Sampling method and sample placement: How do they affect the accuracy of remotely sensed maps?

Photogrammetric Engineering and Remote Sensing

Volumn 69, Issue 3, 2003, Pages 289-297

  Plourde, Lucie ^a   Congalton, Russell G ^a  

^a UNIVERSITY OF NEW HAMPSHIRE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA REDUCTION; FORESTRY; MAPS; SAMPLING;

SAMPLE PLACEMENT;

REMOTE SENSING;

ACCURACY ASSESSMENT; ERROR ANALYSIS; MAPPING; PIXEL; REMOTE SENSING; SAMPLING;

FORESTS; MAPS; REMOTE SENSING; SAMPLING;

EID: 0037334607     PISSN: 00991112     EISSN: None     Source Type: Journal    
DOI: 10.14358/PERS.69.3.289     Document Type: Review

References (19)

1. Card, D., 1982. Using known map category marginal frequencies to improve estimates of thematic map accuracy, Photogrammetric Engineering & Remote Sensing, 48(3):431-439.
2. Chuvieco, E., and R.G. Congalton, 1988. Using cluster analysis to improve the selection of training statistics in classifying remotely sensed data, Photogrammetric Engineering & Remote Sensing, 54(9):1275-1281.
3. Congalton, R.G., 1988. A comparison of sampling schemes used in generating error matrices for assessing the accuracy of maps generated from remotely sensed data, Photogrammetric Engineering & Remote Sensing, 54(5):593-600.
4. _, 1991. A review of assessing the accuracy of classifications of remotely sensed data, Remote Sensing of Environment, 37:35-46.
5. Congalton, R.G., R.G. Oderwald, and R.A. Mead, 1983. Assessing Landsat classification accuracy using discrete multivariate statistical techniques, Photogrammetric Engineering & Remote Sensing, 49(12):1671-1678.
6. Congalton, R.G., and K. Green, 1999. Assessing the Accuracy of Remotely Sensed Data: Principles and Practices, Lewis Publishers, Boca Raton, Florida, 137 p.
7. Fitzpatrick-Lins, K., 1981. Comparison of sampling procedures and data analysis for a land-use and land-cover map, Photogrammetric Engineering & Remote Sensing, 47(3):343-351.
8. Ginevan, M.E., 1979. Testing land-use map accuracy: Another look, Photogrammetric Engineering & Remote Sensing, 45(10):1371-1377.
9. Hord, R.M., and W. Brooner, 1976. Land-use map accuracy criteria, Photogrammetric Engineering & Remote Sensing, 42(5):671-677.
10. Hudson, W.D., and C.W. Ramm, 1987. Correct formulation of the Kappa coefficient of agreement, Photogrammetric Engineering & Remote Sensing, 53(4):421-422.
11. Irland, L.C., 1982. Wildlands and Woodlots: The Story of New Englund's Forests, University Press of New England, Hanover, New Hampshire, 206 p.
12. Klöditz, C., A. van Boxtel, E. Carfagna, and W. van Deursen, 1998. Estimating the accuracy of coarse scale classification using high scale information, Photogrammetric Engineering & Remote Sensing, 64(2):127-133.
13. Ma, Z., and R.L. Redmond, 1995. Tau coefficients for accuracy assessment of classification of remote sensing data, Photogrammetric Engineering & Remote Sensing, 61(4):435-439.
14. Pugh, S.A., and R.G. Congalton, 2001. Applying spatial autocorrelation analysis to evaluate error in New England forest cover type maps derived from Landsat Thematic Mapper data, Photogrammetric Engineering & Remote Sensing, 67(5):613-620.
15. Romesburg, H.C., 1984. Cluster Analysis for Researchers, Lifetime Learning Publications, Belmont, California, 334 p.
16. Stehman, S., 1992. Comparison of systematic and random sampling for estimating the accuracy of maps generated from remotely sensed data, Photogrammetric Engineering & Remote Sensing, 58(9):1343-1350.
17. _, 1996. Estimating the Kappa coefficient and its variance under stratified random sampling, Photogrammetric Engineering & Remote Sensing, 62(4):401-402.
18. _, 1999. Comparing thematic maps based on map value, International Journal of Remote Sensing, 20(12):2347-2366.
19. Story, M., and R.G. Congalton, 1986. Accuracy assessment: a user's perspective, Photogrammetric Engineering & Remote Sensing, 52(3):397-399.