A comparison of resampling methods for remote sensing classification and accuracy assessment

Remote Sensing of Environment

Volumn 208, Issue , 2018, Pages 145-153

  Lyons, Mitchell B ^a   Keith, David A ^a,b   Phinn, Stuart R ^c   Mason, Tanya J ^a   Elith, Jane ^d  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

^b OFFICE OF ENVIRONMENT AND HERITAGE   (Australia)

^c UNIVERSITY OF QUEENSLAND   (Australia)

^d UNIVERSITY OF MELBOURNE   (Australia)

Author keywords

Bias; Bootstrapping; Class area proportion; Cross validation; Land cover mapping; Population parameter; Validation; Variance; Vegetation mapping

Indexed keywords

CLASSIFICATION (OF INFORMATION); DECISION TREES; MAXIMUM LIKELIHOOD; REMOTE SENSING; UNCERTAINTY ANALYSIS;

AREA PROPORTIONS; BIAS; BOOTSTRAPPING; CLASS AREA PROPORTION; CROSS VALIDATION; LAND COVER MAPPING; POPULATION PARAMETER; VALIDATION; VARIANCE; VEGETATION MAPPING;

VEGETATION MAPPING;

ACCURACY ASSESSMENT; BOOTSTRAPPING; COMPARATIVE STUDY; DATA SET; DECISION ANALYSIS; IMAGE CLASSIFICATION; LAND COVER; MAPPING METHOD; MODEL VALIDATION; NUMERICAL METHOD; PARAMETER ESTIMATION; REMOTE SENSING; SAMPLING; SAMPLING BIAS;

EID: 85042182920     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2018.02.026     Document Type: Article

References (29)

1. Brenning, A., Benchmarking classifiers to optimally integrate terrain analysis and multispectral remote sensing in automatic rock glacier detection. Remote Sens. Environ. 113:1 (2009), 239–247.
2. Brenning, A., Spatial cross-validation and bootstrap for the assessment of prediction rules in remote sensing: the R package sperrorest, Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International, 2012, IEEE, 5372–5375 (July).
3. Burgman, M.A., Lindenmayer, D.B., Elith, J., Managing landscapes for conservation under uncertainty. Ecology 86:8 (2005), 2007–2017.
4. Champagne, C., McNairn, H., Daneshfar, B., Shang, J., A bootstrap method for assessing classification accuracy and confidence for agricultural land use mapping in Canada. Int. J. Appl. Earth Obs. Geoinf. 29 (2014), 44–52.
5. Efron, B., Tibshirani, R., Improvements on cross-validation: the 632+ bootstrap method. J. Am. Stat. Assoc. 92:438 (1997), 548–560.
6. Foody, G.M., Status of land cover classification accuracy assessment. Remote Sens. Environ. 80:1 (2002), 185–201.
7. Foody, G.M., Thematic map comparison. Photogramm. Eng. Remote. Sens. 70:5 (2004), 627–633.
8. Foody, G.M., Valuing map validation: the need for rigorous land cover map accuracy assessment in economic valuations of ecosystem services. Ecol. Econ. 111 (2015), 23–28.
9. Gallaun, H., Steinegger, M., Wack, R., Schardt, M., Kornberger, B., Schmitt, U., Remote sensing based two-stage sampling for accuracy assessment and area estimation of land cover changes. Remote Sens. 7:9 (2015), 11992–12008.
10. Guisan, A., Tingley, R., Baumgartner, J.B., Naujokaitis-Lewis, I., Sutcliffe, P.R., Tulloch, A.I., Martin, T.G., Predicting species distributions for conservation decisions. Ecol. Lett. 16:12 (2013), 1424–1435.
11. Hastie, T., Tibshirani, R., Friedman, J.H., The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition. 2nd edn, 2009, Springer-Verlag, New York.
12. Hess, G.R., Bay, J.M., Generating confidence intervals for composition-based landscape indexes. Landsc. Ecol. 12:5 (1997), 309–320.
13. Hsiao, L.H., Cheng, K.S., Assessing uncertainty in LULC classification accuracy by using bootstrap resampling. Remote Sens., 8(9), 2016, 705.
14. Lyons, M., Phinn, S., Roelfsema, C., Integrating Quickbird multi-spectral satellite and field data: mapping bathymetry, seagrass cover, seagrass species and change in Moreton Bay, Australia in 2004 and 2007. Remote Sens. 3 (2011), 42–64.
15. Lyons, M.B., Phinn, S.R., Roelfsema, C.M., Long term land cover and seagrass mapping using Landsat and object-based image analysis from 1972 to 2010 in the coastal environment of South East Queensland, Australia. ISPRS J. Photogramm. Remote Sens. 71 (2012), 34–46.
16. Lyons, M., Roelfsema, C., Kovacs, E., Samper-Villarreal, J., Saunders, M., Maxwell, P., Phinn, S., Rapid monitoring of seagrass biomass using a simple linear modelling approach, in the field and from space. Mar. Ecol. Prog. Ser. 530 (2015), 1–14.
17. Lyons, M., Foster, S., Keith, D., Simultaneous vegetation classification and mapping at large spatial scales. J. Biogeogr., 2017, 10.1111/jbi.13088.
18. Mason, T.J., Keith, D.A., Letten, A.D., Detecting state changes for ecosystem conservation with long-term monitoring of species composition. Ecol. Appl. 27:2 (2017), 458–468.
19. McKenzie, D.P., Mackinnon, A.J., Péladeau, N., Onghena, P., Bruce, P.C., Clarke, D.M., McGorry, P.D., Comparing correlated kappas by resampling: is one level of agreement significantly different from another?. J. Psychiatr. Res. 30:6 (1996), 483–492.
20. McRoberts, R.E., Post-classification approaches to estimating change in forest area using remotely sensed auxiliary data. Remote Sens. Environ. 151 (2014), 149–156.
21. McRoberts, R.E., Magnussen, S., Tomppo, E.O., Chirici, G., Parametric, bootstrap, and jackknife variance estimators for the k-Nearest Neighbors technique with illustrations using forest inventory and satellite image data. Remote Sens. Environ. 115:12 (2011), 3165–3174.
22. Pontius, R.G. Jr., Millones, M., Death to Kappa: birth of quantity disagreement and allocation disagreement for accuracy assessment. Int. J. Remote Sens. 32:15 (2011), 4407–4429.
23. Nascimento, H.E., Laurance, W.F., Total aboveground biomass in central Amazonian rainforests: a landscape-scale study. For. Ecol. Manag. 168:1 (2002), 311–321.
24. Olofsson, P., Foody, G.M., Herold, M., Stehman, S.V., Woodcock, C.E., Wulder, M.A., Good practices for estimating area and assessing accuracy of land change. Remote Sens. Environ. 148 (2014), 42–57.
25. Roberts, D.R., Bahn, V., Ciuti, S., Boyce, M.S., Elith, J., Guillera-Arroita, G., Warton, D.I., Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure. Ecography 40 (2017), 913–925.
26. Roelfsema, C., Lyons, M., Dunbabin, M., Kovacs, E.M., Phinn, S., Integrating field survey data with satellite image data to improve shallow water seagrass maps: the role of AUV and snorkeller surveys?. Remote Sens. Lett. 6 (2015), 135–144.
27. Stehman, S.V., Wickham, J.D., Wade, T.G., Smith, J.H., Designing a multi-objective, multi-support accuracy assessment of the 2001 National Land Cover Data (NLCD 2001) of the conterminous United States. Photogramm. Eng. Remote. Sens. 74:12 (2008), 1561–1571.
28. Weber, K.T., Langille, J., Improving classification accuracy assessments with statistical bootstrap resampling techniques. Sci. Remote. Sens. 44:3 (2007), 237–250.
29. Zhen, Z., Quackenbush, L.J., Stehman, S.V., Zhang, L., Impact of training and validation sample selection on classification accuracy and accuracy assessment when using reference polygons in object-based classification. Int. J. Remote Sens. 34:19 (2013), 6914–6930.