A MODIS-based global 1-km maximum green vegetation fraction dataset

Journal of Applied Meteorology and Climatology

Volumn 53, Issue 8, 2014, Pages 1996-2004

  Broxton, Patrick D ^a   Zeng, Xubin ^a   Scheftic, William ^a   Troch, Peter A ^a  

^a UNIVERSITY OF ARIZONA   (United States)

Author keywords

Geographic information systems (GIS); Interannual variability; Land surface; Satellite observations; Vegetation atmosphere interactions

Indexed keywords

CLIMATOLOGY; GEOGRAPHIC INFORMATION SYSTEMS; RADIOMETERS; SATELLITE IMAGERY;

COMMUNITY LAND MODELS; INTERANNUAL VARIABILITY; LAND SURFACE; LAND-COVER CLASSIFICATION; MODERATE RESOLUTION IMAGING SPECTRORADIOMETER; NORMALIZED DIFFERENCE VEGETATION INDEX; SATELLITE OBSERVATIONS; VEGETATION-ATMOSPHERE INTERACTIONS;

VEGETATION;

ANNUAL VARIATION; ATMOSPHERE-BIOSPHERE INTERACTION; DATA SET; GIS; LAND CLASSIFICATION; LAND COVER; LAND SURFACE; LEAF AREA INDEX; MODIS; NDVI; SATELLITE DATA;

EID: 84905985541     PISSN: 15588424     EISSN: 15588432     Source Type: Journal    
DOI: 10.1175/JAMC-D-13-0356.1     Document Type: Article

References (31)

1. barlage, M., and X. Zeng, 2004: The effects of observed fractional vegetation cover on the land surface climatology of the Community Land Model. J. Hydrometeor., 5, 823-830
2. Bonan, G. B., 1996: A land surface model (LSM version 1.0) for ecological, hydrological, and atmospheric studies: Technical description and user's guide. NCAR Tech. Note NCAR/TN-4171STR, 150 pp. [Available online at http://nldr.library. ucar.edu/repository/assets/technotes/TECH-NOTE-000-000-000-229.pdf.]
3. Broxton, P.D., X. Zeng, D. Sulla-Menashe, and P. A. Troch, 2014:A global land cover climatology using MODIS data. J. Appl. Meteor. Climatol., 53, 1593-1605
4. Carlson, T. N., and D. A. Ripley, 1997: On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sens. Environ., 62, 241-252
5. Chen, F., and J. Dudhia, 2001: Coupling an advanced land surface- hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea.Rev., 129, 569-585
6. Dai, Y., and Coauthors, 2003: The Common LandModel. Bull.Amer. Meteor. Soc., 84, 1013-1023
7. Deardorff, J. W., 1978: Efficient prediction of ground surface temperature and moisture, with inclusion of a layer of vegetation. J. Geophys. Res., 83, 1889-1903
8. DeFries, R. S., J. R. G. Townshend, and M. C. Hansen, 1999: Continuous fields of vegetation characteristics at the global scale at 1-km resolution. J. Geophys. Res., 104, 16 911-16 923
9. Dickinson, R. E., A. Henderson-Sellers, P. J. Kennedy, and M. F. Wilson, 1986: Biosphere-Atmosphere Transfer Scheme (BATS) for the NCAR Community Climate Model. NCAR Tech. Note NCAR/TN-2751STR, 69 pp. [Available online at http://nldr. library.ucar.edu/repository/assets/technotes/TECH-NOTE-000-000-000-527.pdf.]
10. Ek, M. B., K. E. Mitchell, Y. Lin, E. Rogers, P. Grunmann, V. Koren, G. Gayno, and J. D. Tarpley, 2003: Implementation of Noah land surface model advances in the National Centers forEnvironmental Prediction operationalmesoscale EtaModel. J. Geophys. Res., 108, 8851
11. Fensholt, R., and I. Sandholt, 2005: Evaluation of MODIS and NOAA AVHRR vegetation indices with in situ measurements in a semi-arid environment. Int. J. Remote Sens., 26, 2561-2594
12. Friedl, M. A., D. Sulla-Menashe, B. Tan, A. Schneider, N. Ramankutty, A. Sibley, and X. Huang, 2010: MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets. Remote Sens. Environ., 114, 168-182
13. Gutman, G., and A. Ignatov, 1998: The derivation of the green vegetation fraction from NOAA/AVHRR data for use in numerical weather prediction models. Int. J. Remote Sens., 19, 1533-1543
14. Hadley, N. F., and S. R. Szarek, 1981: Productivity of desert ecosystems. Bioscience, 31, 747-753
15. Hansen, M. C., R. S. DeFries, J. R. G. Townshend, R. A. Sohlberg, C. Dimiceli, and M. Carroll, 2002: Towards an operational MODIS continuous field of percent tree cover algorithm: Examples using AVHRR and MODIS data. Remote Sens. Environ., 83, 303-319
16. Hansen, M. C., R. S. DeFries, J. R. G. Townshend, M. Carroll, C. Dimiceli, and R. A. Sohlberg, 2003: Global percent tree cover at a spatial resolution of 500 meters: First results of the MODIS vegetation continuous fields algorithm. Earth Interact., 7
17. Huete, A., K. Didan, T. Miura, E. P. Rodriguez, X. Gao, and L. G. Ferreira, 2002: Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens. Environ., 83, 195-213
18. Koster, R. D., and Coauthors, 2004: Regions of strong coupling between soil moisture and precipitation. Science, 305, 1138- 1140
19. Lawrence, P. J., and T.N. Chase, 2007: Representing a newMODIS consistent land surface in the Community Land Model (CLM 3.0). J. Geophys. Res., 112, G01023
20. Leprieur, C., M.M. Verstraete, and B. Pinty, 1994: Evaluation of the performance of various vegetation indices to retrieve vegetation cover from AVHRR data. Remote Sens. Rev., 10, 265-284
21. Miller, J., M. Barlage, X. Zeng,H.Wei,K.Mitchell, andD. Tarpley, 2006: Sensitivity of the NCEP/Noah land surface model to the MODIS green vegetation fraction data set. Geophys. Res. Lett., 33, L13404
22. Myneni, R. B., and Coauthors, 2002: Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data. Remote Sens. Environ., 83, 214-231
23. Purevdorj, Ts., R. Tateishi, T. Ishiyama, and Y. Honda, 1998: Relationships between percent vegetation cover and vegetation indices. Int. J. Remote Sens., 19, 3519-3535
24. Sellers, P. J., S. O. Los, C. J. Tucker, C. O. Justice, D. A. Dazlich, G. J. Collatz, and D. A. Randall, 1996: A revised land surface parameterization (SiB2) for atmospheric GCMs. Part II: Generation of global fields of terrestrial biophysical parameters from satellite data. J. Climate, 9, 706-737
25. Townshend, J. R. G., 1992: Improved global data for land applications: Aproposal for a new high resolution data set. International Geosphere-Biosphere Program Global Change Rep. 20, 87 pp.
26. Tucker, C. J., 1979: Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ., 8, 127-150
27. Weiss, J. L., D. S. Gutzler, J. E. A. Coonrod, and C. N. Dahm, 2004: Seasonal and inter-annual relationships between vegetation and climate in central New Mexico, USA. J. Arid Environ., 57, 507-534
28. Wittich, K.-P., 1997: Some simple relationships between landsurface emissivity, greenness and the plant cover fraction for use in satellite remote sensing. Int. J. Biometeor., 41, 58-64
29. Zeng,X., R. E. Dickinson, A. Walker,M. Shaikh, R. DeFries, and J.Qi, 2000: Derivation and evaluation of global 1-km fractional vegetation cover data for land modeling. J. Appl.Meteor., 39, 826-839
30. Zeng,X., P. Rao, R. DeFries, and M. C. Hansen, 2003: Interannual variability and decadal trend of global fractional vegetation cover from 1982 to 2000. J. Appl. Meteor., 42, 1525-1530
31. Zeng,X., M. Barlage, C. Castro, andK. Fling, 2010:Comparison of land- precipitation coupling strength using observations and models. J. Hydrometeor., 11, 979-994