Earth Systems Data GLOBAL CHANGE DATA BASE Volume 2 ----------------------------------------------------------------------- Experimental Calibrated Global Vegetation Index from NOAA's Advanced Very High Resolution Radiometer (AVHRR) ----------------------------------------------------------------------- In Two Versions: 1. Biweekly values, Mercator projection, April 1985 - December 1991. By Kevin Gallo, NOAA/NESDIS Office of Research and Applications. 2. Monthly values, Latitude-Longitude (Plate Carree) projection, April 1985 - December 1990. Temporally aggregated and reprojected by the U. S. Geological Survey, re-registered for integrated application in the Global Change Data Base at NOAA's National Geophysical Data Center. ----------------------------------------------------------------------- Prepared and Distributed for Integrated Use by: National Oceanic and Atmospheric Administration National Environmental Satellite, Data, and Information Service National Geophysical Data Center 325 Broadway Boulder, Colorado 80303 June 1992 Trademark Acknowledgements Mention of a company or product in this document does not imply endorsement by the U.S. Government, any of its agencies, or any sponsor or participant of the project for which this document was produced. Use for publicity or advertis- ing purposes of information from this publication concerning proprietary products or the tests of such products is not authorized. In lieu of placing a trademark symbol in every occurrence of a trademarked  373  name, we state that we are using the names only in an editorial fashion with no intention of infringement of the trademark. Trademark information indicat- ed below was derived from various sources and are accurate to the best of our knowledge. IBM is a registered trademark and PS/2, VGA, and AT are trademarks of Interna- tional Business Machines Corporation. IDRISI is a registered trademark of Clark University. PKZIP and PKUNZIP are registered trademarks of Pkware Inc. Disclaimer While every effort has been made to ensure that the information contained in this manual is correct, NOAA cannot assume liability for any damages caused by errors or omissions, or as a result of the failure of the data or software accompanying this manual to function as described. NOAA makes no warranty, expressed or implied, nor does the fact of distribution constitute a warranty. The user must be cautious when using these data and computer programs. Be- cause this is an experimental database constructed from existing sources, errors and omissions can be expected. The user is referred to peer evalua- tions of this product and subsequent revisions for determination of suitabili- ty for any given purpose. Request We invite anyone to propose corrections or offer additions to the Global Change Data Base, or documentation. We do not guarantee that we will be able to incorporate these changes. Nevertheless, we will endeavor to make correc- tions where appropriate, and where our resources allow us to do so. Comments may be addressed to: National Geophysical Data Center, Mail Code E/GC1 325 Broadway, Boulder, Colorado 80303, USA Tel: (303) 497-6125 FAX: (303) 497-6513 TABLE OF CONTENTS Line Number in this ASCII Text File INTRODUCTION...............................................................1 DATA SET DESCRIPTION Data on \2BIWEEK Directory..........................................144 3n3  Data on \1MONTH Directory...........................................244 Directory Structure of this CD-ROM..................................340 DEVELOPMENT OF THESE DATA................................................492 HOW TO USE THIS DISC?....................................................641 SOFTWARE GUIDE...........................................................697 Introductory Notes..................................................725 Software Installation...............................................753 Further Notes.......................................................803 FILE NAMING CONVENTIONS..................................................849 APPENDIX A. SELECTED REFERENCES ON THE NORMALIZED DIFFERENCE VEGETATION INDEX FROM AVHRR..............................................971 APPENDIX B. REPRINT OF A PAPER That Describes the Global Change Data Base's Objectives & Development....................................1155 INTRODUCTION This disc contains two versions of an experimental Global Vegetation Index (EGVI), developed by Kevin Gallo of the Land Sciences Branch, Office of Re- search and Applications, National Environmental Satellite, Data, and Informa- tion Service (NESDIS), National Oceanic and Atmospheric Administration (NOAA): Directory \1MONTH contains monthly maxima derived from Gallo's original bi- weekly EGVI computations. The data were reprojected by the U. S. Geological Survey's Earth Resources Observation Systems Data Center to a to a 10-minute latitude-longitude projection. They were then re-registered at the NOAA National Geophysical Data Center to be compatible with the Global Change Data Base*. Directory \2BIWEEK contains the original biweekly EGVIs produced by Gallo. These data are provided as a source for analysis at higher temporal resolu- tion. As they are in the Mercator projection, they are not immediately com- patible with the Global Change Data Base. In addition, they have not received all of the GCDB's quality control analysis*. The Satellite Data Services Division of NOAA/NESDIS' National Climatic Data  33  Center distributes operational Global Vegetation Indices (GVIs) derived from the Advanced Very High Resolution Radiometer of the NOAA Polar Orbiting Envi- ronmental Satellites. These data may be obtained from: National Oceanic and Atmospheric Administration National Environmental Satellite, Data, and Information Service National Climatic Data Center Satellite Data Services Division (E/CC6) Princeton Executive Square, Suite 100 Washington, DC 20233 Telephone: (301) 763-8400 The experimental GVI (EGVI) contained on this CD-ROM was developed by Kevin Gallo to investigate the benefits of using pre-launch calibration information to improve the usefulness of the GVI. In addition, screening the data for low sun angle and clouds makes the data more useful for some studies (though use of such masked data in spatial analysis systems should be conducted with care). In its support of pluralistic research and education on the Earth's environ- ment, the National Geophysical Data Center distributes other experimental monthly compilations of NOAA's operational GVI data. Additional versions of GVI are planned. ------------------------------- FOOTNOTE TO LINES 156 AND 162 *. Additional information is contained in the hardcopy documentation, and in the README file in this directory. -------------------------------- Why so many versions of a data set? Simply put, single versions of a data set were traditional in past years. Such information was often compiled by a committee of experts into a single map on the topic. Such maps often involved considerable (sometimes heated!) discussion on how to represent the subject. Legend categories were the result of (often agonizing) compromise that didn't completely satisfy any member of the authorship committee, but which were generally recognized as valuable instigators of scientific discussion, analysis, and interpretation. With digital representations, we can now offer several different attempts to represent the same subject. Each representation provides a basis for discus- sion, analysis, and learning. The original NOAA operational GVI, available from the Satellite Data Services Division (see above) have been widely accessible, and have been used by many scientists for qualitative and semi-quantitative analysis. One of the major comments of the operational GVI is that the lack of calibration of the data degrades the use of the GVI. Different AVHRR instruments on different satel- lites have different calibration characteristics, and these characteristics change with time. The Gallo EGVI was an investigation into the use of simple pre-launch calibra- tion information in producing a GVI. This documentation contains a selected bibliography to discussions on the Normalized Difference Vegetation Index. These references cover a variety of approaches to the data, their computation, characteristics, and use. We encourage you to compare this experimental GVI with others that may be available to you, from the Global Change Data Base or from other sources. We believe that increased investigation of alternative methods of producing and analyzing the GVI will result in an improved understanding of the value of such data. Such study will also lead to increased understanding of global environmental phenomena, including those of global change. NOTE: If you plan to use these data with the Global Change Data Base, you should use the data contained in the \1MONTH directory. If you plan to use Kevin Gallo's original data, or if you want to try differ- ent ways to integrate these original data into the Global Change Data Base, use the data contained in the \2BIWEEK directory. DATA SET DESCRIPTION: DATA ON \2BIWEEK DIRECTORY TITLE: EXPERIMENTAL CALIBRATED BIWEEKLY GLOBAL VEGETATION INDEX FROM NOAA's AVHRR PRINCIPAL INVESTIGATOR: Kevin Gallo, NOAA/NESDIS Office of Research and Applications DATE: 1992 PRIMARY LITERATURE REFERENCE: Enclosed "Development of These Data" CONTRIBUTOR: Kevin Gallo, NOAA/NESDIS/ORA DATA DISTRIBUTION CENTER: NOAA National Geophysical Data Center NOAA National Climatic Data Center USGS EROS Data Center GEOGRAPHIC SAMPLING: 1038 lines x 2048 columns, nominal 10.4 minute grid at the Equator COVERAGE: 75oN - 55oS Latitude, 180oW - 180oE Longitude PROJECTION: Mercator TIME SAMPLING: Biweekly averages from weekly temporal composites of AVHRR data PERIOD: April 1985 - December 1991 LINEAGE: (1) AVHRR (Global Mercator Weekly GVI Channel Data) NOAA/NESDIS/National Climatic Data Center Satellite Data Services Division (E/CC6) Princeton Executive Square, Suite 100 Washington, DC 20233 (301) 763-8400 (2) Reprocessed into calibrated biweekly averages by Kevin P. Gallo NOAA/NESDIS/ORA, EROS Data Center, Sioux Falls, SD (now at NOAA/NESDIS/National Climatic Data Center Federal Building Asheville, NC 28801 (704) 259-0878) DATA SET IDENTIFICATION: Gallo, Kevin P., 1992. Experimental biweekly global normalized differ ence vegetation index from NOAA's AVHRR (April 1985-December 1991). Digital Data. NOAA National Geophysical Data Center, Boulder, Colorado. ADDITIONAL REFERENCES: See reference list in this documentation =========================================================== EXPERIMENTAL CALIBRATED BIWEEKLY GLOBAL VEGETATION INDEX FROM NOAA's AVHRR DATA FILE STRUCTURE FILE NAMES: BW8516 - BW9152 (175 files) IMAGE TITLES: KGALLO BIWEEKLY GVI : weeks X-Y : Mercator Projection (where X and Y are the period of data sampling in the image) STRUCTURE: Data type : byte File type : binary Rows : 1038 Columns : 2048 Minimum : 0 Maximum : varies by image Flag values : 0, 1, 2 (see Product Description) Cell size : nominal 10.4 min. at Equator Data units : calibrated unitless NDVI Projection : Mercator ================================================================== DATA SET DESCRIPTION DATA ON \1MONTH DIRECTORY TITLE: EXPERIMENTAL CALIBRATED MONTHLY GLOBAL VEGETATION INDEX FROM NOAA's AVHRR REPROCESSED FROM KEVIN GALLO'S BIWEEKLY GVIs PRINCIPAL INVESTIGATOR: Kevin Gallo, NOAA/NESDIS Office of Research and Applications (with subsequent reprocessing) DATE: 1992 PRIMARY LITERATURE REFERENCE: Enclosed "Development of These Data" CONTRIBUTOR: (Original Data Set): Kevin Gallo, NOAA/NESDIS/ORA (Reprocessing to Monthly Lat/Lon) Douglas Binnie, USGS EROS Data Center DATA DISTRIBUTION CENTER: NOAA National Geophysical Data Center NOAA National Climatic Data Center USGS EROS Data Center GEOGRAPHIC SAMPLING: 10-min grid, resampled from 1038x2048 Mercator grid COVERAGE: 75oN - 55oS Latitude, 180oW - 180oE Longitude for actual data coverage. PROJECTION: Latitude/Longitude TIME SAMPLING: Monthly maxima from Biweekly averages of PERIOD: April 1985 - December 1991 LINEAGE: (1) AVHRR (Global Mercator Weekly GVI Channel Data) NOAA/NESDIS/National Climatic Data Center Satellite Data Services Division (E/CC6) Princeton Executive Square, Suite 100 Washington, DC 20233 (301) 763-8400 (2) Reprocessed into calibrated biweekly averages by Kevin P. Gallo NOAA/NESDIS/ORA, EROS Data Center, Sioux Falls, SD (now at NOAA/NESDIS/National Climatic Data Center Federal Building Asheville, NC 28801 (704) 259-0878) (3) Reprocessed into monthly maxima (of biweekly values) in latitude-longitude (Plate Carree) projection by Douglas R. Binnie U. S. Geological Survey EROS Data Center Sioux Falls, SD 57198 (605) 594-6142 (4) Re-registered to fit the Global Change Data Base by NOAA/NGDC (303) 497-6125 DATA SET IDENTIFICATION: Gallo, Kevin P., 1992. Experimental biweekly global normalized differ- ence vegetation index from NOAA's AVHRR (April 1985-December 1991). Digital Data. NOAA National Geophysical Data Center, Boulder, Colorado. ADDITIONAL REFERENCES: See reference list in this documentation =========================================================== EXPERIMENTAL CALIBRATED MONTHLY GLOBAL VEGETATION INDEX FROM NOAA's AVHRR DATA FILE STRUCTURE FILE NAMES: M8504 - M9012 (69 FILES) IMAGE TITLES: KGALLO MONTHLY GVI : (APRIL 1985-DECEMBER 1990) STRUCTURE: Data type : byte File type : binary Rows : 1080 Columns : 2160 Minimum : 0 Maximum : varies by image Flag values : 0, 1, 2 (see Product Description) Cell size : 10 minute Data units : calibrated unitless NDVI Projection : Latitude/Longitude ===================================================================== DIRECTORY STRUCTURE ON THIS CD-ROM |-------1MONTH.........monthly lat-lon EGVIs | |-ADOC.........see note 1 | |-BDOC.........see note 2 | |-CDOC.........see note 3 | |-CELL.........gridded data | |-CELLHD3......see note 4 | |-CELLHD4......see note 5 | |-------2BIWEEK........biweekly Mercator EGVIs |-ADOC.........see note 3 |-BDOC.........see note 2 |-CELL.........gridded data |-CELLHD.......see note 6 Note 1: The subdirectories ADOC contain standard IDRISI 3 header (.doc) files. The maximum and minimum data value is that for the actual data set. You may want to use this directory for most applications, if using IDRISI. Note 2: The subdirectories BDOC contain standard IDRISI 3 header (.doc) files. The maximum and minimum data values in each file are those for the entire data base, and are the same for each file. Use this directory to get consistent displays with autoscaling in IDRISI's COLOR a command. Note 3: The subdirectory CDOC contains standard IDRISI 4 header (.doc) files. You may want to use these if you are running IDRISI 4. There is no CDOC subdirectory in directory \2BIWEEK, as IDRISI 4 requires projection labeling, yet cannot yet handle the Mercator projection at the time of writing this documentation. Note 4: The subdirectory CELLHD3 contains GRASS3 header (cellhd) files. These use a column-row pixel referencing scheme. Note 5: The subdirectory CELLHD4 contains GRASS4 header (cellhd) files. These use a Latitude-Longitude projection, with coordinates in degrees and minutes. Note 6: The subdirectory CELLHD contains GRASS3-style header (cellhd) files. GRASS does not yet handle Mercator projections, so both GRASS3 and GRASS4 must use column-row pixel referencing. ========================================================================== DEVELOPMENT OF THESE DATA Experimental Biweekly Global Normalized Difference Vegetation Index from NOAA's AVHRR by Kevin P. Gallo National Oceanic and Atmospheric Administration National Environmental Satellite, Data, and Information Service Office of Research and Applications An experimental normalized difference vegetation index (NDVI) was developed and produced during 1988 through 1990, from weekly visible and near-infrared AVHRR channel data available from NOAA's Global Vegetation Index product (Kidwell, 1991) distributed by the: NOAA/NESDIS National Climatic Data Center Satellite Data Services Division (E/CC6) Princeton Executive Square, Suite 100 Washington, DC 20233 Tel: 301-763-8400 FAX: 301-763-8443. NOAA's Mercator-projected product was utilized. The data are produced for the region between 75 degrees North latitude and 55 degrees South latitude. Data resolution in the Mercator projection varies from 19.6 km pixel size at the equator to 15 km at 40 degrees (North or South). The reflectance values of the visible and near-IR data were computed from pre-launch calibration coeffi- cients. The NDVI was computed as: NDVI = (nearIR - visible)/(nearIR + visible). The calibrated visible and near-IR data, and solar zenith angle data included on the NOAA GVI product were utilized to screen the NDVI data for cloud con- tamination and low (less than 15 degrees) solar elevation at the time of data acquisition. Data were also screened for data drops. Two successive weeks of the screened NDVI data were then composited based on the maximum NDVI value of the two weeks. The biweekly data were processed for April 1985 through 1989. The start date of the biweekly composite intervals was 099 (9 April) in 1985. The start dates in 1986, 1987, 1988 were 001 (1 January). Processing inter- vals changed in 1988 on 11 April to a Monday through Sunday weekly cycle. The start date in 1989 was 002 (2 January), in 1990 was 001 (1 January) and for 1991 was 007 (7 January). The biweekly NDVI data have been scaled to a byte format from the original ND value (a real number with a range from -1.00 to 1.00) computed with the above equation, using the following conversion: byteNDVI = (realNDVI x 100) + 100. Thus, a byte NDVI value of 151 in the data set is equivalent to a computed real NDVI value of 0.51. A byte NDVI value of 100 is equivalent to a computed real NDVI of 0.0. Data tagged by the cloud, data drop, or solar elevation algorithms will include values of 0 through 2, respectively. There are 26 biweekly files for each year but 1985, for which the 19 last biweekly periods have files. The file naming convention is YYWW. For exam- ple, file 8602 covers the first two weeks of 1986. Each biweekly data file includes 1038 lines and 2048 samples of data in a byte format. The value that occupies the first line and sample of each file is located at 75 N and 180 W. A FORTRAN program that computes line and sample location from latitude and longitude is appended to this documentation. Additional information about the data is found in the README file in the \2BIWEEK directory; more information can be provided by Kevin Gallo, NOAA/NESDIS, National Climatic Data Center, Federal Building, Asheville, North Carolina 28801, (704) 259-0878, or from the NGDC Global Change Data Base help line at (303) 497-6125. Reference: Kidwell, K. B., (ed), 1991. Global Vegetation Index Users Guide. NOAA/NESDIS, NCDC Satellite Data Services Division (E/CC6), Princeton Execu- tive Square, Suite 100, Washington, DC 20233. =========================================================== Experimental Monthly Global Normalized Difference Vegetation Index from NOAA's AVHRR Computed From Kevin Gallo's Biweekly Experimental GVIs These monthly maxima of the Gallo experimental GVIs were computed by taking the maximum values of biweekly GVIs for each month, then reprojecting the original mercator-projected data to latitude-longitude projection. The compi- lation was produced from Gallo's data by the U. S. Geological Survey's EROS Data Center. Inspection of these data at NOAA's National Geophysical Data Center showed that the computed data were internally consistent to within one grid cell (the locational accuracy usually attributed to the NOAA Polar Orbiting Environmen- tal Satellites that house the AVHRR sensor). However, the data were misregis- tered to the Earth by 1 grid cell (to the south). After colleague confirma- tion by the GeoSPACE project at the Canada Centre for Remote Sensing, the data were reregistered at NGDC by removing the northernmost row of data, and in- serting a new row at the bottom of each data file. As these rows contained no GVI values, no data were lost in the process. The README file in the \1MONTH directory contains more information on these data. PROGRAM TO CONVERT LATITUDES & LONGITUDES INTO MERCATOR MI AND MJ COORDINATES c----------------------------------------------------------- c c This program converts input latitude and longitude values into c MI and MJ coordinates associated with the NOAA Vegetation c Index products with Mercator projections described in Kidwell c (1991). Written by K. P. Gallo, 11 November 1987. c c------------------------------------------------------------- c c real lat,long, mi, mj, in,lonc, x,y,i,j,reply data pi/3.1416/,in/2500.0/,lonc/o.o/ c 20 write(*,701) ' enter latitude and longitude in degrees ' read(*,'(BN,2f7.2)') lat, long write(*,*) lat, long 701 format(a\) c x=in*(long-lonc)/360. y=in*(lat)/360. c i=x+1250.0 j=-y+522.0 c mi=(i*.8192) mj=662.0-(log(tan(-0.00126*j+1.44136))*325.95) c write(*,2001) ' mj(line#)= ', mj, ' mi(sample#)= ', mi 2001 format(a,f7.2,a,f7.2) write(*,701) ' enter a "1" for another lat,long ' read(*,'(BN,f1.0)') reply if (reply .eq. 1) goto 20 end ========================================================================== HOW TO USE THIS DISC? If you use GRASS-GIS (public domain, designed for environmental analysis), you will want to build a link between a fully constructed global data base on your hard disk and the CELL and CELLHD subdirectories in either the /1MONTH or /2BIWEEK directories on the CD-ROM. These subdirectories fulfill their func- tions in the GRASS directory structure. You may also want to link to a work- ing directory for global data to which you could add GRASS support files, etc. When using GRASS, you will have to use entire filenames (e.g. BW8516.IMG). For example, you might want to use (subject to the style of YOUR UNIX): ln /usr/mnt/1month/cellhd3 /usr/grass3/data/global/username/cellhd ln /usr/mnt/1month/cell /usr/grass3/data/global/username/cell to run GRASS3 where: /usr/mnt is the address of your CD-ROM drive /usr/grass3/data/global is the location of your global data base on your hard disk username is your user name If you are running GRASS4, you may wish to link the CELLHD4 instead of the CELLHD3 subdirectory in the /1MONTH directory. GRASS4 hand- les latitude- longitude data better than GRASS3. The CELLHD4 subdirectory contains appro- priate CELLHD files for this. As GRASS handles data in the Mercator projec- tion only as unprojected images, the CELLHD3 directory in /2BIWEEK should be used by all GRASS users of these data. If you are using IDRISI (a low-cost educational GIS), you may want to run pro- grams MONTH or BIWEEK in the enclosed software (see the Software Guide in this manual). Otherwise use the DOS APPEND command to append the ADOC or BDOC subdirectory with the CELL subdirectory of the \1MONTH or the \2BIWEEK direc- tories on this CD-ROM. The standard unheadded binary raster grid of each data file consists of a string of 8-bit byte values (0-255), placed adjacent to each other in the file. This format can be ingested into virtually any image processing system, or any geographic information system that can handle raster data. Most such systems have routines for ingesting these data. For example, in ERDASTM you download the file from your CD-ROM drive, run FIXHEAD and BSTATS, using the appropriate number of lines and samples, as described in the Product Descrip- tion, and shown in the CELL, ADOC and BDOC subdirectories and README file for each version of the data. Some software (such as GRASS and IDRISI) will allow you to work with the data on the CD-ROM. Some other software, especially that which embeds a header into the data file, will require you to copy the data to a hard disk, and work from there. If you have any problems in using this CD-ROM, if you have any comments, or if you have any data that you would like distributed in this way, please contact NGDC at (303) 497-6125. =========================================================================== SOFTWARE GUIDE Browse and Visualization Modules for the Experimental Global Vegetation Index CD-ROM WELCOME! This disk contains a subset of the IDRISI Geographic Analysis System that has been specially prepared by Clark University and NOAA/NGDC for use with the Global Change Data Base. Almost any 8088-, 80286-, 80386 or compatible person- al computer running IBM-DOS or compatible operating system, with EGA, VGA, or 8514A compatible graphics should be able to run these modules. In the future, NGDC plans to have browse and visualization software that runs on IBM-PC/MS-Windows, Macintosh, and UNIX/X-Windows environments. This soft- ware will be a generalized version of NGDC's GeoVu software (which had its debut in NGDC's CD-ROM on Geophysics of North America). This software can be run from the floppy diskette, but more practically should be copied to a separate CDROMVU (or other) program directory. You can then run the program named MENU. The MENU lists modules contained on this disk, which can then be run interactively by typing in the appropriate command name. To get the MENU, type MENU or HELP. __________________________________! INTRODUCTORY NOTES: 1. These modules were developed especially for NGDC's Global Change Data Base, and for a cooperative project called the "Global Ecosystems Database Project" between NOAA/NGDC and the U. S. Environmental Protection Agency. Some parts of the software refer specifically to this cooperative project, which, within NGDC, is a part of the overall Global Change Database Program. 2. This disk contains two versions of the COLOR program -- one simply called COLOR for EGA and VGA systems and a second called COLOR85 for 8514/A or XGA systems (the EGA/VGA version can also be used with 8514/A and XGA systems). If you are working with an 8514/A or XGA or compatible graphics adaptor, please be sure that your applications interface (AI) driver has been loaded. If the module fails to produce a graphic image, it indicates that the AI driver is not memory resident. 3. You should have your CD-ROM drive installed, following the manufacturer's instructions. This browse and visualization assumes that your CD-ROM drive is called drive F: If your CD-ROM drive carries a different designation, pay attention to installation step 3 below. 4. If you already own a copy of IDRISI, these modules may be copied to your IDRISI directory. However, since many of these modules are revisions that have been specially prepared for this project, you should keep these separate from the general-release versions. This is why we suggest a separate CDROMVU subdirectory. SOFTWARE INSTALLATION: 1. The software can be run from floppy disk, but is better run from a hard disk. If you have a hard disk, copy the entire contents of the enclosed floppy diskette to a new directory in your hard disk. The software is setup to run in a CDROMVU directory on your C: hard disk. 2. If you install the software in a different environment, you should run the ENVIRON command (just go to the directory containing the software and type ENVIRON and hit the ENTER key). Follow the instructions on the screen to interactively change the drive and directory settings appropriately. 3. The BIWEEK and MONTH programs are set up to run successfully if your CD- ROM drive is your "F:" drive. If your CD-ROM drive has a different designa- tion, you will need to perform a simple editing of these programs. To do so: --Run your favorite word processor or text editor in ASCII mode. (That is, DON'T have it change these files into the proprietary format of your word processor, but retain the ASCII file structure.) --Have it read the file BIWEEK.BAT, which contains a single line: APPEND f:\1biweek\adoc;f:\2biweek\cell --Change this line to read: APPEND DLETTER:\1biweek\adoc;DLETTER:\1biweek\cell Where DLETTER is the letter designation of your CD-ROM drive (perhaps D, E, F, L, or M?). --Save this file. --Repeat this process for the MONTH.BAT file. 4. Run ENVIRON to assign the drive and path of the directory on your hard disk that will be your working directory. This may be the destination direc- tory to which you will write subscenes extracted from the global GVI files (if you want to work regionally rather than globally, you can do this with the enclosed utility SUBSET). Or, this may be the directory to which you might want to write output files (such as ASCII versions of the images by using the enclosed utility CONVERT). You may use the default setting (C:\CDROMVU) if you want your output data in the same location as the software; but this may not be convenient for you in the long run. You may want to use different working directories for different purposes. This is easy to do with ENVIRON. FURTHER NOTES: 5. Note that we are including several .pal files. These are alternate color palettes for displaying images with COLOR or COLOR85. You may want to experi- ment with these, especially those with GVI in their names. To use such a palette, note when COLOR or COLOR85 ask you for your choice of palette. Answer with the number for "user-defined palette." Then, when prompted, give the name of the palette (which you must know beforehand by using DOS commands). 6. All IDRISI modules belong to Clark University and are protected by Inter- national Copyright Law. The modules distributed here have been made available to the EPA and NOAA/NGDC through a special Memorandum of Understanding with Clark University. They may not be distributed independently of the Global Change Data Base. For further information about the Global Change Data Base, please contact : NOAA/NGDC 325 Broadway Boulder, CO 80303 USA Tel : (303) 497-6125 FAX : (303) 497-6125 Attn: David Schoolcraft For further information about the IDRISI Geographic Analysis System please contact : IDRISI Project Clark University 950 Main St. Worcester MA 01610 USA Tel : (508) 793-7526 FAX : (508) 793-8881 ============================================================================ FILE NAMING CONVENTIONS DATES OF IMAGERY ON THIS CD-ROM \BIWEEK directory The biweekly files are listed below. Each file is prefixed with a "BW," followed by the year (e.g. "86"), followed by a number corresponding to the sampling period of the image. Each image file has a ".IMG" extension. For example, file "BW8516.IMG" is a file covering the biweekly period of weeks 15-16 of 1985. When using the software enclosed with this CD-ROM, you should not enter the ".IMG" when specifying an image to be displayed or processed. The ".IMG" is assumed by the software. With GRASS-GIS, use the entire file name (e.g. "BW8516.IMG") With other software, use the file naming conventions specified in your user's manual. With some software you may have to modify the naming conventions of these files, which would mean that they may not work from the CD-ROM. BW8516.IMG BW8544.IMG BW8620.IMG BW8648.IMG BW8518.IMG BW8546.IMG BW8622.IMG BW8650.IMG BW8520.IMG BW8548.IMG BW8624.IMG BW8652.IMG BW8522.IMG BW8550.IMG BW8626.IMG BW8702.IMG BW8524.IMG BW8552.IMG BW8628.IMG BW8704.IMG BW8526.IMG BW8602.IMG BW8630.IMG BW8706.IMG BW8528.IMG BW8604.IMG BW8632.IMG BW8708.IMG BW8530.IMG BW8606.IMG BW8634.IMG BW8710.IMG BW8532.IMG BW8608.IMG BW8636.IMG BW8712.IMG BW8534.IMG BW8610.IMG BW8638.IMG BW8714.IMG BW8536.IMG BW8612.IMG BW8640.IMG BW8716.IMG BW8538.IMG BW8614.IMG BW8642.IMG BW8718.IMG BW8540.IMG BW8616.IMG BW8644.IMG BW8720.IMG BW8542.IMG BW8618.IMG BW8646.IMG BW8722.IMG ==================================================== BW8724.IMG BW8848.IMG BW8920.IMG BW9144.IMG BW8726.IMG BW8850.IMG BW8922.IMG BW9146.IMG BW8728.IMG BW8852.IMG BW8924.IMG BW9148.IMG BW8730.IMG BW8902.IMG BW8926.IMG BW9150.IMG BW8732.IMG BW8904.IMG BW8928.IMG BW9152.IMG BW8734.IMG BW8906.IMG BW8930.IMG BW9102.IMG BW8736.IMG BW8908.IMG BW8932.IMG BW9104.IMG BW8738.IMG BW8910.IMG BW8934.IMG BW9106.IMG BW8740.IMG BW8912.IMG BW8936.IMG BW9108.IMG BW8742.IMG BW8914.IMG BW8938.IMG BW9110.IMG BW8744.IMG BW8916.IMG BW8940.IMG BW9112.IMG BW8746.IMG BW8918.IMG BW8942.IMG BW9114.IMG BW8748.IMG BW8920.IMG BW8944.IMG BW9116.IMG BW8750.IMG BW8922.IMG BW8946.IMG BW9118.IMG BW8752.IMG BW8924.IMG BW8948.IMG BW9120.IMG BW8802.IMG BW8926.IMG BW8950.IMG BW9122.IMG BW8804.IMG BW8928.IMG BW8952.IMG BW9124.IMG BW8806.IMG BW8930.IMG BW9102.IMG BW9126.IMG BW8808.IMG BW8932.IMG BW9104.IMG BW9128.IMG BW8810.IMG BW8934.IMG BW9106.IMG BW9130.IMG BW8812.IMG BW8936.IMG BW9108.IMG BW9132.IMG BW8814.IMG BW8938.IMG BW9110.IMG BW9134.IMG BW8816.IMG BW8940.IMG BW9112.IMG BW9136.IMG BW8818.IMG BW8942.IMG BW9114.IMG BW9138.IMG BW8820.IMG BW8944.IMG BW9116.IMG BW9140.IMG BW8822.IMG BW8946.IMG BW9118.IMG BW9142.IMG BW8824.IMG BW8948.IMG BW9120.IMG BW9144.IMG BW8826.IMG BW8950.IMG BW9122.IMG BW9146.IMG BW8828.IMG BW8952.IMG BW9124.IMG BW9148.IMG BW8830.IMG BW8902.IMG BW9126.IMG BW9150.IMG BW8832.IMG BW8904.IMG BW9128.IMG BW9152.IMG BW8834.IMG BW8906.IMG BW9130.IMG BW8836.IMG BW8908.IMG BW9132.IMG BW8838.IMG BW8910.IMG BW9134.IMG BW8840.IMG BW8912.IMG BW9136.IMG BW8842.IMG BW8914.IMG BW9138.IMG BW8844.IMG BW8916.IMG BW9140.IMG BW8846.IMG BW8918.IMG BW9142.IMG ============================================================================ \MONTH directory The monthly files are listed below. Naming is as described above, in a month- ly context. Thus, file "M8512.IMG" is a file covering the biweekly period of month 12 (e.g. September) of 1985. Remember that the GVIs are actually an average of two biweekly values, so that our sample image would be an average of BW8550.IMG and BW8552.IMG. When using the software enclosed with this CD-ROM, you should not enter the ".IMG" when specifying an image to be displayed or processed. The ".IMG" is assumed by the software. With GRASS-GIS, use the entire file name (e.g. "M8512.IMG") With other software, use the file naming conventions specified in your user's manual. With some software you may have to modify the naming conventions of these files, which would mean that they may not work from the CD-ROM. M8504.IMG M8609.IMG M8802.IMG M8907.IMG M8505.IMG M8610.IMG M8803.IMG M8908.IMG M8506.IMG M8611.IMG M8804.IMG M8909.IMG M8507.IMG M8612.IMG M8805.IMG M8910.IMG M8508.IMG M8701.IMG M8806.IMG M8911.IMG M8509.IMG M8702.IMG M8807.IMG M8912.IMG M8510.IMG M8703.IMG M8808.IMG M9001.IMG M8511.IMG M8704.IMG M8809.IMG M9002.IMG M8512.IMG M8705.IMG M8810.IMG M9003.IMG M8601.IMG M8706.IMG M8811.IMG M9004.IMG M8602.IMG M8707.IMG M8812.IMG M9005.IMG M8603.IMG M8708.IMG M8901.IMG M9006.IMG M8604.IMG M8709.IMG M8902.IMG M9007.IMG M8605.IMG M8710.IMG M8903.IMG M9008.IMG M8606.IMG M8711.IMG M8904.IMG M9009.IMG M8607.IMG M8712.IMG M8905.IMG M9010.IMG M8608.IMG M8801.IMG M8906.IMG M9011.IMG M9012.IMG ===================================================================== APPENDIX A. SELECTED REFERENCES ON THE NORMALIZED DIFFERENCE VEGETATION INDEX FROM AVHRR Asrar, G., Fuchs, M., Kanemasu, E. T., and Hatfield, J. L., 1984. Estimating absorbed photosynthetic radiation and leaf area index from spectral reflec- tions in wheat. Agron. J., V. 76, pp. 300-306. Bartlett, D. S., Hardisky, M. A., Johnson, R. W., Gross, M. F., Klemes, V., and Hartman J. M., 1988. Continental scale variability in vegetation reflect- ance and its relationship to canopy morphology. International Journal of Remote Sensing, 9(7), 1223-1241. Choudhury, B. J., and Golus, R. E., 1988. Estimating soil wetness using satel- lite data. International Journal of Remote Sensing, 9(7), 1251-1257. Cihlar, J., St.-Laurent, L., and Dyer, J. A., 1991. Relation between the normalized difference vegetation index and ecological variables. Remote Sensing of Environment, v. 35, pp. 279-298. Clark, David M., Hastings, David A., and Kineman, John J., 1991. Global data- bases and their implications for GIS. IN Maguire, David J., Goodchild, Mi- chael F., and Rhind, David W., eds., Geographical Information Systems: Over- view, Principles and Applications. Burnt Mill, Essex, United Kingdom, Long- man. V.2, pp. 217-231. Di, L., 1991. Regional-scale soil moisture monitoring using NOAA/ AVHRR data, Ph.D. Dissertation, Department of Geography, University of Nebraska-Lincoln. Di, L., Rundquist, D., and Han, L., 1991. A mathematical model for predicting NDVI using daily precipitation. Manuscript to be published. Gallo, K. P., 1990. Satellite-derived vegetation indices: a new climatic variable? Proceedings, Symposium on global change systems, February 5-9, 1990, Anaheim, California. American Meteorological Society, Boston, Massachu- setts. Gallo, K. P., and Heddinghaus, T. R., 1989. The use of satellite-derived vegetation indices as indicators of climatic variability. Proceedings, Sixth Conference on Applied Climatology, March 7-10, 1989, Charleston, SD. American Meteorological Society, Boston, Massachusetts. Gallo, K. P., and Brown, J. F., 1990. Satellite-derived indices for monitor- ing global phytoclimatology. Proceedings, 10th International Geoscience and Remote Sensing Symposium, May, 1990, Washington, DC. Gallo, K. P., and Brown, J. F., 1990. Evaluation of data reduction and com- positing of the NOAA Global Vegetation Index product: A cast study. Washing- ton, DC, NOAA Technical Report NESDIS 54, Gallo, K. P., Daughtry, C. S. T., and Bauer, M. E., 1985. Spectral estimation of absorbed photosynthetically active radiation in corn canopies. Remote Sensing of Environment, V. 17, pp. 221-232. Gatlin, J. A., Sullivan R. J., Tucker, C. J., 1984. Consideration of and improvements to large-scale vegetation monitoring. IEEE Trans. on Geoscience and Remote Sensing, GE-22(6), 496-502. Goward, S. N. 1990. Experiences and perspective in compiling long-term remote sensing data sets on landscapes and biospheric processes. GeoJournal, v. 20, pp. 107-114. Goward, S. N., Dye, D., Kerber, A., and Kalb, V., 1987. Comparison of North and South American biomass from AVHRR observations. Geocarto International, v. 1, pp. 27-39. Goward, S. N., Markham, B., Dye, D. G., Dulaney, W., and Yang, J., 1991. Derivation of quantitative normalized difference vegetation index measurements from Advanced Very High Resolution Radiometer observations. Remote Sensing of Environment, v. 35, pp. 257-277. Gray, T. I., and McCrary, D. G., 1981. The environmental vegetation index, a tool potentially useful for arid land management. AgRISTAR Report No. EW-N-1- 04076, Johnson Space Center, Houston, Texas 17132. Gutman, G. Garik, 1991. Vegetation indices from AVHRR: An update and future prospects. Remote Sensing of Environment, v. 35, pp. 121-136. Gutman, G. Garik, and Liu, William T., 1991. Bio-climates of South America as derived from multispectral AVHRR data. 24th International Symposium on Remote Sensing of Environment, Rio de Janeiro, May 1991. Ann Arbor, Michigan, Envi- ronmental Research Institute of Michigan. Summary pp. 19-20; Proceedings in press. Hastings, David A., and Di, Liping, 1992. Modeling Global Change Phenomena with GIs using the Global Change Data Base. Remote Sensing of Environment. (in press) Hastings, David A. Kineman, John J., Davis, W. M., and Clark, David M., 1989. Two unsung problems with GIS: Getting a system that does what you need, and working with non-ideal data. Proceedings of the 2nd National Conference on Geographic Information Systems, U. S. Professional Development Corporation and Government Computer News. Hastings, David A., Kineman, John J., and Clark, David D., 1991. Development and application of global data bases: considerable progress, but more collab- oration needed. International Journal of Geographical Information Systems, v. 5., pp. 137-146. Kidwell, Katherine B., 1990. Global Vegetation Index Users Guide. National Oceanic and Atmospheric Administration, National Climatic Data Center, Satel- lite Data Services Division, Washington DC 20233. 45 pp. Kineman, J. J., Clark, D. M., and Croze, H., 1990. Data integration and mo- delling for global change: An international experiment. Proceedings of the International Conference and Workshop on Global Natural Resource Monitoring and Assessments: Preparing for the 21st Century (Venice, Italy, 24-30 Septem- ber 1989). Bethesda, Maryland, American Society of Photogrammetry and Remote Sensing, Vol. 2, pp. 660-669 Kogan, F., 1991. Remote sensing of weather impacts on vegetation in non- homogeneous areas. International Journal of Remote Sensing, in press. Koomanoff, V. A., 1989. Analysis of global vegetation patterns: a comparison between remotely sensed data and a conventional map. Biogeography Research Series, Report #890201, Department of Geography, University of Maryland, College Park, 111 pp. Ohring, G., Gallo, K., Gruber, A., Planet, W., Stowe, L., and Tarpley, J. D., 1989. Climate and global change: Characteristics of NOAA satellite data. EOS Transactions of the American Geophysical Union, v. 70, pp. 889,891,894,901. Peters, A. J., 1989. Coarse Spatial Resolution Satellite Remote Sensing of Drought Conditions in Nebraska: 1985-1988. PhD Dissertation, Department of Geography, University of Nebraska, Lincoln. Rosenthal, W. D., Blanchard, B. J., and Blanchard, A. J., 1985. Visible/ infrared/microwave agriculture classification, biomass, and plant height algorithms. IEEE Trans. on Geoscience and Remote Sensing, GE-23(2), 84-90. Rouse, J. W., Hass, R. H., Schell, J. A., Deering, D. W., and Harlan, J. C., 1974. Monitoring the Vernal Advancement and Retrogradation (Greenwave Effect) of Natural Vegetation. National Aeronautics and Space Administration Goddard Space Flight Center Final Report. Greenbelt, Maryland. Tarpley, J. D., Schneider, S. R., and Money, R. L., 1984. Global vegetation indices from the NOAA-7 meteorological satellite. Journal of Climate and Applied Meteorology. v. 23, pp. 491-494. Townshend, J. R. G., Goff, T. E., and Tucker, C. J., 1985. Multitemporal dimensionality of images of normalized difference vegetation index at conti- nental scales. IEEE Transactions, Geoscience and Remote Sensing, v. 23, pp. 888-895. Townshend, J. R. G., Justice, C. O., and Kalb, V. T., 1987. Characterization and classification of South American land cover types using satellite data. International Journal of Remote Sensing. v. 8, pp. 1189-1207. Townshend, J. R. G., Justice, C. O., Choudhury, B. J., Tucker, C. J., Kalb, V. T., and Goff, T. E., 1989. A comparison of SMMR and AVHRR data for continen- tal land cover characterization. International Journal of Remote Sensing. v. 10, pp. 1633-1642. Tucker, C. J., and T. A. Gatlin, 1984. Monitoring vegetation in the Nile Delta with NOAA-6 and NOAA-7 AVHRR imagery. Photogrammetric Engineering and Remote Sensing, 50(1), 53-61. Tucker, C. J., Hielkema, J. U., and Roffey, j., 1985a. The potential of satel- lite remote sensing of ecological conditions for survey and forecasting desert-locust activity. International Journal of Remote Sensing, 6(1), 127- 138. Tucker, C. J., Vanpraet, C. L., Sharman., M. J., and van Ittersum, G., 1985b. Satellite remote sensing of total herbaceous biomass production in the Senega- lese Sahel: 1980-1984. Remote Sensing of Environment, 17, 233-249. Tucker, C. J., Fung, I. Y., Keeling, C. D., and Gammon, R. H., 1986. Rela- tionship between atmospheric CO2 variations and a satellite-derived vegetation index. Nature, v. 319, pp. 195-199. Walsh, S. J., 1987. Comparison of NOAA-AVHRR data to meteorological drought indices. Photogrammetric Engineering and Remote Sensing, 53(8), 1069-1074. Wiegand, C. L., Gerbermann, A. H., Gallo, K. P., Blad, B. L., and Dusek, D., 1990. Multisite analyses of spectral-biophysical data for corn. Remote Sensing of Environment, v. 33, pp. 1-16. =================================================================== ABSTRACT/RESUME The Global Change Data Base results from a cooperatively developed method of publishing peer-reviewed data designed for integrated multivariate spatial analysis. The GCDB with accompanying documentation and access software lie entirely within the public domain. They are designed (1) to further re- search, education, and overall awareness of the global en-vironment; (2) to provide beneficial feedback to enable the authors to enhance their own re- search and data development, and (3) to provide a mechanism for scientists to share and receive credit for the intellectual content and expression of their experimental designs, analyses, interpretations, and models of the global environment. The prime medium for distribution is CD-ROM, though educational data sets are being prepared for distribution on floppy diskette, ac-companied by a manual of exercises. Keywords: global change, data, integration, research, education, outreach. 1. INTRODUCTION An increasing number of laboratories and individual scientists have been developing digital spatial data sets to describe va-rious aspects of the global environment. A cooperative effort to integrate many of these data has been progressing for seve-ral years, and is about to reach fruition in the first public release of NGDC's Global Change Data Base (GCDB; Ref. 1) The integration effort has involved careful inspection of data for spatial registration, consistency between documentation and data content, and appro- priateness for multivariate anal-ysis and modeling in image processing, spa- tial statistics, and geographic information systems. To reduce the hugeness of the task of data integration, the GCDB is starting with only global data sets. However, as it advances, interest is increasing for continental- and regional-scale data bases. Selected continental-scale data sets may soon be added to the GCDB. This task may appear menial and boring. Indeed, there is much tedious inspec- tion of data and documentation. However, the Global Change Data Base is also an experiment in inte-grating and improving access to individual data sets. When combined, these data constitute a fascinating view of (1) the Earth as a system, and (2) how we conduct science. 2. OBJECTIVES Why the need for an integrated data base? Many people currently concentrating on one or two parameters that attempt to describe certain aspects of the global environment would like access to more data to work with. However, assembling such data is tedious. Even without rigorously assuring cartograph- ic fidelity and scientific accountability, simply finding and acquiring such data can be time consuming. A single reference data set can thus be acquired more easily, can be used as a focal point for comparisons, etc. In addition, resources needed to improve the geographic fit and scientific usefulness of such data can be expended once to a certain level, leaving the scientist or educator to move beyond this point in whatever way s/he chooses. 2.1 Integration of Data for Multivariate Analysis Many existing environmental data sets are produced individ-ually by special- ists in a particular field. These data are often designed for a special application, with compromises that may not be optimal for other users. The data may also have characteristics (cartographic projection, legend catego- ries, simplifications) that may make them difficult to use as part of an integrated multivariate study. For the past few years, the USA's National Oceanic and Atmospheric Administra- tion has placed emphasis on "Earth Systems" approaches to science. NOAA's National Geophys-ical Data Center, and its co-located World Data Center - A, Boulder (Colorado) Centers, is emphasizing the development of integrated data sets for studying the Earth as a system. Many studies of the global environment emphasize only one or two types of data. For example, detailed studies are sometimes made of several weeks or years of Global Vegetation Index (GVI) from NOAA's Advanced Very High Resolu- tion Radiometer (AVHRR), perhaps comparing such data with past and predicted crop yields in the African Sahel. Such data can be internally consistent but slightly misregistered to the globe (as one can still identify the West Afri- can coastline, for example, in the imagery) without significantly affecting some studies. However, (1) attempts to relate the GVI to vegetation type, soils, or topography (Ref. 2), or (2) attempts to "validate" production and processing of satellite imagery by comparisons with ground-based data can be greatly assisted if the separate data sets are integrated into an overall data base designed for multivariate application. The Global Change Data Base is an attempt to address this issue of integration and quality assessment. Hastings and others (Ref. 3), Clark and others (Ref. 4) and Kineman and others (Ref. 5), discuss some aspects of this activity in greater detail than the present review. 2.2 Peer-Reviewed "Publication" of Data Fundamental analytical scientific data are often more widely used, with hun- dreds of users, than are typical scientific research papers, which may typi- cally be cited by a few other authors. Yet financial/logistical/moral support for sharing data is often low. Why this problem, and how to solve it? The design and execution of experiments that collect data have frequently been recognized as intellectual contributions only if the scientists involved produced publishable findings from the data. As such, sufficient acknowledge- ment may not have previously been made for the development of certain pioneer- ing attempts to characterize the global environment. Faced with such a reception, scientists have sometimes pre-ferred to publish findings from data, rather than to thoroughly document the data and share them with the public. On the other hand, there has been considerable discussion on what constitutes scientifically valid data on the environment. How are such data certified? Should committees be formed to validate such data? One alternative is to adapt certain existing traditions of peer review and hardcopy publication to digital data. The Global Change Data Base is an attempt to support such thinking. In the GCDB, individual data sets are considered as authored chapters in a symposium volume. Each chapter consists of data, basic documentation on file format and data development, written discussion of scientific applications of the data (often with technical writings on research findings), guidelines on characteristics of the data that might affect new applications, and a bibliog- raphy of other writings on the data. The data are reviewed in-house at NOAA/NGDC for geographic registration, accuracy and appropriateness of categorization, completeness of documentation, and ability to be used with other data in the GCDB. Many data sets have ini- tial problems in these areas that may not have affected their original appli- cations but which, if not corrected, would cause trouble when used in the multivariate spatial GCDB. Data and documentation are corrected and/or en- hanced for some data sets, to improve their integration into the GCDB. The data are then sent to several experts for their comments. These comments are used to further edit the data and documentation, for increased value to users of the data base. The Global Change Data Base has had two forms of peer review to date: (1) The first prototype, an integrated collection of data for Africa, was reviewed by scientists on six continents, as part of the International Geosphere-Biosphere Programme's (IGBP's) Global Change Database Project, Pilot Project for Africa. (2) A CD-ROM containing about 500 megabytes of integrated global data was reviewed by about 150 Beta testers as part of a cooperative Global Ecosystems Database project with the USA's Environmental Protection Agency. Both of these data sets are described in more detail below. Peer-reviewed data should not be considered as perfect, especially in these early stages of describing the global environment. However, they have been determined by reviewers to be appropriate for cautious study by scientists who will read the documentation and use care and judgment in their use of the data. As in hardcopy information, we can expect people to find enhancements, alternatives, or additions to the GCDB. We invite anyone to contact us with comments, suggestions, or data for subsequent releases of the data base. 2.3 Public-Domain, Accessible The Global Change Data Base, as is the case for all data distributed by NOAA/NGDC, is completely in the public domain. There is no restriction on the distribution or use of the GCDB, other than common courtesy that the authors and publisher be referenced in any subsequent use. NOAA/NGDC distributes its data in all appropriate media. Magnetic tape, floppy diskette, and Compact Disc Read-Only Memory (CD-ROM) have been used for data contained in the GCDB. Because of the large volumes of data already in the GCDB, CD-ROM is considered the most practical (and most economical) form of distribution for the data. On-line distribution of scientific data has been attractive to many scien- tists. With such systems, a person can collect large quantities of data for the cost of a connection to a communications network, or for telephone hookup via modem to the source of the data. Currently, there are no plans for such distribution for the Global Change Data Base other than during the review process. NOAA/NGDC must recover its costs of managing the data, which places a nominal charge on data (with numerous exceptions, such as for contributors of data, researchers or cooperators in various programs, who get the data at no charge). Also, the size of the Global Change Data Base (over a gigabyte and growing rapidly) makes even high speed network transmission nontrivial. Also, networks are not yet fully accountable for data quality, which makes them inappropriate media for operationally transmitting the reviewed GCDB. The data are accompanied by software that helps the user to browse through and visualize the GCDB and select appropriate data for use. The current version of the software is being enhanced and implemented for multiple platforms, such as IBM-compatible computers, Apple Macintosh computers, and UNIX workstations. The data are immediately compatible with several spatial analysis systems including GRASS-GIS (for UNIX; Ref. 6) and IDRISI (for DOS; Ref. 7). The data have been easily imported into several more spatial analysis systems. 2.4 Support Research, Education, Awareness The previous paragraph notes that one can view several aspects of the global environment with the data and accompanying software. However, the main pur- poses of the data base are better served by using software of the user's choice for research, education, or public awareness. For this purpose, the data are stored in a latitude-longitude unheaded grid format (with associated vector data) compatible with ingest into many software systems. In-house analysis at NOAA/NGDC has already begun to produce some research results (Ref. 2). Several Beta testers have commented on their research activities with the data. The IGBP's Global Change Database Project has been conducted with the United Nations Environment Programme (UNEP) the United Nations Institute for Training and Research (UNITAR), la Sociedad de Especialistas Latinoamericanos en Per- cepcion Remota (SELPER, the Society of Latin American Remote Sensing Special- ists) and other organizations to conduct training and awareness workshops in Africa and Latin America. One result of this activity is a training manual designed for self-instruction and exploration of the global environment, focusing on Africa as an example. NOAA/NGDC has enhanced the IGBP training workbook for publication in 1992. There are plans for additional educational materials, such as narrated 35mm slide sets, and perhaps a video. We invite commercial publishers to produce value-added products from these materials, after the GCDB materials are publicly released. 2.5 Provide Feedback to Authors of Data Sets The integration, in-house and external testing, and development of educational materials is done in consultation with the authors of the data, even if the data have already been placed into the public domain. No data set enters the GCDB without explicit approval of its author(s) for its unrestricted distribu- tion. We want the GCDB to be as useful to the authors of the data as to customers of the data base. The authors are the ultimate authorities on their work. The authors are also pioneers in attempting to describe the environment. However, the GCDB offers feedback on attempts to integrate and use these with other data, and in documenting the data for users outside the authors' own special- ties. Our analysis of spatial and thematic representations, intercomparison, and other research on the integration of the data offers back to the original authors information that might stimulate improvements in (and new applications of) the data. 2.6 A Is this a Prototype for Future Distribution Of Digital Data? Are there elements of the GCDB that can be useful to others in the business of distributing data? We hope so. Indeed, interchange of ideas between NOAA/- NGDC and the Canada Centre for Remote Sensing has been fruitful for the GCDB, as well as helping in the development of CCRS' Global Change Encyclopedia for the International Space Year. Just as the hardcopy publishing industry has many producers of a wide variety of publications, we can predict many different sources of digital data in the future. We hope that some of these sources will improve the technology of data quality, integration, review/certification, documentation, and accessi- bility. 3. CURRENT STATUS OF THE GCDB 3.1 Current Contents The current version of the GCDB includes the following data: topography (Ref. 8) distribution of population (Ref. 8) surface water coverage (Ref. 8) terrain characteristics (Ref. 8) topography/bathymetry (Ref. 9) vegetation (Ref. 10) land use (Ref. 10) seasonal albedo (Ref. 10) ecosystems (Refs. 11, 12) soils (Refs. 13, 14) life zones (Ref. 15) temperature & precipitation (Refs. 16-18) vector base map linework (Ref. 19) vegetation index from AVHRR (Refs 20-22) Many other data sets are at various stages of incorporation into the data base. Such data will be added to the GCDB as they proceed through acquisi- tion, discussion with authors, ingest, quality control, integration, Beta Test peer review, and documentation. Although all of these data sets are global, we plan to incorporate significant regional data sets at a later date: for example, where such data might help stimulate demand for (and later supply of) global versions of such data. 3.2 Availability The Beta Test of the IGBP Pilot (Diskette) Project for Africa was conducted in 1990-1991. The Beta Test of the NOAA/EPA Global Ecosystems Database was conducted, in conjunction with the USA's Environmental Protection Agency, in 1991-1992. The revised GCDB Pilot Project for Africa is slated for distribution on floppy diskette, with documentation and training workbook, sometime in 1992. Anno- tated slide sets may follow later in 1992. We invite anyone interested in producing educational materials for schools (or any other audience) to contact NGDC in Boulder or NOAA's Educational Affairs Division in Washington, DC. The full Global Change Data Base is slated for publication on a series of CD- ROMs, also in 1992. A new Beta Test of proposed additions to the GCDB will also be conducted in 1992. We invite anyone interested in the data to contact NOAA/NGDC for an informa- tion packet, and to be placed on the mailing list for the data. We also encourage authors of global or regional data sets to contact us if they are interested in the concept of peer-reviewed publication of such data. 4. REFERENCES 1. NOAA, 1992. Global Change Data Base, Digital Data with Documentation. Boulder, Colorado, National Oceanic and Atmospheric Administration, National Geophysical Data Center. 2. Hastings, David A., and Liping Di, 1992. Modeling of global change phenom- ena with GIS using the Global Change Data Base. Remote Sensing of Environ- ment, in review. 3. Hastings, David A., Kineman, John J., and Clark, David D., 1991. Develop- ment and application of global data bases: considerable progress, but more collaboration needed. International Journal of Geographical Information Systems, v. 5., pp. 137-146. 4. Clark, David M., Hastings, David A., and Kineman, John J., 1991. Global databases and their implications for GIS. IN Maguire, David J., Goodchild, Michael F., and Rhind, David W., eds., Geographical Information Systems: Overview, Principles and Applications. Burnt Mill, Essex, United Kingdom, Longman. V.2, pp. 217-231. 5. Kineman, J. J., Clark, D. M., and Croze, H., 1990. Data integration and modelling for global change: An international experiment. Proceedings of the International Conference and Workshop on Global Natural Resource Monitoring and Assessments: Preparing for the 21st Century (Venice, Italy, 24-30 Septem- ber 1989). Bethesda, Maryland, American Society of Photogrammetry and Remote Sensing, Vol. 2, pp. 660-669 6. CERL, 1991. The Geographic Resources Analysis Support System (GRASS-GIS), Version 4.0. U. S. Army Corps of Engineers, Construction Engineering Research Laboratory, Champaign, Illinois. 7. Eastman, J. R., 1990. Idrisi, A Grid-Based Geographic Analysis System: User's Manual for Release 3.2. Worcester, Massachusetts, Clark University Graduate School of Geography, 364 pp. 8. Cuming, Michael J., and Hawkins, Barbara A., 1981. TERDAT: The FNOC System for Terrain Data Extraction and Processing. Technical Report MII Project M-254 (2nd Edition), Montgomery, California, U. S. Navy Fleet Numeri- cal Oceanography Center. 9. Edwards, Margaret Helen, 1986. Digital Image Processing of Local and Global Bathymetric Data. Masters Thesis, Department of Earth and Planetary Sciences. Washington University, St. Louis, Missouri, 106 pp. 10. Matthews, E., 1984. Vegetation, Land-use, and Seasonal Albedo Data Sets: Documentation of Archived Data Tape. National Aeronautics and Space Adminis- tration Technical Memorandum 86-107, 12 pp. 11. Olson, J. S., 1982. Earth's vegetation and atmospheric carbon dioxide. IN Clark, W. C., ed., Carbon Dioxide Review: 1982. Oxford, Oxford University Press, pp. 388-398. 12. Olson, J. S., 1990. World Ecosystems (WE 1.4): Digital Data. Boulder, Colorado, NOAA National Geophysical Data Center. 13. Staub, Brad and Rosenzweig, Cynthia, 1987. Global digital data sets of soil type, soil texture, surface slope, and other properties. National Aero- nautics and Space Administration Technical Memorandum 100685. 14. Witt, R., ed., 1984. Global FAO Soil Unite (2-min grid): Digital Data. Carouge, Switzerland, United Nations Environment Programme, Global Resources Information Database. 15. Leemans, Rik, 1990. Possible Changes in Natural Vegetation Patterns due to a Global Warming. Laxenburg, Austria, International Institute for Applied Systems Analysis, Working Paper WP-90-08, 13 pp. 16. Legates, David R., and Willmott, Cort J., 1989. Mean seasonal and spatial variability in gauge-corrected, global precipitation. International Journal of Climatology, v. 10, pp. 111-127. 17. Legates, David R., and Willmott, Cort J., 1990. Mean seasonal and spatial variability in global surface air temperature. Theoretical and Applied Clima- tology, v. 41, pp. 11-21. 18. Leemans, Rik and Cramer, Wolfgang, P., 1990. The IISA Database for Mean Monthly Values of Temperature, precipitation, and Cloudiness on a Global Terrestrial Grid. Laxenburg, Austria, International Institute for Applied Systems Analysis, Working Paper SP-90-41, 27 pp. 19. Pospeschill, Fred, 1988. Micro World Data Bank II: Coastlines, Country Boundaries, Islands, Lands, and Rivers. Micro Doc. 3108 Jackson Street, Bellevue, Nebraska. 20. Kidwell, Katherine B., 1990. Global Vegetation Index Users Guide. Na- tional Oceanic and Atmospheric Administration, National Climatic Data Center, Satellite Data Services Division, Washington DC 20233. 45 pp. 21. Gallo, K. P., 1992. Experimental global vegetation index from AVHRR utilizing pre-launch calibration, cloud and sun-angle screening. Digital Data. National Oceanic and Atmospheric Administration, National Geophysical Data Center, Boulder, Colorado. 22. Ohring, G., Gallo, K., Gruber, A., Planet, W., Stowe, L., and Tarpley, J. D., 1989. Climate and global change: Characteristics of NOAA satellite data. EOS Transactions of the American Geophysical Union, v. 70, pp. 889, 891, 894, 901.