[Location: Location_Category='CONTINENT', Location_Type='AFRICA', Location_Subregion1='NORTHERN AFRICA']
Compendium of Environmental Sustainability Indicator Collections: The Wellbeing of NationsEntry ID: CIESIN_SEDAC_CESIC_WELLBEING
Abstract: The Wellbeing of Nations portion of the Compendium of Environmental Sustainability Indicator Collections contains a subset of 123 variables assembled from the Wellbeing of Nations, which assesses human and ecosystem wellbeing for 183 countries. The variables selected include both raw data and processed indicators and indices created by the report's author, Robert Prescott-Allen. The data are ... distributed by the Columbia University Center for International Earth Science Information Network (CIESIN).
The data in comma-separated values (CSV), SPSS (SAV) and Stata (DTA) formats, a data dictionary for all indicators and ancillary variables in Word (DOC), Portable Document Format (PDF), and Microsoft Access (MDB) formats as well as and maps in Portable Document Format (PDF) and Portable Network Graphics (PNG) formats are available from the NASA Socioeconomic Data and Applications Center (SEDAC).
Purpose: To provide data that address the key issues of sustainability by combining indicators of human wellbeing with those of environmental sustainability to generate a more comprehensive picture of the state of the world.
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Data Set Citation
Dataset Originator/Creator: Prescott-Allen, R.
Dataset Title: Compendium of Environmental Sustainability Indicator Collections: The Wellbeing of Nations
Dataset Release Date: 2001
Dataset Release Place: Washington, DC
Dataset Publisher: Island Press
Data Presentation Form: tabular, mapOnline Resource: http://sedac.ciesin.columbia.edu/data/set/cesic-wellbeing-of-nations
Start Date: 1990-01-01Stop Date: 2000-01-01
Temporal Resolution: 5-min
Temporal Resolution Range: 1 minute - < 1 hour
ISO Topic Category
Quality In MYD29 Version 4 (V004) data, the sea ice algorithm uses Aqua/MODIS band 7. Good quality has been observed in the sea ice maps; however, investigation of effects of the switch to band 7 is continuing. The cloud mask product, MYD35_L2, used as input to the MYD29 algorithm also changed to use of band 7. The effect of that change relative to sea ice/cloud discrimination is being investigated. The ... IST was not affected by the switch to band 7 except, possibly indirectly by the cloud mask switch to band 7. Validation status is set at provisional until further validation work specific to Aqua IST maps can be completed. Provisional means that the products are partially validated; incremental improvements are still occurring. These are early science validated products and are useful for exploratory and process scientific studies. Quality may not be optimal since validation and quality assurance are ongoing. Users are urged to review product quality summaries before publication of results. Analysis of the quality of the sea ice data products is an ongoing activity. Specific information on the science quality of the sea ice data products is reported in the ScienceQualityFlagExplanation object in the CoreMetadata.0 global attribute. The URL for the quality assessment site is given in the product metadata and is linked to from the EOS Data Gateway (EDG) when ordering data. The ScienceQualityFlagExplanation is changed in response to analysis and should be checked for updated information. In the MOD29 and MOD29P1D data products there are two instances of the ScienceQualityFlagExplanation, one for sea ice determined by reflectance data and one for IST written in the metadata. Information on both is posted at that URL. The Ice Surface Temperature PixelQA and the Sea Ice by Reflectance PixelQA data fields provide additional information on algorithm results for each pixel within a spatial context, and are used as a measure of usefulness for sea ice data. QA data are stored as bit flags. QA information is extracted by reading the bits within a byte (See MODIS Sea Ice Quality Assurance Fields). The QA information tells if algorithm results were nominal, abnormal, or if other defined conditions were encountered for a pixel (Riggs, Hall, and Salomonson 2003). See MODIS Land Quality Assessment for further details.
Data Set Progress
Distribution Media: upon request
Distribution Size: 0.5-6.0
Distribution Format: HDF-EOS
Email: George.A.Riggs at nasa.gov
NASA Goddard Space Flight Center (GSFC) Science Systems and Applications, Inc. Code 614.1
Province or State: MD
Postal Code: 20771
National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) Mail stop 614.1
Province or State: MD
Postal Code: 20771
Email: vincent.salomonson at utah.edu
University of Utah Department of Meteorology 135 S 1460 E, Rm 809
City: Salt Lake City
Province or State: UT
Postal Code: 84112
Role: TECHNICAL CONTACT
Phone: +1 (303) 492-6199
Fax: +1 (303) 492-2468
Email: nsidc at nsidc.org
National Snow and Ice Data Center CIRES, 449 UCB University of Colorado
Province or State: CO
Postal Code: 80309-0449
Earth Science Data and Information System (ESDIS). 1996. EOS ground system (EGS) systems and operations concept. Greenbelt, MD: Goddard Space Flight Center. Hall, D. K., A. B. Tait, G. A. Riggs, and V. V. Salomonson. 1998. Algorithm Theoretical Basis Document (ATBD) for the MODIS Snow-, Lake Ice- and Sea Ice-Mapping Algorithms (Version 4.0). Electronic version is available online at ... http://snowmelt.gsfc.nasa.gov/MODIS_Snow/atbd.html. Hall, D. K. and J. Martinec. 1985. Remote sensing of ice and snow. London: Chapman and Hall. Key, J. R., J. B. Collins, C. Fowler, and R. S. Stone. 1997. High latitude surface temperature estimates From thermal satellite data. Remote Sensing of the Environment 61:302-309. Key, J. R., J. A. Maslanik, T. Papakyriakou, M. C. Serreze, and A. J. Schweiger. 1994. On the validation of satellite-derived sea ice surface temperature. Arctic 47:280-287. Markham, B. L. and J. L. Barker. 1986. Landsat MSS and TM post-calibration dynamic ranges, exoatmospheric reflectances and at-satellite temperatures. EOSAT Technical Notes 1:3-8. MODIS Characterization and Support Team (MCST). 2000. MODIS level 1B product user's guide for level 1B Version 2.3.x Release 2. MCST Document #MCM-PUG-01-U- DNCN. MODIS Web. MODIS Science and Instrument Team. 2001. http://modis.gsfc.nasa.gov/. Pearson II, F. 1990. Map projections: theory and applications. Boca Raton, FL: CRC Press, Inc. Riggs, G., D. Hall, and V. Salomonson. 2001. MODIS sea ice products user's guide. Electronic version is available online at http://modis-snow-ice.gsfc.nasa.gov/siugkc.html. Riggs, G. A., D. K. Hall, and S. A. Ackerman. 1999. Sea ice extent and classification mapping with the Moderate Resolution Imaging Spectroradiometer Airborne Simulator. Remote Sensing of the Environment 68:152-163. Wiscombe, W. J. and S. G. Warren. 1980. A model for the spectral albedo of snow I: pure snow. Journal of the Atmospheric Sciences 37:2712-2733.
Creation and Review Dates
DIF Creation Date: 2003-05-23
Last DIF Revision Date: 2011-02-11