Satellite-Derived Land Cover Intercomparison and Validation References
2026
Vollrath, A., Jonckheere, I., Hamilton, R., Michel, J.M. and Donegan, E., eds. 2026. Good practices in sample-based area estimation. White paper. Second edition. Rome, FAO. https://doi.org/10.4060/ce2179en
Wellington, D., Stehman, S. V., Horton, J., Pengra, B., Barber, C. P., 2026, Methodology for assessing the accuracy of long-term, annual land cover monitoring at national scale: Experiences from the Land Change Monitoring, Assessment, and Projection (LCMAP) initiative, Remote Sensing of Environment, Vol 348, 2027, 115705, ISSN
0034-4257, https://doi.org/10.1016/j.rse.2026.115705.
2025
Tyukavina, A., Stehman, S. V., Pickens, A. H., Potapov, P., & Hansen, M. C. (2025). Practical global sampling methods for estimating area and map accuracy of land cover and change. Remote Sensing of Environment, 324, 114714. https://doi.org/10.1016/j.rse.2025.114714
Skakun, S., (2025). The impact of map accuracy on area estimation with remotely sensed data within the stratified random sampling design, Remote Sensing of Environment, 326, 114805. https://doi.org/10.1016/j.rse.2025.114805.
Tyukavina, A., Stehman, S. V., Foody, G. M., Bontemps, S., See, L., Olofsson, P., Tsendbazar, N. E., Radoux, J., Komarova, A., Serre, B. M., Song, X. P., d'Andrimont, R., Koren, G., Potapov. P., Bullock, E. L., Campbell., P., de Bruin, &., Defourny, P., Friedl., M. A., Fritz., S., Hansen, M. C., Herold, M.,Lamarche, C., Lesiv, M., Mané, L., Meroni, M., Nickeson, J. E., Pelletier, F., Pickens, A., Reiche, J.,Schepaschenko, D., Tarrio, K., Verhegghen, A., Woodcock, C., Xiao, X. (2025). Land Cover and Change Map Accuracy Assessment and Area Estimation Good Practices Protocol. Version 1.1. In A. Tyukavina, S. V. Stehman, G. Foody, S. Bontemps, A. Komarova, N. E. Tsendbazar and J. Nickeson (Eds.), Good Practices for Satellite Derived Land Product Validation, (p. 188): Land Product Validation Subgroup (WGCV/CEOS), doi:10.5067/doc/ceoswgcv/lpv/lc.001
2024
Jonckheere, I., Hamilton, R., Michel, J. M., & Donegan, E. (2024). Good practices in sample-based area estimation. Food & Agriculture Org. https://doi.org/10.4060/cc9276en
Xu, Panpan, Nandin-Erdene Tsendbazar, Martin Herold, Sytze De Bruin, Myke Koopmans, Tanya Birch, Sarah Carter et al. "Comparative validation of recent 10 m-resolution global land cover maps." Remote Sensing of Environment 311 (2024): 114316. https://doi.org/10.1016/j.rse.2024.114316
Foody, G. M. (2023). Challenges in the real world use of classification accuracy metrics: From recall and precision to the Matthews correlation coefficient. Plos one, 18(10), e0291908.
2023
Valle, D., Izbicki, R., & Leite, R. V. (2023). Quantifying uncertainty in land-use land-cover classification using conformal statistics. Remote Sensing of Environment, 295, 113682.
Foody, G. M. (2023). Challenges in the real world use of classification accuracy metrics: From recall and precision to the Matthews correlation coefficient. Plos one, 18(10), e0291908.
2022
Stehman, S. V., & Xing, D. (2022). Confidence intervals for proportion of area estimated from a stratified random sample. Remote sensing of environment, 280, 113193.
Stehman, S. V., Mousoupetros, J., McRoberts, R. E., Næsset, E., Pengra, B. W., Xing, D., & Horton, J. A. (2022). Incorporating interpreter variability into estimation of the total variance of land cover area estimates under simple random sampling. Remote Sensing of Environment, 269, 112806.
2021
Verhegghen, A.,d'Andrimont, R.; Waldner, F.; Van der Velde, M. (2021). Accuracy assessment of the first EU-wide crop type map with LUCAS data. 2021 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Brussels, Belgium, 11-16 July 2021.
2020
Olofsson, P., Arévalo, P., Espejo, A. B., Green, C., Lindquist, E., McRoberts, R. E., & Sanz, M. J. (2020). Mitigating the effects of omission errors on area and area change estimates. Remote Sensing of Environment, 236, 111492.
Foody, G.M., (2020). Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification. Remote Sensing of Environment, 239, p.111630.
2019
Arévalo, P., Olofsson, P. and Woodcock, C. E. (2019). Continuous monitoring of land change activities and post-
disturbance dynamics from Landsat time series: A test methodology for REDD+ reporting. Remote Sensing of Environment, 111051
Stehman, S. V. & Foody, G. M. (2019). Key issues in rigorous accuracy assessment of land cover products. Remote Sensing of Environment, 231: 111199.
2017
Waldner, F. and Defourny, P. (2017). Where can pixel counting area estimates meet user-defined accuracy requirements? International Journal of Applied Earth Observation and Geoinformation, 60: 1-10
2016
Comber, A., Brunsdon, C., Charlton, M. and Harris, P. (2016). Geographically weighted correspondence matrices for local error reporting and change analyses: mapping the spatial distribution of errors and change. Remote Sensing Letters, 8(3): 234-243.
Tsendbazar, N. E., de Bruin, S. and Herold, M. (2016). Assessing global land cover reference datasets for different user communities. ISPRS Journal of Photogrammetry and Remote Sensing, 103: 93-114
Tsendbazar, N.E., de Bruin, S., Mora, B., Schouten, L., Herold, M. (2016). Comparative assessment of thematic accuracy of GLC maps for specific applications using existing reference data, International Journal of Applied Earth Observation and Geoinformation, 44 (2016) 124-135.
2015
Pengra, B., Long, J., Dahal, D., Stehman, S.V., Loveland, T.R. (2015). A global reference database from very high resolution commercial satellite data and methodology for application to Landsat derived 30 m continuous field tree cover data, Remote Sensing of Environment, Volume 165, Pages 234-248.
Wagner, J. E. and Stehman, S. V. (2015). Optimizing sample size allocation to strata for estimating area and map accuracy. Remote Sensing of Environment, 168: 126-133.
2014
Olofsson, P., Foody, G. M., Herold, M., Stehman, S. V., Woodcock, C. E. and Wulder, M. A. (2014). Good Practices for Assessing Accuracy and Estimating Area of Land Change. Remote Sensing of Environment, 148:42-57.
Tsendbazar, N. E., S. de Bruin, M. Herold (2014). Assessing global land cover reference datasets for different user communities. ISPRS Journal of Photogrammetry and Remote Sensing, DOI: 10.1016/j.isprsjprs.2014.02.008
Stehman, S. V. (2014). Estimating area and map accuracy for stratified random sampling when the strata are different from the map classes. International Journal of Remote Sensing 35.13: 4923-4939.
2013
Olofsson, P., G.M. Foody, S.V. Stehman, and C.E. Woodcock (2013). Making better use of accuracy data in land
change studies: estimating accuracy and area and quantifying uncertainty using stratified estimation. Remote
Sensing of Environment, 129:122-131.
Gallego, F. J. and Stibig, H. J. (2013). Area estimation from a sample of satellite images: the impact of stratification on the clustering efficiency. International Journal of Applied Earth Observation and Geoinformation, 22: 139-146.
2012
Olofsson, P., Stehman, S.V., Woodcock, C.E., Friedl, M.A. Sulla-Menashe, D., Sibley, A.M., Newell, J.D. and M. Herold
(2012). A global land cover validation data set, I: Fundamental Design principles, International Journal of Remote
Sensing 33(18):5768-5788.
Stehman, S.V., Olofsson, P., Woodcock, C.E., M. Herold , and M.A. Friedl, (2012). A global land cover validation
data set, II: Augmenting a stratified sampling design to estimate accuracy by region and land-cover class, IJRS,
33(22), pp. 6975-6993.
Bontemps, S.; Herold, M.; Kooistra, L.; van Groenestijn, A.; Hartley, A.; Arino, O.; Moreau, I.; Defourny, P. (2012). Revisiting land cover observations to address the needs of the climate modeling community, Biogeosciences
p. 2145-2157.
Defourny, P.; Mayaux, P.; Herold, M.; Bontemps, S. (2012) Global land-cover map validation experiences: Toward
the characterization of uncertainty, In: Remote Sensing of Land Use and Land Cover: Principles and Applications
Giri, C.P., Boca Raton, Taylor & Francis series remote sensing applications: CRC Press, p. 207-224.
Herold, M.; Gregorio, A. di (2012) Evaluating land-cover legends using the UN Land-Cover Classification System, In:
Remote Sensing of Land Use and Land Cover: Principles and Applications / Giri, C.P., Boca Raton: CRC Press,
Taylor & Francis series remote sensing applications, p. 65-90.
Herold, M.; Kooistra, L.; Groenestijn, A. van; Defourny, P.; Schmullius, C.; Vasileios, K.; Arino, O. (2012) Building
saliency, legitimacy, and credibility toward operational global and regional land-cover observations and
assessments in the context of international processes and observing essential climate variables, In: Remote
Sensing of Land Use and Land Cover: Principles and Applications / Giri, C.P., Boca Raton: CRC Press, Taylor &
Francis series remote sensing applications, p. 397-414.
2006
Strahler, A. H., Boschetti, L., Foody, G. M., Friedl, M. A., Hansen, M. C., Herold, M., Mayaux, P., Morisette, J. T., Stehman, S. V. and Woodcock, C. E. (2006). Global land cover validation: Recommendations for evaluation and accuracy assessment of global land cover maps. European Communities, Luxembourg, 51(4).
