Dealing with clustered samples for assessing map accuracy by cross-validation-Reference-Cited by-同舟云学术

Dealing with clustered samples for assessing map accuracy by cross-validation

Published:2022-07 Issue: Volume:69 Page:101665
ISSN:1574-9541
Container-title:Ecological Informatics
language:en
Short-container-title:Ecological Informatics

Author:

de Bruin Sytze,Brus Dick J.,Heuvelink Gerard B.M.,van Ebbenhorst Tengbergen Tom,Wadoux Alexandre M.J-C.

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computer Science Applications,Ecological Modeling,Modeling and Simulation,Ecology,Ecology, Evolution, Behavior and Systematics

Reference56 articles.

1. An assessment of forest biomass maps in Europe using harmonized national statistics and inventory plots;Avitabile;For. Ecol. Manag.,2018

2. Spatial Point Patterns: Methodology and Applications with R;Baddeley,2016

3. No unbiased estimator of the variance of K-fold cross-validation;Bengio;J. Mach. Learn. Res.,2004

4. Spatial Cross-Validation and Bootstrap for the Assessment of Prediction Rules in Remote Sensing: The R Package Sperrorest;Brenning,2012

5. CCI Biomass Product Validation and Intercomparison Report, Year 2, Version 2;de Bruin,2020

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