Global land cover classifications at 8 km spatial resolution: The use of training data derived from Landsat imagery in decision tree classifiers

International Journal of Remote Sensing

Volumn 19, Issue 16, 1998, Pages 3141-3168

  DeFries, R S ^a   Hansen, M ^a   Townshend, J R G ^a   Sohlberg, R ^a  

^a UNIVERSITY OF MARYLAND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE PROCESSING; MULTISPECTRAL SCANNERS; OPTICAL RESOLVING POWER; RADIOMETERS; SATELLITES; TREES (MATHEMATICS); VEGETATION;

ADVANCED VERY HIGH RESOLUTION RADIOMETERS (AVHRR); NORMALIZED DIFFERENCE VEGETATION INDEX (NDVI);

REMOTE SENSING;

AVHRR; IGBP; LAND CLASSIFICATION; LAND COVER; LANDSAT MULTISPECTRAL SCANNER; SPATIAL RESOLUTION;

EID: 0032216156     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/014311698214235     Document Type: Article

References (41)

1. Agbu, P. A., and James, M. E., 1994, The NOAA/NASA Pathfinder AVHRR Land Dataset User’s Manual, Goddard Distributed Active Archive Center Publications, GCDG, Greenbelt, MD, USA.
2. Belward, A. S., and Loveland, T. R., 1995, The IGBP DIS 1 km land cover project: remote sensing in action.Proceedings of the 21st Annual Conference of the Remote Sensing Society, Southhampton, UK, pp. 1099-1106.
3. Breiman, L., Friedman, J. H., Olshend, R. A., and Stone, C. J., 1984, Classification and Regression Trees(Monterey, CA: Wadsworth).
4. Brodley, C. E., and Friedl, M. A., 1996, Improved automated land cover mapping by identifying and eliminating mislabelled observations from training data.International Geoscience and Remote Sensing Symposium, Lincoln, Nebraska, FOCUS Interactive Technology, Inc.
5. Cihlar, J., Ly, H., Li, Z., Chen, J., Pokrant, H., and Huang, F., 1997, Multitemporal, multichannel AVHRR datasets for land biosphere studies-artifacts and corrections.Remote Sensing of Environment, 60, 35-57.
6. Clark, L. A., and Pergibon, D., 1992, Tree-based models. InStatistical Models in S, edited by T. J. Hastie (Pacific Grove, CA: Wadsworth and Brooks).
7. DeFries, R., Hansen, M., Steininger, M., Dubayah, R., Sohlberg, R., and Townshend, J., 1997, Subpixel forest cover in Central Africa from multisensor, multitemporal data.Remote Sensing of Environment, 60, 228-246.
8. DeFries, R., Hansen, M., and Townshend, J., 1995, Global discrimination of land cover types from metrics derived from AVHRR Pathfinder data.Remote Sensing of Environment, 54, 209-222.
9. DeFries, R. S., and Townshend, J. R. G., 1994 a, Global land cover: comparison of ground-based datasets to classifications with AVHRR data. InEnvironmental Remote Sensing from Regional to Global Scales, edited by G. Foody and P. Curran (Chichester, UK: John Wiley).
10. DeFries, R. S., and Townshend, J. R. G., 1994 b, NDVI-derived land cover classification at global scales.International Journal of Remote Sensing, 15, 3567-3586.
11. DeFries, R. S., and Townshend, J. R. G., 1995, An initial coarse resolution NDVI-derived global land cover classification. InISLSCP Initiative I—GlobalDatasetsfor Land-Atmosphere Models, 1987-1988, Volumes 1-5, edited by B. W. Meeson, F. E. Corprew, J. M. P. McManus, D. W. Myers, J. W. Closs, K.-J. Sun, D. J. Sunday and P. J. Sellers, published on CD (Washington, DC: NASA) (USA NASA GDAAC_ ISLSCP 001—USA NASA GDAAC ISLSCP 005).
12. Ehrlich, D., and Lambin, E. F., 1996, Broad scale land-cover classification and interannual climatic variability.International Journal of Remote Sensing, 17, 845-862.
13. Eidenshink, J. C., and Faudeen, J. L., 1994, The 1km AVHRR global land dataset: first stages in implementation.International Journal of Remote Sensing, 15, 3443-3462.
14. Hansen, M., Dubayah, R., and DeFries, R., 1996, Classification trees: an alternative to traditional land cover classifiers.International Journal of Remote Sensing, 17, 1075-1081.
15. Holben, B. N., 1986, Characteristics of maximum-value composite images from temporal AVHRR data, International Journal of Remote Sensing, 12, 1147-1163.
16. James, M. E., and Kalluri, S. N. V., 1994, The Pathfinder AVHRR land dataset: An improved coarse resolution dataset for terrestrial monitoring, International Journal of Remote Sensing, 15, (17), 3347-3364.
17. Lloyd, D., 1990, A phenological classification of terrestrial vegetation cover using shortwave vegetation index imagery, International Journal of Remote Sensing, 11, (12), 2269-2270.
18. Loveland, T. R., and Belward, A. S., 1997, The IGBP-DIS global 1 km land cover dataset, DISCover: first results.International Journal of Remote Sensing, 18, 3289-3295.
19. LoveLand, T. R., Merchant, J. W., OhLen, D. O., and Brown, J. F., 1991, Development of a land-cover characteristics database for the conterminous U.S.Photogrammetric Engineering and Remote Sensing, 57, 1453-1463.
20. Matthews, E., 1983, Global vegetation and land use: new high resolution data bases for climate studies.Journal of Climate and Applied Meteorology, 22, 474-487.
21. MichaeLson, J., Schimel, D. S., Friedl, M. A., Davis, F. W., and Dubayah, R. O., 1994, Regression tree analysis of satellite and terrain data to guide vegetation sampling and surveys.Journal of Vegetation Science, 5, 673- 696.
22. NeLson, R., 1989, Regression and ratio estimators to integrate AVHRR and MSS data.Remote Sensing of Environment, 30, 201-216.
23. Nemani, R., and Running, S., 1995, Satellite monitoring of global land cover changes and their impact on climate.Climatic Change, 31, 395-413.
24. OLson, J. S., Watts, J., and ALLison, L., 1983, Carbon in live vegetation of major world ecosystems Report W-7405-ENG-26, US Department of Energy, Oak Ridge National Laboratory, USA.
25. Price, J. C., 1984, Land surface temperature measurements from the split window channels of NOAA-7/AVHRR.Journal of Geophysical Research, 100, 81-92.
26. Quirnan, R. J., 1993, C4.5: Programs for Machine Learning,(San Mateo, CA: Morgan Kaufmann).
27. Reed, B. D., Brown, J. F., Vanderzee, D., Loveland, T. R., Merchant, J. W., and Omen
28. D. O., 1994, Measuring phenological variability from satellite imagery.Journal of Vegetation Science, 5, 703-714.
29. Running, S. W., LoveLand, T. R., and Pierce, L. L., 1994, A vegetation classi® cation logic based on remote sensing for use in global biogeochemical models.Ambio, 23,(1), 77-81.
30. Running, S. W., LoveLand, T. W., Pierce, L. L., Nemani, R. R., and Hunt, E. R. Jr, 1995, A remote sensing based vegetation classi® cation logic for global land cover analysis.Remote Sensing of Environment, 51, 39-48.
31. 2on climate.Science, 271,(5254), 1402.
32. SeLLers, P. J., Tucker, C. J., CoLLatz, G. J., Los, S. O., Justice, C. O., DazLich, D. A., and Randall, D. A., 1994, A global 1 degree by 1 degree dataset for climate studies. Part 2: The generation of global fields of terrestrial biophysical parameters from the NDVI.International Journal of Remote Sensing, 15, 3519-3545.
33. Shea, D., 1986, Climatological atlas: 1950-1979. Surface air temperature, precipitation, sea-level pressure, and sea surface temperature. Technical Note NCAR/TN-269 + str NCAR, Boulder, CO, USA.
34. Stone, T. A., SchLesinger, P., Houghton, R. A., and Woodwell, G. M., 1994, A map of the vegetation of South America based on satellite imagery.Photogrammetric Engineering and Remote Sensing, 60, 541-551.
35. Townshend, J. R. G. (editor), 1992, Improved global data for land applications: a proposal for a new high resolution dataset. Report No 20, International Geosphere- Biosphere Program, Stockholm, Sweden.
36. Townshend, J. R. G., Justice, C. O., and KaLb, V. T., 1987, Characterization and classi® cation of South American land cover types using satellite data.International Journal of Remote Sensing, 8, 1189-1207.
37. Townshend, J. R. G., Justice, C. O., Li, W., Gurney, C., and McManus, J., 1991, Global land cover classi® cation by remote sensing: present capabilities and future possibilities.Remote Sensing of the Environment, 35, 243- 256.
38. Townshend, J. R. G., Justice, C. O., Skole, D., Malingreau, J.-P., Cirnar, J., Teinet, P., Sadowski, F., and Ruttenberg, S., 1994, The 1 km resolution global dataset: needs of the International Geosphere-Biosphere Programme.International Journal of Remote Sensing, 15, 3417-3441.
39. Tucker, C. J., Townshend, J. R. G., and Goff, T. E., 1985, African land-cover classification using satellite data.Science, 227, 369-375.
40. Venables, W. N., and Ripley, B. D., 1994, Modern Applied Statistics with S-Plus(New York: Springer-Verlag).
41. Wilson, M. F., and Henderson-Seners, A., 1985, A global archive of land cover and soils data for use in general circulation models.Journal of Climatology, 5, 119-143.