SAFARI 2000 Land Cover from AVHRR, 1-km, 1994 (Hansen et al.)
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Abstract
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The data set consists of a southern Africa subset of the 1km Global Land Cover
Data Set Derived from AVHRR developed at the Laboratory for Global Remote
Sensing Studies (LGRSS) at the University of Maryland.
Over the past several years, researchers have increasingly turned to remotely
sensed data to improve the accuracy of data sets that describe the geographic
distribution of land cover at regional and global scales. To develop improved
methodologies for global land cover classifications as well as to provide global
land cover products for immediate use in global change research, researchers at
the Laboratory for Global Remote Sensing Studies (LGRSS) at the University of
Maryland, have employed the NASA/NOAA Pathfinder Land (PAL) data set with a
spatial resolution of 1km. This data set has a record length of 14 years (1981-
1994), providing the ability to test the stability of classification algorithms.
Furthermore, this data set includes red, infrared, and thermal bands in addition
to the Normalized Difference Vegetation Index (NDVI). Inclusion of these
additional bands improves discrimination between cover types. The project aim is
to develop and validate global land cover data sets and to develop advanced
methodologies for more realistically describing the vegetative land surface
based on satellite data.
The 1km global land cover product was created from 1992-93 LAC AVHRR data. 41
metrics were developed to describe global vegetation phenology and these data
were used to make the 1km land cover map. The final product contains 13 land
cover classes.
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Background Information
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Investigators:
Matthew Hansen
mhansen@Glue.umd.edu
Ruth DeFries
rd63@umail.umd.edu
John Townshend
jt59@umail.umd.edu
Rob Sohlberg
rsohlber@geog.umd.edu
Project: SAFARI 2000
Data Set Title: SAFARI 2000 Land Cover from AVHRR, 1-km, 1994 (Hansen et al.)
Site: Southern Africa
Westernmost Longitude: 5
Easternmost Longitude: 60
Northernmost Latitude: 5
Southernmost Latitude: -35
Data Set Citation:
Hansen, M. C., R. S. DeFries, J. R. G. Townshend, and R. Sohlberg. 2002.
SAFARI 2000 Land Cover from AVHRR, 1-km, 1994 (Hansen et al.). Available
on-line [http://www.daac.ornl.gov/] from Oak Ridge National Laboratory
Distributed Active Archive Center, Oak Ridge, Tennessee, U.S.A.
Southern African subset extractions of this data were performed by Oak Ridge
National Laboratory:
ORNL DAAC User Services Office
ornldaac@ornl.gov
+1 (423) 241-3952
Original Data Set Link: http://glcf.umiacs.umd.edu/
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ASCII File Information
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The data file is in ASCII Grid format for ArcInfo. More information on
this format is contained within the README file (link provided above). The
file contains a single ASCII array with integer values. Data values range
rom 0 to 13. Coordinates listed below are in decimal degrees.
Rows 4800
Columns 6600
UpLeftX 5
UpLeftY 5
LoRightX 60
LoRightY -35
cellsize 0.0083333
Projection geographic
The ASCII file consists of header information containing a set of keywords,
followed by cell values in row-major order. The file format is:
{NCOLS xxx}
{NROWS xxx}
{XLLCORNER xxx}
{YLLCORNER xxx}
{CELLSIZE xxx}
{NODATA_VALUE xxx}
row 1
row 2
.
.
.
row n
where xxx is a number, and the keyword NODATA_VALUE is optional and defaults
to -9999. Row 1 of the data is at the top of the grid, row 2 is just
under row 1 and so on. The end of each row of data from the grid is
terminated with a carriage return in the file.
To import this file into ArcInfo use the following command at an ARC prompt:
ASCIIGRID {in_ascii_file} {out_grid} {INT | FLOAT}
Arguments:
{in_ascii_file} - the ASCII file to be converted.
{out_grid} - the name of the grid to be created.
{INT | FLOAT} - the data type of the output grid.
INT - an integer grid will be created.
FLOAT - a floating-point grid will be created.
Binary File Information
-----------------------
The ASCII data file has also been converted into a binary image file that
can be viewed in any standard image viewing package. The file is a single-byte
image, no header, 6600 columns by 4800 rows. Missing data (ASCII -9999)
have been converted to the maximum value of 255.
File Compression Information
---------------------------
For this archive, the data files have been compressed with the MS
Windows-standard Zip compression scheme. These files were compressed using
Aladdin's DropZip on a Macintosh. DropZip uses the Lempel-Ziv algorithm,
also used in Zip and PKZIP programs. The compressed files
may be uncompressed using PKZIP (with the -expand option) on MS Windows
and UNIX, or with StuffIt Expander on the Mac OS. You can get newer versions
from the PKZIP Web site at http://www.pkware.com/shareware/.
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Procedure Used to Create the Southern Africa Subset
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The original data were obtained and read following the directions in the
original documentation. The data were converted to ASCII arrays and then
imported into ArcInfo using the ASCIIGRID command.
Using GRID (a raster- or cell-based geoprocessing toolbox that is
integrated with ArcInfo) the SETWINDOW command was used to define the
subarea of interest. This subarea was defined by identifying the bounding
coordinates as follows:
x_min 5 y_min -35 x_max 60 y_max 5
The "snap_grid" option of the SETWINDOW command was used. This snaps the
lower-left corner of the specified window to the lower-left corner
of the nearest cell in the snap_grid and snaps the upper-right corner of
the specified window to the upper-right corner of the nearest cell in the
snap_grid. In this case the snap_grid is an original data grid. The
purpose of this is to ensure the proper registration of the newly set
analysis window. The command format used is as follows:
SETWINDOW x_min y_min x_max y_max original_grid
Once the window was set, creating the new grid was simply a matter of
setting the new subset grid equal to the original grid.
subset_grid = original_grid
An ASCII array was created from the new subset grid using the GRID command
GRIDASCII.
file.dat = GRIDASCII(subset_grid)
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Legend & Additional Sources of Information
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The following legend is used in the original data set:
0 Water (and Goode's interrupted space)
1 Evergreen needleleaf forest
2 Evergreen broadleaf forest
3 Deciduous needleleaf forest
4 Deciduous broadleaf forest
5 Mixed forest
6 Woodland
7 Wooded grassland
8 Closed shrubland
9 Open shrubland
10 Grassland
11 Cropland
12 Bare ground
13 Urban and built-up
Although not all of these categories may be represented in the subset of
the data, the original legend has been retained. The original data and
documentation can be obtained from the Global Land Cover Facility at the
University of Maryland: http://glcf.umiacs.umd.edu/