Metadata - STATSGO Soils
GEODATASET NAME: GLSSTGOMU
IDENTIFICATION INFORMATION
Description:
STATSGO soil map units with supporting attributes for the Great Lakes Basin
study area including 5-km buffer extension
Abstract:
Derived from 1:250,000-scale NRCS STATSGO soils coverage for the U.S.
Data Type:
Coverage, polygon
Data Originator:
USDA Natural Resources Conservation Service
National Cartography and GIS Center
P.O. Box 6567
Fort Worth, TX 76115
Data Processors:
Rick Van Remortel, Ed Evanson, Lee Bice
Lockheed Martin Environmental Services
1050 E. Flamingo Road, Suite E120
Las Vegas, NV 89119
(702)897-3295
rvanremo@lmepo.com
Data Provider:
Ricardo Lopez, Ph.D.
U.S. Environmental Protection Agency
National Exposure Research Laboratory
P.O. Box 93478
Las Vegas, NV 89193-3478
(702)798-2394
lopez.ricardo@epa.gov
Keywords:
Great Lakes Basin, watershed, soils, STATSGO
Version:
N/A
Status:
Interim
Revision Number:
1
Series Name:
Online Link (URL):
Time Period of Content:
From Dec. 1994 revision
Use Constraints:
This coverage contains uncertainty specific to given locations on landscapes,
so users should exercise caution when applying results to local situations.
STATSGO is a state-level database and, as such, the specific attribute value
at a given point on the landscape cannot be known with certainty because the
distribution of soil components within each map unit is variable across a
state. Finer resolution data can be derived from the SSURGO database (for
soil survey areas) where such data have been released by NRCS. However,
SSURGO data only has improved resolution and still is not point-specific.
Caution must be exercised with the interpretations drawn from STATSGO and
SSURGO applications. The present version of this coverage should be
considered Draft, for internal use only at this time.
Purpose:
Great Lakes Basin Landscape Metric Browser website
Date of metadata entry/update:
11/15/2004
No Publication Information Available
No File Security Information Available
DATA QUALITY INFORMATION
Cloud Cover:
Not applicable
Software:
ArcGIS 8.2 Workstation
Operating System:
Windows XP Pro
Path Name:
solec/gds/glsstgomu
Logical Consistency Report:
Not presently available
Completeness Report:
Not presently available
Horizontal Positional Accuracy:
Not presently available
Vertical Positional Accuracy:
Not presently available
Attribute Accuracy:
Not presently available
Procedures:
The base Albers NAD27 state-level coverages were copied from the
U.S. STATSGO workspace and were mapjoined, reprojected to the study area
projection, and then rebuilt and clipped to the study area 5-km buffer
boundary. All required state-level Info attribute files were
copied from the U.S. STATSGO workspace. Using the coverage name, new
attribute files were created to populated with the appended state Info
attribute data.
Reviews Applied to Data
Lockheed Martin internal review
Related Spatial Data Files:
All geodatasets with gls_ prefix
Other References Cited:
Notes:
Update Frequency:
As needed
SPATIAL REFERENCE INFORMATION
Description of DOUBLE precision coverage GLSSTGOMU
FEATURE CLASSES
Number of Attribute Spatial
Feature Class Subclass Features data (bytes) Index? Topology?
------------- -------- --------- ------------ ------- ---------
ARCS 14278
POLYGONS 5062 260 Yes
NODES 9750
ANNOTATIONS (blank) 0
SECONDARY FEATURES
Tics 1343
Arc Segments 465636
Polygon Labels 5061
TOLERANCES
Fuzzy = 0.000 V Dangle = 0.000 N
COVERAGE BOUNDARY
Xmin = 213000.109 Xmax = 1712183.750
Ymin = 1990383.125 Ymax = 2821798.303
STATUS
The coverage has not been Edited since the last BUILD or CLEAN.
COORDINATE SYSTEM DESCRIPTION
Projection ALBERS
Datum NAD83
Units METERS Spheroid GRS1980
Parameters:
1st standard parallel 29 30 0.000
2nd standard parallel 45 30 0.000
central meridian -96 0 0.000
latitude of projection's origin 23 0 0.000
false easting (meters) 0.00000
false northing (meters) 0.00000
ENTITY AND ATTRIBUTE INFORMATION
Annotation Name:
ATTRIBUTE LISTING FOR: GLSSTGOMU
TYPE NAME INTERNAL NAME NO. RECS LENGTH EXTERNL
------------------------------------------------------------------------------
DF GLSSTGOMU.MLRA ARC0061DAT 1253 12
DF GLSSTGOMU.STHK ARC0062DAT 17287 40
DF GLSSTGOMU.PAT ARC0063DAT 5062 260 XX
DF GLSSTGOMU.STHK_C ARC0065DAT 1253 60
DF GLSSTGOMU.HYDGRP ARC0066DAT 17287 36
DF GLSSTGOMU.HYDGRP_C ARC0067DAT 1253 86
DF GLSSTGOMU.HG_A ARC0068DAT 1777 36
DF GLSSTGOMU.HGPCT_A ARC0069DAT 525 16
DF GLSSTGOMU.HG_B ARC0070DAT 6223 36
DF GLSSTGOMU.HGPCT_B ARC0071DAT 1124 16
DF GLSSTGOMU.HG_C ARC0072DAT 4586 36
DF GLSSTGOMU.HGPCT_C ARC0073DAT 911 16
DF GLSSTGOMU.HG_D ARC0074DAT 1224 36
DF GLSSTGOMU.HGPCT_D ARC0075DAT 546 16
DF GLSSTGOMU.HG_AB ARC0076DAT 0 36
DF GLSSTGOMU.HGPCT_AB ARC0077DAT 0 16
DF GLSSTGOMU.HG_AC ARC0078DAT 4 36
DF GLSSTGOMU.HGPCT_AC ARC0079DAT 4 16
DF GLSSTGOMU.HG_AD ARC0080DAT 1112 36
DF GLSSTGOMU.HGPCT_AD ARC0081DAT 477 16
DF GLSSTGOMU.HG_BC ARC0082DAT 1 36
DF GLSSTGOMU.HGPCT_BC ARC0083DAT 1 16
DF GLSSTGOMU.HG_BD ARC0084DAT 1566 36
DF GLSSTGOMU.HGPCT_BD ARC0085DAT 694 16
DF GLSSTGOMU.HG_CD ARC0086DAT 457 36
DF GLSSTGOMU.HGPCT_CD ARC0087DAT 305 16
DF GLSSTGOMU.HG_VAR ARC0088DAT 0 36
DF GLSSTGOMU.HGPCT_VAR ARC0089DAT 0 16
DF GLSSTGOMU.HG_ND ARC0090DAT 337 36
DF GLSSTGOMU.HGPCT_ND ARC0091DAT 278 16
DF GLSSTGOMU.HGPCT ARC0092DAT 17287 72
DF GLSSTGOMU.WTDEP ARC0093DAT 17287 40
DF GLSSTGOMU.WTDEP_C ARC0094DAT 1253 44
DF GLSSTGOMU.KFAC1 ARC0095DAT 17125 32
DF GLSSTGOMU.KFAC1_C ARC0096DAT 1250 24
DF GLSSTGOMU.CLAY1 ARC0097DAT 17125 32
DF GLSSTGOMU.CLAY1_C ARC0099DAT 1250 36
DF GLSSTGOMU.OM ARC0102DAT 55669 38
DF GLSSTGOMU.OM_L ARC0104DAT 17043 30
DF GLSSTGOMU.OM_LC ARC0107DAT 1250 36
DF GLSSTGOMU.TIC ARC0108DAT 1343 20 XX
DF GLSSTGOMU.BND ARC0109DAT 1 32 XX
DF GLSSTGOMU.CACO3 ARC0110DAT 55669 34
DF GLSSTGOMU.CACO3_L ARC0111DAT 17043 30
DF GLSSTGOMU.CACO3_LC ARC0112DAT 1250 36
DF GLSSTGOMU.BD ARC0113DAT 53366 38
DF GLSSTGOMU.BD_L ARC0114DAT 16303 30
DF GLSSTGOMU.BD_LC ARC0115DAT 1249 36
DF GLSSTGOMU.AWC ARC0116DAT 55672 38
DF GLSSTGOMU.AWC_L ARC0117DAT 17045 30
DF GLSSTGOMU.AWC_LC ARC0118DAT 1250 36
DF GLSSTGOMU.PERM ARC0119DAT 57225 40
DF GLSSTGOMU.PERM_L ARC0120DAT 17063 32
DF GLSSTGOMU.PERM_LC ARC0121DAT 1250 38
DF GLSSTGOMU.SPSF ARC0122DAT 53576 160
DF GLSSTGOMU.SPSF_L ARC0124DAT 16375 92
DF GLSSTGOMU.SPSF_LC ARC0127DAT 1249 178
DF GLSSTGOMU.SAND_LC ARC0128DAT 1249 22
DF GLSSTGOMU.CLAY ARC0129DAT 55669 42
DF GLSSTGOMU.CLAY_L ARC0130DAT 17043 30
DF GLSSTGOMU.CLAY_LC ARC0131DAT 1250 36
DF GLSSTGOMU.COMP ARC0247DAT 17287 292
DF GLSSTGOMU.COMPYLD ARC0248DAT 77246 60
DF GLSSTGOMU.FOREST ARC0249DAT 57198 24
DF GLSSTGOMU.INTERP ARC0250DAT 445074 24
DF GLSSTGOMU.LAYER ARC0251DAT 58407 244
DF GLSSTGOMU.MAPUNIT ARC0252DAT 1253 142
DF GLSSTGOMU.PLANTCOM ARC0253DAT 0 24
DF GLSSTGOMU.PLANTNM ARC0254DAT 1853 98
DF GLSSTGOMU.RSPROD ARC0255DAT 0 88
DF GLSSTGOMU.TAXCLASS ARC0256DAT 1769 164
DF GLSSTGOMU.WINDBRK ARC0257DAT 139666 24
DF GLSSTGOMU.WLHABIT ARC0258DAT 16929 122
DF GLSSTGOMU.WOODLAND ARC0259DAT 103200 28
DF GLSSTGOMU.WOODMGT ARC0260DAT 13676 58
DF GLSSTGOMU.YLDUNITS ARC0261DAT 1808 40
DF GLSSTGOMU.S5_LAYER ARC0262DAT 58407 302
DF GLSSTGOMU.S5_COMP ARC0263DAT 17287 152
METADATA REFERENCE SECTION
FGDC Content Standards for Digital Geospatial Metadata
FGDC Standards Version 6/98 / metadata.aml ver. 1.3 5/21/99
SUPPLEMENTAL METADATA (where available)
Overview
STATSGO was compiled for each state and designed primarily for
regional, multi-state, river basin, state and multi-county resource
planning, management, and monitoring. STATSGO data are not sufficiently
detailed to make interpretations at the county level. In most areas,
STATSGO maps were compiled by generalizing more detailed SSURGO maps.
Where more detailed soil survey maps were not available, data on geology,
topography, vegetation, and climate were assembled, together with LANDSAT
images. Soils of like areas were studied, and probable classification and
extent of soils was determined. STATSGO map units are combinations of areas
on the more detailed soils maps. Attributes of STATSGO map units are
statistical summaries of attributes from all the component soils used to
characterize an entire map unit. Consequently, each map unit can have
multiple components (maximum of 21) and each component can have multiple
layers (maximum of six). The soils component attribute table maintains
60 variables for each soil component. The layer table maintains 28 variables
for each soil component layer. In addition to the soil tables (component
and layer), STATSGO contains ten interpretive data tables and three lookup
tables for use with the spatial database.
STATSGO includes a complex variety of soil and soil-related data on
a state-wide basis. The challenge in creating a tool to access this database
is to make access efficient and easy-to-use within the constraints of the
database design. The STATSGO multiple component and layer structure of the
database makes its use with GIS complex. The structure of STATSGO requires
linking map units and attribute tables through a many-to-many-to-many
relationship. That is, there are many non-contiguous polygons in each STATSGO
map unit. Texas, for example, has map units with as many as 45 discrete polygons,
and one map unit in Alaska has 90 polygons. Individual state component tables
are related to map units by map unit identifier (MUID). There are as many as
21 soil components for each map unit. The layer table is related to the
component table by unique component identifiers made up of a MUID and sequence
number (SEQNUM). Sequence numbers represent soil layers in each component.
There are as many as 6 soil layers for each soil component.
The STATSGO map unit is the smallest spatial entity that can be queried
and mapped while remaining consistent with the database. Map units are comprised
of up to 21 components of varying areas that contribute to the total area of the
map unit. The areal/spatial composition of the map unit was derived from a
statistical analysis of transects across detailed soil survey maps. The area of
the map unit occupied by each component is proportional to the length of the
transects containing that component. The area occupied by each component is
represented as a percent of the map unit, but there is no specific location of
individual components within any polygon. Thus, the percentage of each soil
component area in the map unit must be used to characterize the map unit.
In order to make STATSGO soils data compatible with the Arc/Info data
model, the structure of the database can be modified include an intermediate
key file and an accumulation table to replace the many-to-many relationships
with one-to-many relationships. The key file contains the component percentages
for each map unit.
Narrative
The U.S. Department of Agriculture (USDA) Natural Resources
Conservation Service (NRCS), formerly Soil Conservation Service (SCS), leads
National Cooperative Soil Survey (NCSS) and is responsible for collecting,
storing, maintaining, and distributing soil survey information for privately
owned lands in the United States. The NRCS established three soil geographic
data bases representing kinds of soil maps. The maps are produced from
different intensities and scales of mapping. Each data base has a common link
to an attribute data file for each map unit component. The Soil Interpretations
Record (SIR) data base provides attribute data for each geographic data base.
The three soil geographic data bases are the Soil Survey Geographic
(SSURGO) data base, the State Soil Geographic (STATSGO) data base, and the
National Soil Geographic (NATSGO) data base. Components of map units in each
data base are generally phases of soil series that enable the most precise
interpretation. Interpretations are displayed differently for each geographic
data base to be consistent with differing levels of detail. The SIR data base
contains physical and chemical soil properties for approximately 18,000 soil
series recognized in the United States.
The SSURGO data base provides the most detailed level of information
and was designed primarily for farm and ranch, landowner/user, township, county,
or parish natural resource planning and management. Using the soil attributes,
this data base serves as an excellent source for determining erodible areas and
developing erosion control practices, reviewing site development proposals and
land use potential, making land use assessments, and identifying potential
wetlands and sand and gravel aquifer areas. Using NCSS mapping standards,
soil maps in the SSURGO data base are made using field methods. Surveyors
observe soils along delineation boundaries and determine map unit composition
by field traverses and transects. Aerial photographs are interpreted and
used as the field map base. Maps are made at scales ranging from 1:12,000 to
1:63,360. Typically scales are 1:15,840, 1:20,000, or 1:24,000. The maps, along
with comprehensive descriptions, produce an attribute and spatial data base for
NCSS publications. Line segments (vectors) are digitized in accordance with
specifications and standards established by the NRCS for duplicating the
original soil survey map. The mapping bases are normally orthophotoquads,
and digitizing is performed by NRCS, by contractors, or by cooperating Federal,
State, and local governments. Data for the SSURGO data base are collected and
archived in 7.5 minute topographic quadrangle units and distributed as a
complete coverage for a soil survey area usually consisting of 10 or more
quadrangle units. The adjoining 7.5 minute units are matched within the survey
areas.
The STATSGO data base was designed primarily for regional, multistate,
river basin, State, and multicounty resource planning, management, and
monitoring. STATSGO data are not detailed enough to make interpretations
at a county level. Soil maps for STATSGO are compiled by generalizing more
detailed (SSURGO) soil survey maps. Where more detailed soil survey maps are
not available, data on geology, topography, vegetation, and climate are
assembled, together with Land Remote Sensing Satellite (LANDSAT) images.
Soils of like areas are studied, and the probable classification and extent
of the soils are determined. Map unit composition for a STATSGO map is
determined by transecting or sampling areas on the more detailed maps and
expanding the data statistically to characterize the whole map unit. Using
the United States Geological Survey's (USGS) 1:250,000 scale, 1- by 2-degree
quadrangle series as a map base, the soil data are digitized by line segment
(vector) method to comply with national guidelines and standards. Data for
the STATSGO data base are collected in 1- by 2-degree topographic quadrangle
units and merged and distributed as statewide coverages. Features are edge
matched between states. The map unit composition and the proportionate
extent of the map unit components also match between states.
The NATSGO data base is used primarily for national and regional
resource appraisal, planning, and monitoring. The boundaries of the major
land resource areas (MLRA) and regions were used to form the NATSGO data
base [6]. The MLRA boundaries were developed primarily from State general
soil maps. Map unit composition for NATSGO was determined by sampling done
as part of the 1982 National Resources Inventory [7]. Sample data were
expanded for the MLRAs, with sample design being statistically significant
to State parts of the MLRAs. The NATSGO map was compiled on an NRCS-adapted
version of the 1970 Bureau of Census automated State and county map data
base and it was digitized from the USGS 1:5,000,000 scale U.S. base map.
This document describes the STATSGO data, which provide national
coverage at a scale of 1:250,000, except for Alaska, which is at a scale
of 1:2,000,000. A soil map in a soil survey is a representation of soil
patterns in a landscape. The scale of the map and the complexity of the
soil patterns determine what can be shown on the soil map. In designing
soil surveys, the projected uses of the survey and the complexity of the
soil patterns largely determine the scale of the soil map [4]. When using
soil maps, remember that scale, accuracy, and detail are not synonymous.
Scale is the relationship between corresponding distance on a map and the
actual distance on the ground. Accuracy is the degree or precision with
which map information is obtained, measured, and recorded, and detail is
the amount of information shown.
Map scale, accuracy, and detail are interrelated. A large-scale map
is not necessarily more accurate or more detailed than a small-scale map;
however, it generally shows more detail than a small-scale map. Soil maps
are made by using field investigation methods. The accuracy of the maps is
determined by many factors, including the complexity of the soils, design
of the soil map units, intensity of field observations and data collection,
and skills of the mapper. A soil map at 1:250,000 scale should not be used
to locate soils for intensive land uses, such as determining suitability for
house lots. It is useful for understanding the soil resources and for planning
broad use in a State or region. A soil map at 1:20,000 scale is useful in
understanding and planning the soil resources of fields, farms, and
communities, but it is not useful for planning small (less than 1 acre)
research plots. In many places the pattern of soils is very complex, and in
some places soils grade imperceptibly to others. Because of this, soil
delineations, even on large-scale maps, are not homogeneous or pure; thus,
onsite investigations are needed to determine, for example, the suitability
of a plot for a septic tank installation when using a soil map at scale of
1:20,000. The common practice of enlarging soil maps does not result in more
detailed or accurate maps. Soil survey maps enlarged to 1:12,000 scale from
1:20,000 scale are no more accurate or detailed than the original 1:20,000 map.
Many times the information on soil maps is transferred to other base maps at
different scales, which diminishes the new map's accuracy, especially if the
base map is not planimetrically correct.
Soil interpretive maps for specific uses are commonly made from the
soil maps. These kinds of maps are single purpose and have the same credibility
and limitations as the soil maps from which they are made. Recognizing the
different kinds of soil maps, knowing their merits and limitations, and
understanding the relationship of map scale, accuracy, and detail are important.
In a detailed SSURGO soil map, each map unit is usually represented by a single
soil component, typically a soil series phase [5]. Some SSURGO map units may
have up to three named components. An interpretive map is normally made by
classifying each unit according to the set of soil properties for a single
component. In contrast, each map unit on a STATSGO map contains up to 21
discrete components for which there are attribute data, but there is no
visible distinction as to the location of these components within the
delineation. Thus, to present information on an attribute, a series of maps
must be used to portray the more complex set of available information. The
legend for STATSGO interpretive maps commonly shows the percentage of the map
unit that meets a criterion or criteria. Caution must be used in evaluating
the statistics presented in such a legend. Percentage ranges given represent
all delineations in that class and do not represent an individual STATSGO
delineation. Percentages do not statistically represent a subset of the
delineation such as a county portion. They also do not represent the areas
of the soil components that satisfy the criterion. However, the area of each
map unit component is recorded in the data base and can be used to produce
a table, even though the components cannot be displayed directly on the map.
When STATSGO data are overlayed with other data, such as land use data,
caution must be used in generating statistics on the co-occurrence of the land
use data with the soil data. The composition of the STATSGO map unit can be
characterized independently for the land use and for the soil component, but
there are no data on their joint occurrence at a more detailed level. Analysis
of the overlayed data should be on a map polygon basis. It is incorrect to
assign land use attributes to the soil components by multiplying the
proportions of soil components by the proportions of land uses. Additional
political, watershed, or other boundaries may be intersected with the soil data.
Although the composition of each political and watershed unit may be described
in terms of the STATSGO map units, information is not available to assign the
components to the boundary units with full accuracy. As with the land use
categories, the analysis should be restricted to the classified components.
Map Unit Delineations
Approximate minimum area delineated is 625 hectares (1,544 acres),
represented on a map of 1:250,000 scale by an area appropriately 1 cm by
1 cm (0.4 inch by 0.4 inch). Linear delineations should not be less than
0.5 cm (0.2 inch) in width. The number of delineations per 1:250,000
quadrangle should range from 100 to 200, but a range of up to 400 is allowed.
Delineations depict the dominant soils making up thelandscape. Other dissimilar
soils, too small to be delineated, are present within a delineation. Map unit
delineations must join at State boundaries and composition of map
units must be coordinated across State boundaries, not only in the identity,
but also in the relative extent of each component. All component phase
criteria are to join across State boundaries.
Digital enlargements of these maps to scales greater than at which
they were originally mapped can cause misinterpretation of the data. If
enlarged, maps do not show the small areas of contrasting soils that could
have been shown at a larger scale. The depicted soil boundaries,
interpretations, and analysis derived from them do not eliminate the need for
onsite sampling, testing, and detailed study of specific sites for intensive
uses. Thus, these data and their interpretations are intended for planning
purposes only.
Components
Map units are a combination of associated phases of soil series.
Information about map units includes reliable estimates of the components
and the percentage and method by which the composition is determined.
Composition is determined by transecting representative segments of map
units in published or unpublished soil surveys and documenting component
composition or by using acreage data in the map unit use file. Transects
may be observed in the field; however, it is more likely that they will be
located and examined on soil survey field sheets or in published soil surveys.
Attribute Tables
Map unit delineations are described by the Map Unit
Interpretations Record data base. This attribute data base
gives the proportionate extent of the component soils and the
properties for each soil. The data base contains both
both estimated and measured data on the physical and chemical
soil properties and soil interpretations for engineering,
water management, recreation, agronomic, woodland, range and
wildlife uses of the soil. The Soil Map Unit Interpretations
Record data base consist of the following relational tables:
codes (data base codes) - stores information on all codes
used in the data base
comp (map unit component) - stores information which will
apply to a specific component of a soil map unit
compyld (component crop yield) - stores crop yield
information for soil map unit components
forest (forest understory) - stores information for plant
cover as forest understory for soil map unit components
interp (interpretation) - stores soil interpretation
ratings (both limitation ratings and suitability
ratings) to soil map unit components
layer (soil layer) - stores characteristics which apply to
soil layers for soil map unit components
mapunit (map unit) - stores information which applies to
all components of a soil map unit
plantcom (plant composition) - stores plant symbols and
percent of plant composition associated with components
of soil map units
plantnm (plant name) - stores the common and scientific
names for plants used in the data base
rsprod (range site production) - stores range site
production information for soil map unit components
taxclass (taxonomic classification) - stores the taxonomic
classification for soils in the data base
windbrk (windbreak) - stores information on recommended
windbreak plants for soil map unit components
wlhabit (wildlife habitat) - stores wildlife habitat
information for soil map unit components
woodland (woodland) - store information on common indicator
trees for soil map unit components
woodmgt (woodland management) - stores woodland management
information for soil map unit components
yldunits (yield units) - stores crop names and the units
used to measure yield
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