Design-based mapping of land use/land cover classes with bootstrap estimation of precision by nearest-neighbour interpolation

Author:

Marcelli Agnese1,Di Biase Rosa Maria2,Corona Piermaria3,Stehman Stephen V.4,Fattorini Lorenzo5

Affiliation:

1. Department for Innovation in Biological, Agro-food and Forest Systems, University of Tuscia

2. Department of Sociology and Social Research, University of Milano Bicocca

3. CREA, Research Centre for Forestry and Wood

4. Department of Sustainable Resources Management, SUNY College of Environmental Science and Forestry

5. Department of Economic and Statistics, University of Siena

Publisher

Institute of Mathematical Statistics

Subject

Statistics, Probability and Uncertainty,Modeling and Simulation,Statistics and Probability

Reference44 articles.

1. AL-DOSKI, J., MANSOR, S. B., SAN, H. P. and KHUZAIMAH, Z. (2020). Land cover mapping using remote sensing data. Am. J. Geogr. Inf. Syst. 9 33–45.

2. AUCH, R. F., WELLINGTON, D. F., TAYLOR, J. L., STEHMAN, S. V., TOLLERUD, H. J., BROWN, J. F., LOVELAND, T. R., PENGRA, B. W., HORTON, J. A. et al. (2022). Conterminous United States land-cover change (1985–2016): New insights from annual time series. Land 11 298.

3. BARABESI, L. (2003). A Monte Carlo integration approach to Horvitz–Thompson estimation in replicated environmental designs. Metron LXI 355–374.

4. BARABESI, L., FRANCESCHI, S. and MARCHESELLI, M. (2012). Properties of design-based estimation under stratified spatial sampling with application to canopy coverage estimation. Ann. Appl. Stat. 6 210–228.

5. BROWN, J. F., TOLLERUD, H. J., BARBER, C. P., ZHOU, Q., DWYER, J. L., VOGELMAN, J. E., LOVELAND, T. R., WOODCOK, C. E., STEHMAN, S. V. et al. (2020). Lessons learned implementing an operational continuous United States national land change monitoring capability: The land change monitoring, assessment, and projection (LCMAP) approach. Remote Sens. Environ. 238 111356.

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