Estimating area from an accuracy assessment error matrix

Remote Sensing of Environment

Volumn 132, Issue , 2013, Pages 202-211

  Stehman, Stephen V ^a  

^a STATE UNIVERSITY OF NEW YORK   (United States)

Author keywords

Design based inference; Difference estimator; Model assisted estimation; Poststratified estimator; Sampling

Indexed keywords

ACCURACY ASSESSMENT; AREA ESTIMATION; AUXILIARY VARIABLES; CLASSIFICATION ERRORS; DESIGN-BASED INFERENCE; DIFFERENCE ESTIMATOR; ERROR MATRICES; ESTIMATED ERROR; LAND COVER; LAND-COVER CHANGE; OVERALL ACCURACIES; POSTSTRATIFIED ESTIMATOR; REGRESSION ESTIMATORS; REMOTELY SENSED DATA; SAMPLE SIZES; SAMPLING DESIGN; SIMPLE APPROACH; SIMPLE RANDOM SAMPLE; SIMPLE RANDOM SAMPLING; SIMULATION STUDIES; STRATIFIED RANDOM SAMPLING;

EQUIVALENCE CLASSES; LANDFORMS; MATRIX ALGEBRA; REMOTE SENSING; SAMPLING;

ESTIMATION;

DESIGN; ERROR ANALYSIS; ESTIMATION METHOD; LAND COVER; MAPPING METHOD; MATRIX; NUMERICAL MODEL; REMOTE SENSING; SAMPLING; SATELLITE DATA;

EID: 84874354814     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2013.01.016     Document Type: Article

References (23)

1. Baffetta F., Fattorini L., Franceschi S., Corona P. Design-based approach to k-nearest neighbours technique for coupling field and remote sensed data in forest surveys. Remote Sensing of Environment 2009, 113:463-475.
2. Card D.H. Using known map category marginal frequencies to improve estimates of thematic map accuracy. Photogrammetric Engineering and Remote Sensing 1982, 48:431-439.
3. Cochran W.G. Sampling techniques 1977, John Wiley & Sons, New York. 3rd ed.
4. Czaplewski R.L. Misclassification bias in areal estimates. Photogrammetric Engineering and Remote Sensing 1992, 58:189-192.
5. Czaplewski R.L. Recursive restriction estimation: an alternative to post-stratification in surveys of land and forest cover 2010, U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, CO, (32 pp. http://treesearch/pubs/36116).
6. Czaplewski R.L. Complex sample survey estimation in static state-space. Gen. Tech. Rep. RMRS-GTR-239 2010, U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fort Collins, CO, (124 pp.).
7. Gallego F.J. Remote sensing and land cover area estimation. International Journal of Remote Sensing 2004, 25:3019-3047.
8. Gregoire T.G., Ståhl G., Næsset E., Gobakken T., Nelson R., Holm S. Model-assisted estimation of biomass in a LiDAR sample survey in Hedmark County, Norway. Canadian Journal of Forest Research 2011, 41:83-95.
9. Kalton G. Survey sampling. Encyclopedia of statistical sciences 1988, Vol. 9:111-119. Wiley, New York.
10. Lohr S.L. Sampling: Design and analysis 2010, Brooks/Cole, Boston, MA. 2nd ed.
11. McRoberts R.E. Probability- and model-based approaches to inference for proportion forest using satellite imagery as ancillary data. Remote Sensing of Environment 2010, 114:1017-1025.
12. McRoberts R.E. Satellite image-based maps: Scientific inference or pretty pictures?. Remote Sensing of Environment 2011, 115:715-724.
13. McRoberts R.E., Walters B.F. Statistical inference for remote sensing-based estimates of net deforestation. Remote Sensing of Environment 2012, 124:394-401.
14. Olofsson P., Foody G.M., Stehman S.V., Woodcock C.E. Making better use of accuracy data in land change studies: Estimating accuracy and area and quantifying uncertainty using stratified estimation. Remote Sensing of Environment 2013, 129:122-131.
15. Särndal C.E., Swensson B., Wretman J. Model-assisted survey sampling 1992, Springer-Verlag, New York.
16. Stehman S.V. Comparing estimators of gross change derived from complete coverage mapping versus statistical sampling of remotely sensed data. Remote Sensing of Environment 2005, 96:466-474.
17. Stehman S.V. Model-assisted estimation as a unifying framework for estimating the area of land cover and land-cover change from remote sensing. Remote Sensing of Environment 2009, 113:2455-2462.
18. Stehman S.V. Sampling designs for accuracy assessment of land cover. International Journal of Remote Sensing 2009, 30:5243-5272.
19. Stehman S.V., Selkowitz D.J. A spatially stratified, multi-stage cluster sampling design for assessing accuracy of the Alaska (USA) National Land-Cover Data (NLCD). International Journal of Remote Sensing 2010, 31:1877-1896.
20. Strahler A.H., Boschetti L., Foody G.M., Friedl M.A., Hansen M.C., et al. Global land cover validation: Recommendations for evaluation and accuracy assessment of global land cover maps. EUR 22156 EN - DG 2006, Office for Official Publications of the European Communities, Luxembourg, (48 pp.).
21. Vibrans A.C., McRoberts R.E., Moser P., Nicoletti A.L. Using satellite image-based maps and ground inventory data to estimate the area of the remaining Atlantic forest in the Brazilian state of Santa Catarina. Remote Sensing of Environment 2013, 130:87-95.
22. Wickham J.D., Stehman S.V., Fry J.A., Smith J.H., Homer C.G. Thematic accuracy of the NLCD 2001 land cover for the conterminous United States. Remote Sensing of Environment 2010, 114:1286-1296.
23. Zimmerman P.L., Housman I.W., Perry C.H., Chastain R.A., Webb J.B., Finco M.V. An accuracy assessment of forest disturbance mapping in the western Great Lakes. Remote Sensing of Environment 2013, 128:176-185.