USGS Home
Contact USGS
Search USGS

South America Land Cover Characteristics Data Base Version 2.0

PLEASE NOTE: This is the Version 2.0 release of the South America land cover characteristics data base. The land cover information has been updated from Version 1.2.  Please read section 5.0 for information about the revision process and what changes have been made to the data. 

Table of Contents

• 1.0 Data Description
• 1.1 Anonymous FTP for UNIX or PC Users
• 1.2 Downloading from the World Wide Web Site
• 2.0 Geometric Characteristics
• 2.1 Interrupted Goode Homolosine Projection Parameters
• 2.2 Lambert Azimuthal Equal Area Projection Parameters
• 3.0 File Listing
• 4.0 Derived Data Sets
• 4.1 South America Seasonal Land Cover Regions Legend
• 4.2 Global Ecosystems Legend
• 4.3 IGBP Land Cover Legend
• 4.4 USGS Land Use/Land Cover System Legend
• 4.5 Simple Biosphere Model Legend
• 4.6 Simple Biosphere 2 Model Legend
• 4.7 Biosphere-Atmosphere Transfer Scheme Legend
• 4.8 Vegetation Lifeforms Legend
• 5.0 Information on Version 2.0
• 6.0 References

The South America land cover data base is one portion of a global land cover characteristics data base that was developed on a continent-by-continent basis. All continents in the global data base share the same map projections (Interrupted Goode Homolosine and Lambert Azimuthal Equal Area), have 1-km nominal spatial resolution, and are based on 1-km AVHRR data spanning April 1992 through March 1993 (Loveland and others, 1999). Each continental data base has unique elements that are based on the salient geographic aspects of the specific continent. In addition, a core set of derived thematic maps produced through the aggregation of seasonal land cover regions are included in each continental data base. These are:

• Global Ecosystems (Olson, 1994a, 1994b)
• IGBP Land Cover Classification (Belward, 1996)
• U.S. Geological Survey Land Use/Land Cover System (Anderson and others, 1976)
• Simple Biosphere Model (Sellers and others, 1986)
• Simple Biosphere 2 Model (Sellers and others, 1996)
• Biosphere-Atmosphere Transfer Scheme (Dickinson and others, 1986)
• Vegetation Lifeforms (Running and others, 1994)

For a description of the methodology for the global data base, see the global readme file found under the LP DAAC home page (http://LPDAAC.usgs.gov/glcc/glcc.php).

The South America land cover characteristics data are in a flat, headerless raster format. The pixel values correspond to class numbers defined in the appropriate land cover classification scheme legend. Data are distributed as compressed and uncompressed single-band images. The files can be obtained either by anonymous file transfer protocol (ftp) or downloaded from the LP Distributed Active Archive Center (DAAC) World Wide Web site: (http://LPDAAC.usgs.gov/glcc/sa_int.php). The instructions for accessing these files are contained in the following two sections.

1.1 Anonymous FTP for PC or UNIX Users

1. Contact the FTP server. At your command prompt, use the command: ftp edcftp.cr.usgs.gov
2. Login as an anonymous user and use your email address as the password.
3. Change to the directory pub/data/glcc
4. Change to the South America subdirectory, sa
5. Change to the directory for the projection of interest (i.e., goode for Interrupted Goode Homolosine projection or lambert for Lambert Azimuthal Equal Area Projection).
6. Locate the file of interest (a complete file listing is located in section 3.0 of this readme). The image files were compressed using the GNU 'gzip' software and can be identified by the ".gz" file extension. These files must be uncompressed before use with the 'gunzip' utility, a part of the 'gzip' software. Directions for acquiring the gzip software from GNU can be found on the WWW on the GNU home page (http://www.gnu.org/). If you do not have access to gzip, the ftp server can uncompress the files as they are retrieved.
7. To FTP compressed files:
• Use the FTP command 'binary' to transfer image data.
• Use the FTP command 'get' followed by the file name. Include the .gz extension to receive as a compressed file (e.g., get sabats2_0.img.gz).
8. To FTP uncompressed files:
• Use the FTP command 'binary' to transfer image data.
• Use the FTP command 'get' followed by the file name without the .gz extension to transfer an uncompressed file (e.g., get sabats2_0.img). Please note that the uncompressed files are typically many times larger than the compressed versions and therefore will take much longer to transmit.

From the South America Land Cover page, select either data in Interrupted Goode Homolosine projection or data in Lambert Azimuthal Equal Area projection. The selection will link to a page that contains links to all documentation files and the image files (both compressed and uncompressed). NOTE: World Wide Web browsers can vary in how the files will be downloaded. On PCs, some browsers will allow a user to interactively select the location where the file will be saved and to edit the file name. However, on certain browsers files may be automatically downloaded to a default storage location on the local system.

1. Select either button, compressed or uncompressed, for the file of interest.
2. A pop-up screen may appear, showing information on the download procedure. At this point, choose the directory in which to save the file.
3. For compressed files, the .gz extension must be added to the filename before downloading. However, if the browser will not accept adding an extension, continue with the download, and then rename the file with the .gz extension when the download is complete.
4. For uncompressed files, leave the .gz extension off. If a pop-up screen shows the filename with a .gz extension either edit the filename, or proceed with the download and rename the file without the extension after the procedure is complete.

The South America data base is available in two different map projections: the Interrupted Goode Homolosine and the Lambert Azimuthal Equal Area (see Steinwand, 1994 , and Steinwand and others, 1995, for a complete description of these projections).

2.1 Interrupted Goode Homolosine Projection Parameters

The data dimensions of the Interrupted Goode Homolosine projection for the South America land cover characteristics data set are 8,016 lines (rows) and 5,632 samples (columns) resulting in a data set size of approximately 45 megabytes for 8-bit (byte) images. The following is a summary of the map projection parameters used for this projection:

Projection Type: Interrupted Goode Homolosine

Units of measure: meters

Pixel Size: 1000 meters

Radius of sphere: 6370997 m

XY corner coordinates (center of pixel) in projection units (meters):

Lower left: ( -9276000, -6385000)



Upper left: ( -9276000, 1630000)

Upper right: ( -3645000, 1630000)

Lower right: ( -3645000, -6385000)

The data dimensions of the Lambert Azimuthal Equal Area projection for the South America land cover characteristics data set are 8,000 lines (rows) and 6,000 samples (columns) resulting in a data set size of approximately 48 megabytes for 8-bit (byte) images. The following is a summary of the map projection parameters used for this projection:

Projection Type: Lambert Azimuthal Equal Area

Units of Measure: meters

Pixel Size: 1000 meters

Radius of sphere: 6370997 m

Longitude of origin: 60 00 00 W

Latitude of origin: 15 00 00 S

False easting: 0.0

False northing: 0.0

XY corner coordinates (center of pixel) in projection units (meters):

Lower left: ( -3000000, -4899000)



Upper left: ( -3000000, 3100000)

Upper right: ( 2999000, 3100000)

Lower right: ( 2999000, -4899000)

4.0 Derived Data Sets

4.1 South America Seasonal Land Cover Regions Legend

South America, v. 2.0

4.2 Global Ecosystems Legend

4.3 IGBP Land Cover Legend

4.4 USGS Land Use/Land Cover System Legend (Modified Level 2)

4.5 Simple Biosphere Model Legend

Value	Description
1	Evergreen Broadleaf Trees
2	Broadleaf Deciduous Trees
3	Deciduous and Evergreen Trees
4	Evergreen Needleleaf Trees
5	Deciduous Needleleaf Trees
6	Ground Cover with Trees and Shrubs
7	Groundcover Only
8	Broadleaf Shrubs with Perennial Ground Cover
9	Broadleaf Shrubs with Bare Soil
10	Groundcover with Dwarf Trees and Shrubs
11	Bare Soil
12	Agriculture or C3 Grassland
17	Persistent Wetland
18	Dry Coastal Complexes
19	Water
20	Ice Cap and Glacier

4.6 Simple Biosphere 2 Model Legend

4.7 Biosphere-Atmosphere Transfer Scheme Legend

4.8 Running Vegetation Lifeforms Legend

5.0 Information on Version 2.0

The first version of the global land cover database was completed and released to the public in November, 1997.  We applied the feedback we received from the users of this database (Brown and others, 1999) and broad lessons learned from the validation exercise of the IGBP DISCover land cover data (Scepan, 1999; Muchoney and others, 1999) to the development of this revised version of the database.  Version 2.0 of the South America land cover database contains updated land cover classes and revised labels.  Users can identify the revised images and documentation by observing  "2.0" or "2_0" in file names (for example, saigbp2_0g.img).  Links to the previous version (1.2) of the land cover database are found on glcc_version1.php. Please send any questions to our Land Cover Applications Center ( lcac@usgs.gov ).

We have provided the specific changes to the South America land cover database in the ascii text file, salcdbtab2_0.txt.   The file contains 42 fields (columns) and the data are of variable width with tabs as field delimiters.  The first record of the file corresponds to the field titles.  The following records in the file are indexed by the second field to the South America Seasonal Land Cover Regions (Version 2.0).  The field entitled "Update" contains information specific to the action taken in order to revise the particular Seasonal Land Cover Region (for example, the class was split, merged with another region, or relabeled).

6.0 References

Anderson, J.R., Hardy, E.E., Roach J.T., and Witmer R.E., 1976, A land use and land cover classification system for use with remote sensor data: U.S. Geological Survey Professional Paper 964, 28 p.

Belward, A.S., ed., 1996, The IGBP-DIS global 1 km land cover data set (DISCover)-proposal and implementation plans: IGBP-DIS Working Paper No. 13, Toulouse, France, 61 p.

Brown, J.F., Loveland, T.R., Ohlen, D.O., Zhu, Z., 1999. The Global Land-Cover Characteristics Database: The Users' Perspective. Photogrammetric Engineering and Remote Sensing , v. 65, no. 9, p. 1,069-1,074.

Dickinson, R.E., Henderson-Sellers, A., Kennedy, P.J., and Wilson, M.F., 1986, Biosphere-atmosphere transfer scheme (BATS) for the NCAR community climate model: NCAR Technical Note NCAR/TN275+STR, Boulder, CO. 69 p.

Loveland, T.R., Zhu, Z., Ohlen, D.O., Brown, J.F., Reed, B.C., and Yang, L., 1999. An Analysis of the IGBP Global Land-Cover Characterization Process. Photogrammetric Engineering and Remote Sensing , v. 65, no. 9, p. 1021-1032.

Muchoney, D., Strahler, A., Hodges, J., and LoCastro, J., 1999. The IGBP DISCover Confidence Sites and the System for Terrestrial Ecosystem Parameterization: Tools for Validating Global Land-Cover Data. Photogrammetric Engineering and Remote Sensing , v. 65, no. 9, p. 1061-1067.

Olson, J.S., 1994a, Global ecosystem framework-definitions: USGS EROS Data Center Internal Report, Sioux Falls, SD, 37 p.

_____ 1994b, Global ecosystem framework-translation strategy: USGS EROS Data Center Internal Report, Sioux Falls, SD, 39 p.

Running, S.W., Loveland, T.R., and Pierce, L.L., 1994. A Vegetation Classification Logic Based on Remote Sensing for Use in Global Biogeochemical Models, Ambio , v. 23, n. 1, p. 77-81.

Scepan, J., 1999. Thematic Validation of High-Resolution Global Land-Cover Data Sets, Photogrammetric Engineering and Remote Sensing , v. 65, no. 9, p. 1051-1060.

Sellers, P.J., Mintz, Y., Sud, Y.C., and Dalcher A., 1986, A simple biosphere model (SiB) for use within general circulation models: Journal of Atmospheric Science , v. 43, p. 505-531.

Sellers, P.J., Randall, D.A., Collatz, G.J., Berry, J.A., Field, C.B., Dazlich, D.A., Zhang, C., Collelo, G.D., and Bounoua, L., 1996, A revised land surface parameterization (SiB2) for atmospheric GCMs - Part I-model formulation: Journal of Climate , v. 9, p. 676-705.

Steinwand, D.R., 1994, Mapping raster imagery to the Interrupted Goode Homolosine projection: International Journal of Remote Sensing , v. 15, no. 17, p. 3,463-3,472.

Steinwand, D.R., Hutchinson, J.A., and Snyder, J.P. ,1995, Map projections for global and continental data sets and an analysis of pixel distortion caused by reprojection: Photogrammetric Engineering and Remote Sensing , v. 61, p. 1,487-1,497.