The impact of imperfect ground reference data on the accuracy of land cover change estimation

International Journal of Remote Sensing

Volumn 30, Issue 12, 2009, Pages 3275-3281

  Foody, Giles M ^a  

^a UNIVERSITY OF NOTTINGHAM   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

REMOTE SENSING;

ACCURATE ESTIMATION; CHANGE DETECTION; HIGH-ACCURACY; IMPERFECT GROUND; LAND-COVER CHANGE; REFERENCE DATA;

ERROR DETECTION;

ACCURACY ASSESSMENT; DATA QUALITY; LAND COVER; LANDSCAPE CHANGE; REMOTE SENSING;

EID: 70449441439     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431160902755346     Document Type: Article

References (19)

1. ANDERSON, J.R., 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, Geological Survey Professional Paper 964 (Washington D.C.: US Geological Survey).
2. CONGALTON, R.G. and GREEN, K., 1999, Assessing the Accuracy of Remotely Sensed Data: Principles and Practices (Boca Raton, FL: Lewis Publishers).
3. FOODY, G.M., 2002, Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80, pp. 185-201.
4. FOODY, G.M., 2008, Harshness in image classification accuracy assessment. International Journal of Remote Sensing, 29, pp. 3137-3158.
5. FOODY, G.M. and DOAN, H.T.X., 2007, Variability in soft classification prediction and its implications for sub-pixel scale change detection and super resolution mapping. Photogrammetric Engineering and Remote Sensing, 73, pp. 923-933.
6. FRITZ, S. and SEE, L., 2008, Identifying and quantifying uncertainty and spatial disagreement in the comparison of global land cover for different applications. Global Change Biology, 14, pp. 1057-1075.
7. HAGEN, A., 2003, Fuzzy set approach to assessing similarity of categorical maps. International Journal of Geographical Information Systems, 17, pp. 235-249.
8. JOHNSON, E.W. and ROSS, J., 2008, Quantifying error in aerial survey data. Australian Forestry, 71, pp. 216-222.
9. KHORRAM, S. (Ed.), 1999, Accuracy Assessment of Remote Sensing-Derived Change Detection (Bethesda, MD: American Society for Photogrammetry and Remote Sensing).
10. LU, D. and WENG, Q., 2007, A survey of image classification methods and techniques for improving classification performance. International Journal of Remote Sensing, 28, pp. 823-870.
11. MANN, S. and ROTHLEY, K.D., 2006, Sensitivity of Landsat/IKONOS accuracy comparison to errors in photointerpreted reference data and variations in test point sets. International Journal of Remote Sensing, 27, pp. 5027-5036.
12. MUNDIA, C.N. and ANIYA, M., 2005, Analysis of land use/cover changes and urban expansion of Nairobi city using remote sensing and GIS. International Journal of Remote Sensing, 26, pp. 2831-2849.
13. PRISLEY, S.P. and SMITH, J.L., 1987, Using classification error matrices to improve the accuracy of weighted land-cover models. Photogrammetric Engineering and Remote Sensing, 53, pp. 1259-1263.
14. SALA, O.E., CHAPIN, F.S., ARMESTO, J.J., BERLOW, E., BLOOMFIELD, J., DIRZO, R., HUBERSANWALD, E., HUENNEKE, L.F., JACKSON, R.B., KINZIG, A., LEEMANS, R., LODGE, D.M., MOONEY, H.A., OESTERHELD, M., POFF, N.L., SYKES, M.T., WALKER, B.H., WALKER, M. and WALL, D.H., 2000, Global biodiversity scenarios for the year 2100. Science, 287, pp. 1770-1774.
15. STAQUET, M., ROZENCWEIG, M., LEE, Y.J. and MUGGIA, F.M., 1981, Methodology for the assessment of new dichotomous diagnostic tests. Journal of Chronic Diseases, 34, pp. 599-610.
16. VALENSTEIN, P.N., 1990, Evaluating diagnostic tests with imperfect standards. American Journal of Clinical Pathology, 93, pp. 252-258.
17. VAN OORT, P.A.J., 2005, Improving land cover change estimates by accounting for classification errors. International Journal of Remote Sensing, 26, pp. 3009-3024.
18. VAN OORT, P.A.J., 2007, Interpreting the change detection error matrix. Remote Sensing of Environment, 108, pp. 1-8.
19. WILKINSON, G.G., 2005, Results and implications of a study of fifteen years of satellite image classification experiments. IEEE Transactions on Geoscience and Remote Sensing, 43, pp. 433-440.