SAFARI 2000 Land Cover from AVHRR, 1-Deg, 1994 (Defries and Townshend) -------------------------------------------------- Abstract -------- The University of Maryland (UMD) 1 degree Global Land Cover product was produced by researchers at the Laboratory for Global Remote Sensing Studies (LGRSS) at UMD. The product is based on Advanced Very High Resolution adiometer (AVHRR) maximum, monthly composites for 1987 of Normalized Difference Vegetation Index (NDVI) values at approximately 8 km resolution, averaged to one by one degree resolution. This coarse resolution data set was used as the basis for a supervised classification of eleven cover types that broadly represent the major biomes of the world. Because of missing values at high latitudes, the Pathfinder AVHRR data set for 1987 for summer monthly NDVI and red reflectance values were used to distinguish the following cover types: tundra, high latitude deciduous forest and woodland, coniferous evergreen forest and woodland. The complete 1 degree global land cover product is available for download from the Global Land Cover Facility (GLCF) web site at http://glcf.umiacs.umd.edu/. The data are available as a global coverage in both binary and ASCII format. Additional information and references on this data set can be found at the GLCF web site as well as at the LGRSS web site (link provided at the GLCF web site ) and in the readme files found along with the data. ========================================================================= Background Information ---------------------- Investigators: Ruth DeFries rd63@umail.umd.edu John Townshend jt59@umail.umd.edu Project: SAFARI 2000 Data Set Title: SAFARI 2000 Land Cover from AVHRR, 1-Deg, 1994 (Defries and Townshend) Site: Southern Africa Westernmost Longitude: 5 Easternmost Longitude: 60 Northernmost Latitude: 5 Southernmost Latitude: -35 Start Date: 1987-01-01 End_Date: 1987-12-31 Data Set Citation: DeFries, R. S., and J. R. G. Townshend. 2002. SAFARI 2000 Land Cover from AVHRR, 1-Deg, 1994 (Defries and Townshend). 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 (865) 241-3952 Original Data Set Link: http://glcf.umiacs.umd.edu/ ========================================================================= ASCII File Information ---------------------- The data file is in ASCII Grid format for ArcInfo. The file contains a single ASCII array with integer values. Data values range from 0 to 12. Coordinates listed below are in decimal degrees. Rows 40 Columns 55 UpLeftX 5 UpLeftY 5 LoRightX 60 LoRightY -35 cellsize 1 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, 55 columns by 40 rows. Missing data (ASCII -9999) have been converted to the maximum value of 255. ========================================================================= 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 legends are used in the original data for the categorical fields: 0 Water 1 Broadleaf evergreen forest 2 Coniferous evergreen forest and woodland 3 High latitude deciduous forest and woodland 4 Tundra 5 Mixed coniferous forest and woodland 6 Wooded grassland 7 Grassland 8 Bare ground 9 Shrubs and bare ground 10 Cultivated crops 11 Broadleaf deciduous forest and woodland 12 Data unavailable 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/