A priori evaluation of two-stage cluster sampling for accuracy assessment of large-area land-cover maps

International Journal of Remote Sensing

Volumn 25, Issue 6, 2004, Pages 1235-1252

  Wickham, J D ^a   Stehman, S V ^b   Smith, J H ^a   Wade, T G ^a   Yang, L ^c  

^a U S ENVIRONMENTAL PROTECTION AGENCY   (United States)

^b STATE UNIVERSITY OF NEW YORK   (United States)

^c SCIENCE APPLICATIONS INTERNATIONAL CORPORATION   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA REDUCTION; DECISION MAKING; ERROR ANALYSIS; ESTIMATION;

CLUSTER SAMPLING; SAMPLE ELEMENTS;

REMOTE SENSING;

ACCURACY ASSESSMENT; CLUSTER ANALYSIS; LAND CLASSIFICATION; LAND COVER; MAPPING METHOD;

EID: 1542347795     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/0143116031000149998     Document Type: Article

References (24)

1. Anderson, J. F., Hardy, E. E., Roach, J. T., and Witmer, R. E., 1976, A land use and land cover classification system for use with remote sensor data, US Geological Survey Professional Paper 964, 28 pp. US Department of Interior, Washington, DC.
2. Bond, D., and Devine, P., 1991, The role of geographic information systems in survey analysis. The Statistician, 40, 209-215.
3. Brown, N., Gerard, F., and Fuller, R., 2002, Mapping of land use classes within the CORINE land cover map of Great Britain. The Cartographic Journal, 39, 5-14.
4. CAMPBELL, J. B., 1987, Introduction to Remote Sensing (New York: Guilford Press).
5. Congalton, R. G., 1988a, A comparison of sampling schemes used in generating error matrices for assessing the accuracy of maps generated from remotely sensed data. Photogrammetric Engineering and Remote Sensing, 54, 593-600.
6. Congalton, R. G., 1988b, Using spatial autocorrelation analysis to explore the errors in maps generated from remotely sensed data. Photogrammetric Engineering and Remote Sensing, 54, 587-592.
7. CONGALTON, R. G., and Green, K., 1999, Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. (New York: Lewis Publishers).
8. Edwards, Jr, T. C., Moisen, G. G., and Cutler, D. R., 1998, Assessing map accuracy in a remotely sensed ecoregion-scale cover map. Remote Sensing of Environment, 63, 73-83.
9. Lillesand, T. M., 1994, Strategies for improving the accuracy and specificity of large-area, satellite-based land cover inventories. Proceedings of the ISPRS Commision IV Symposium on Mapping and Geographic Information Systems, Athens, GA: 31 May-3 June 1994, 30, 23-30.
10. Lohr, S., 1999, Sampling: Design and Analysis (Pacific Grove, CA: Brookes/Cole Publishing Company).
11. Loveland, T. R., and Shaw, D. M., 1996, MultiResolution Land Characterization: building collaborative partnerships. in Gap Analysis: A Landscape Approach to Biodiversity Planning, Proceedings of the ASPRS/GAP Symposium, edited by J. M. Scott, T. Tear and F. Davis (Charlotte, NC: ASPRS/GAP), June 1994, National Biological Service, Moscow, Idaho, pp. 83-89.
12. Maxim, L. D., and Harrington, L., 1984, An optimal two-stage cluster sampling for aerial surveys with detection errors. Photogrammetric Engineering and Remote Sensing, 50, 1613-1627.
13. Moisen, G. G., Edwards, Jr., T. C., and Cutler, D. R., 1994, Spatial sampling to assess classification accuracy of remotely sensed data. in Environmental Information Management and Analysis: Ecosystem to Global Scales, edited by W. K. Michener, J. W. Brunt and S. G. Stafford (Philadelphia: Taylor &Francis), pp. 159-176.
14. Scepan, J., 1999, Thematic validation of high-resolution global land-cover data sets. Photogrammetric Engineering and Remote Sensing, 65, 1051-1060.
15. Smith, J. H., Wickham, J. D., Stehman, S. V., and Yang, L., 2002, Effect of patch size and heterogeneity on thematic accuracy of land-cover data. Photogrammetric Engineering and Remote Sensing, 68, 65-70.
16. Stehman, S. V., 1996, Estimating standard errors of accuracy assessment statistics under cluster sampling. Remote Sensing of Environment, 60, 258-269.
17. Stehman, S. V., 2001, Statistical rigor and practical utility in thematic map accuracy assessment. Photogrammetric Engineering and Remote Sensing, 67, 727-734.
18. Todd, W. j., Gehring, D. G., and Haman, J. F., 1980, Landsat wildland mapping accuracy. Photogrammetric Engineering and Remote Sensing, 46, 509-520.
19. Townshend, J. R. G., Huang, C., Kalluri, S. N. V., Defries, R. S., Liang, S., and Yang, K., 2000, Beware of per-pixel characterization of land cover. International Journal of Remote Sensing, 21, 839-843.
20. Vogelmann, J. E., Howard, S. M., Yang, L., Larson, C. R., Wylie, B. K., and VAN Driel, N., 2001, Completion of the 1990s national land cover data set for the conterminous United States from Landsat Thematic Mapper data and ancillary data sources. Photogrammetric Engineering and Remote Sensing, 67, 650-662.
21. Wickham, J. D., and Norton, D. J., 1994, Mapping and analyzing landscape patterns. Landscape Ecology, 9, 7-23.
22. Wickham, J. D., O’Neill, R. V., Riitters, K. H., Wade, T. G., and Jones, K. B., 1997, Sensitivity of selected landscape pattern metrics to land-cover misclassification and differences in land-cover composition. Photogrammetric Engineering and Remote Sensing, 63, 397-402.
23. Yang, L., Stehman, S. V., Smith, J. H., and Wickham, J. D., 2001, Thematic accuracy of MRLC land cover for the eastern United States. Remote Sensing of Environment, 76, 418-422.
24. Zhu, Z., Yang, L., Stehman, S. V., and Czaplewski, R. L., 2000, Accuracy assessment for the U.S. Geological Survey regional land cover mapping program: New York and New Jersey Region. Photogrammetric Engineering and Remote Sensing, 66, 1425-1435.