubs; shrub canopy accounts for
25-100 percent of the cover. Shrub cover is generally greater than 25
percent when tree cover is less than 25 percent. Shrub cover may be
less than 25 percent in cases when the cover of other life forms (e.g.
herbaceous or tree) is less than 25 percent and shrubs cover exceeds
the cover of the other life forms.
Non-natural Woody - Areas dominated by non-natural woody vegetation;
non-natural woody vegetative canopy accounts for 25-100 percent of the
cover. The non-natural woody classification is subject to the
availability of sufficient ancillary data to differentiate non-natural
woody vegetation from natural woody vegetation.
61. Orchards/Vineyards/Other - Orchards, vineyards, and other areas
planted or maintained for the production of fruits, nuts, berries, or
ornamentals.
Herbaceous Upland - Upland areas characterized by natural or
semi-natural herbaceous vegetation; herbaceous vegetation accounts for
75-100 percent of the cover.
71. Grasslands/Herbaceous - Areas dominated by upland grasses and
forbs. In rare cases, herbaceous cover is less than 25 percent, but
exceeds the combined cover of the woody species present. These areas
are not subject to intensive management, but they are often utilized
for grazing.
Planted/Cultivated - Areas characterized by herbaceous vegetation that
has been planted or is intensively managed for the production of food,
feed, or fiber; or is maintained in developed settings for specific
purposes. Herbaceous vegetation accounts for 75-100 percent of the cover.
81. Pasture/Hay - Areas of grasses, legumes, or grass-legume mixtures
planted for livestock grazing or the production of seed or hay crops.
82. Row Crops - Areas used for the production of crops, such as corn,
soybeans, vegetables, tobacco, and cotton.
83. Small Grains - Areas used for the production of graminoid crops
such as wheat, barley, oats, and rice.
84. Fallow - Areas used for the production of crops that are
temporarily barren or with sparse vegetative cover as a result of
being tilled in a management practice that incorporates prescribed
alternation between cropping and tillage.
85. Urban/Recreational Grasses - Vegetation (primarily grasses)
planted in developed settings for recreation, erosion control, or
aesthetic purposes. Examples include parks, lawns, golf courses,
airport grasses, and industrial site grasses.
Wetlands - Areas where the soil or substrate is periodically saturated
with or covered with water as defined by Cowardin et al.
91. Woody Wetlands - Areas where forest or shrubland vegetation
accounts for 25-100 percent of the cover and the soil or substrate is
periodically saturated with or covered with water.
92. Emergent Herbaceous Wetlands - Areas where perennial herbaceous
vegetation accounts for 75-100 percent of the cover and the soil or
substrate is periodically saturated with or covered with water.
Metadata_Date: 4/25/2003
Metadata_Contact
Contact_Organization: Montana State Library
Contact_Person: Gerry Daumiller
Address: PO Box 201800
City: Helena
State_or_Province: Montana
Postal_Code: 59620-1800
Contact_Voice_Telephone: (406) 444-5358
Contact_Electronic_Mail_Address: gdaumiller@mt.gov