Evaluation of ISLSCP Initiative II satellite-based land cover data sets and assessment of progress in land cover data for global modeling

Journal of Geophysical Research Atmospheres

Volumn 111, Issue 22, 2006, Pages

  Brown de Colstoun, Eric C ^a   DeFries, Ruth S ^b   Townshend, John R G ^b  

^a NASA GODDARD SPACE FLIGHT CENTER   (United States)

^b UNIVERSITY OF MARYLAND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CLIMATOLOGY; DATA REDUCTION; FORESTRY; MATHEMATICAL MODELS; VEGETATION;

AGGREGATION; ASSESSMENT METHOD; DATA SET; LAND COVER; LAND USE; SATELLITE DATA; VEGETATION COVER;

EID: 34548548411     PISSN: 01480227     EISSN: None     Source Type: Journal    
DOI: 10.1029/2006JD007453     Document Type: Article

References (58)

1. Asrar, G., M. Fuchs, E. T. Kanemasu, and J. L. Hatfield (1984), Estimating absorbed photosynthetically active radiation and leaf area index from spectral reflectance in wheat, Agron. J., 76, 300-306.
2. Bartholomé, E., and A. S. Belward (2005), GLC2000: A new approach to global land cover mapping from Earth observation data, Int. J. Remote Sens., 26, 1959-1977.
3. Bonan, G. B. (1995), Land-atmosphere interactions for climate system models: Coupling biophysical, biogeochemical, and ecosystem dynamical processes, Remote Sens. Environ., 51, 57-73.
4. Bonan, G. (1997), Effects of land use on the climate of the United States, Clim. Change, 37, 449-486.
5. Bonan, G. B. (2002), Ecological Climatology: Concepts and Applications, Cambridge Univ. Press, New York.
6. Bondeau, A., D. W. Kicklighter, J. Kaduk, and the Participants of the Potsdam NPP Model Intercomparison (1999), Comparing global models of terrestrial net primary productivity (NPP): Importance of vegetation structure on seasonal NPP estimates, Global Change Biol., 5, 35-45.
7. Bounoua, L., R. S. DeFries, G. J. Collatz, P. Sellers, and H. Khan (2002), Effects of land cover conversion on surface climate, Clim. Change, 52, 29-64.
8. Brown de Colstoun, E. C., W. Yang, R. DeFries, M. Hansen, and J. Townshend (2000), Surface type visible/infrared imager radiometer suite algorithm theoretical basis document, version 3.0. Natl. Polar-orbiting Oper. Environ. Satell. Syst., Silver Spring, Md. (Available at http:// npoesslib.ipo.noaa.gov/u_listcategory_v3.php?35).
9. Charney, J., P. H. Stone, and W. J. Quirk (1975), Drought in the Sahara: A biogeophysical feedback mechanism, Science, 187, 434-435.
10. Daughtry, C. S. T., K. P. Gallo, S. N. Goward, S. D. Prince, and W. P. Kustas (1992), Spectral estimates of absorbed radiation and phytomass production in corn and soybean canopies, Remote Sens. Environ., 39, 141-152.
11. DeFries, R. S., and S. O. Los (1999), Implications for land-cover misclassification for parameter estimates in global land-surface models: An example from the Simple Biosphere Model (SiB2), Photogramm. Eng. Remote Sens., 65, 1083-1088.
12. DeFries, R. S., and J. R. G. Townshend (1994a), NDVI-derived land cover classifications at a global scale, Int. J. Remote Sens., 15, 3567-3586.
13. DeFries, R. S., and J. R. G. Townshend (1994b), Global land cover: Comparison of ground-based data sets to classifications with AVHRR data, in Environmental Remote Sensing From Regional to Global Scales, edited by G. Foody and P. Curran, pp. 84-110, John Wiley, Hoboken, N. J.
14. DeFries, R. S., M. Hansen, and J. Townshend (1995), Global discrimination of land cover types from metrics derived from AVHRR pathfinder data, Remote Sens. Environ., 54, 209-222.
15. DeFries, R. S., M. Hansen, J. R. G. Townshend, and R. Sohlberg (1998), Global land cover classifications at 8 km spatial resolution: the use of training data derived from Landsat imagery in decision tree classifiers, Int. J. Remote Sens., 19, 3141-3168.
16. Defries, R. S., J. R. G. Townshend, and M. Hansen (1999), Continuous fields of vegetation characteristics at the global scale at 1 km resolution, J. Geophys. Res., 104, 16,911-16,925.
17. DeFries, R. S., M. C. Hansen, J. R. G. Townshend, A. C. Janetos, and T. R. Loveland (2000), A new global 1-km dataset of percentage tree cover derived from remote sensing, Global Change Biol., 6, 247-254.
18. Dickinson, R. E. (1983), Land surface processes and climate-surface albedos and energy balance, Adv. Geophys., 25, 305-350.
19. 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-275+STR, Natl. Cent. for Atmos. Res., Boulder, Colo.
20. DiGregorio, A., and L. J. M. Jansen (2000), Land Cover Classification System (LCCS): Classification concepts and user manual, U. N. Food and Agric. Organ., Rome.
21. Dorman, J. L., and P. J. Sellers (1989), A global climatology of albedo, roughness length and stomatal resistance for atmospheric general circulation models as represented by the simple biosphere model, J. Appl. Meteorol., 28, 833-855.
22. Eidenshink, J. C., and J. L. Faundeen (1994), The 1 km AVHRR global land data set: First stages in implementation, Int. J. Remote Sens., 15, 3443-3462.
23. Friedl, M. A., et al. (2002), Global land cover mapping from MODIS: Algorithms and early results, Remote Sens. Environ., 83, 287-302.
24. Hall, F. G., E. Brown de Colstoun, G. J. Collatz, D. Landis, P. Dirmeyer, A. Betts, G. Huffman, L. Bounoua, and B. Meeson (2006), ISLSCP Initiative II global data sets: Surface boundary conditions and atmospheric forcings for land-atmosphere studies, J. Geophys. Res., doi:10.1029/2006JD007366, in press.
25. Hansen, M., and B. Reed (2000), A comparison of the IGBP-DIScover and the University of Maryland 1 km global land cover products, Int. J. Remote Sens., 21, 1365-1374.
26. Hansen, M. C., R. S. DeFries, J. R. G. Townshend, and R. Sohlberg (2000), Global land cover classification at 1 km spatial resolution using a classification tree approach, Int. J. Remote Sens., 21, 1331-1364.
27. Hansen, M. C., R. S. DeFries, J. R. G. Townshend, R. 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.
28. Houghton, R. A. (2003), Revised estimates of the annual net flux of carbon to the atmosphere from changes in land use and land management 1850-2000, Tellus, Ser. B, 55, 378-390.
29. James, M. E., and S. N. V. Kalluri (1994), The pathfinder AVHRR land data set: An improved coarse resolution data set for terrestrial monitoring, Int. J. Remote Sens., 15, 3347-3364.
30. Justice, C. O., J. R. G. Townshend, B. N. Holben, and C. J. Tucker (1985), Analysis of the phenology of global vegetation using meteorological satellite data, Int. J. Remote Sens., 6, 1271-1318.
31. Kicklighter, D. W., A. Bondeau, A. L. Schloss, J. Kaduk, A. D. McGuire and the Participants of the Potsdam NPP Model Intercomparison (1999), Comparing global models of net primary productivity (NPP): Global pattern and differentiation by major biomes, Global Change Biol., 5, 16-24.
32. Klein Goldewijk, K. (2001), Estimating global land use change over the past 300 years: The HYDE database, Global Biogeochem. Cycles, 15(2), 417-433.
33. Klein Goldewijk, K., and N. Ramankutty (2004), Land cover change over the last three centuries due to human activities: The availability of new global data sets, Geojournal, 61, 335-344.
34. Loveland, T. R., and A. S. Belward (1997), The IGBP-DIS global 1 km land cover data set, DISCover: First results, Int. J. Remote Sens., 18, 3289-3295.
35. Loveland, T. R., J. W. Merchant, D. O. Ohlen, and J. F. Brown (1991), Development of a land-cover characteristics database for the conterminous U.S., Photogramm. Eng. Remote Sens., 57, 1453-1463.
36. Manabe, S. (1969), Climate and the ocean circulation: 1. The atmospheric circulation and the hydrology of the Earth's surface, Mon. Weather Rev., 97, 739-805.
37. Matthews, E. (1983), Global vegetation and land use: New high-resolution data bases for climate studies, J. Clim. Appl. Meteorol., 22, 474-487.
38. Melillo, J. M. (1994), Modeling land-atmosphere interactions: A short review, in Changes in Land Use and Land Cover: A Global Perspective, edited by W. B. Meyer and B. L. Turner III, pp. 387-410, Cambridge Univ. Press, New York.
39. Melillo, J. M., et al. (1993), Global climate change and terrestrial net primary production, Nature, 363, 234-240.
40. Mueller-Dombois, D. (1984), Classification and mapping of plant communities: A review with emphasis on tropical vegetation, in The Role of Terrestrial Vegetation in the Global Carbon Cycle: Measurement by Remote Sensing, edited by G. M. Woodwell, pp. 19-88, John Wiley, Hoboken, N. J.
41. Nemani, R., and S. W. Running (1996), Implementation of a hierarchical global vegetation classification in ecosystem function models, J. Veg. Sci., 7, 337-346.
42. New, M., M. Hulme, and P. Jones (2000), Representing twentieth-century space-time climate variability. Part II: Development of 1901-1996 monthly grids of terrestrial surface climate, J. Clim., 13(13), 2217-2238.
43. Olson, J. S., J. Watts, and L. Allison (1983), Carbon in live vegetation of major world ecosystems, Rep. W-7405-ENG-26, U.S. Dep. of Energy, Oak Ridge Natl. Lab., Oak Ridge, Tenn.
44. Plattner, G., F. Joos, and T. F. Stocker (2002), Revision of the global carbon budget due to changing air-sea oxygen fluxes, Global Biogeochem. Cycles, 16(4), 1096, doi:10.1029/2001GB001746.
45. Prentice, K. C. (1990), Bioclimatic distribution of vegetation for general circulation models, J. Geophys. Res., 95, 11,811-11,830.
46. Ramankutty, N., and J. A. Foley (1998), Characterizing patterns of global land use: An analysis of global croplands data, Global Biogeochem. Cycles, 12, 667-685.
47. Ramankutty, N., and J. A. Foley (1999), Estimating historical changes in global land cover: Croplands from 1700 to 1992, Global Biogeochem. Cycles, 13, 997-1027.
48. Running, S. W., and E. R. Hunt Jr. (1993), Generalization of a forest ecosystem process model for other biomes, BIOME-BGC, and an application for global-scale models, in Scaling Processes Between Leaf and Landscape Levels, edited by J. R. Ehleringer and C. Field, pp. 141-158, Elsevier, New York.
49. Running, S. W., T. R. Loveland, L. L. Pierce, R. R. Nemani, and E. R. Hunt Jr. (1995), A remote sensing based vegetation classification logic for global land cover analysis, Remote Sens. Environ., 51, 39-48.
50. Scepan, J. (1999), Thematic validation of high-resolution global land-cover data sets, Photogramm. Eng. Remote Sens., 65, 1051-1060.
51. Sellers, P. J., S. O. Los, C. J. Tucker, C. O. Justice, D. A. Dazlich, G. J. Collatz, and D. A. Randall (1996a), A revised land surface parameterization (SiB2) for atmospheric GCMs. Part II: The generation of global fields of terrestrial biophysical parameters from satellite data, J. Clim., 9, 706-737.
52. Sellers, P. J., B. W. Meeson, J. Closs, J. Collatz, F. Corprew, D. Dazlich, and F. G. Hall (1996b), The ISLSCP Initiative I global datasets: Surface boundary conditions and atmospheric forcings for land-atmosphere studies, Bull. Am. Meteorol. Soc., 77, 1987-2005.
53. Skole, D. L., and C. J. Tucker (1993), Tropical deforestation and habitat fragmentation in the Amazon: Satellite data from 1978 to 1988, Science, 260, 1905-1910.
54. Still, C. J., J. A. Berry, G. J. Collatz, and R. S. DeFries (2003), Global distribution of C3 and C4 vegetation: Carbon cycle implications, Global Biogeochem. Cycles, 17(1), 1006, doi:10.1029/2001GB001807.
55. Townshend, J. R. G., C. O. Justice, and V. T. Kalb (1987), Characterization and classification of South American land cover types using satellite data, Int. J. Remote Sens., 8, 1189-1207.
56. Townshend, J. R. G., C. O. Justice, D. Skole, J.-P. Malingreau, J. Cihlar, P. Teillet, F. Sadowski, and S. Ruttenberg (1994), The 1 km resolution global data set: Needs of the International Geosphere Biosphere Programme, Int. J. Remote Sens., 15, 3417-3442.
57. Tucker, C. J., J. R. G. Townshend, and T. E. Goff (1985), African landcover classification using satellite data, Science, 227, 369-375.
58. Wilson, M. F., and A. Henderson-Sellers (1985), A global archive of land cover and soils data for use in general circulation models, J. Clim., 5, 119-143.