SAFARI 2000 Land Cover from AVHRR, 1-km, 1994 (Hansen et al.) ---------------------------------------------- Abstract -------- 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. ========================================================================= Background Information ---------------------- 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/ ========================================================================= ASCII File Information ---------------------- 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/. ========================================================================= Procedure Used to Create the Southern Africa Subset --------------------------------------------------- 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) ========================================================================= Legend & Additional Sources of Information ------------------------------------------ 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/