Prediction of forest aboveground biomass: An exercise on avoiding overfitting

Sara Silva, Vijay Ingalalli, Susana Vinga, João M.B. Carreiras, Joana B. Melo, Mauro Castelli, Leonardo Vanneschi, Ivo Gonçalves, José Caldas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Citations (Scopus)

Abstract

Mapping and understanding the spatial distribution of forest aboveground biomass (AGB) is an important and challenging task. This paper describes an exercise of predicting the forest AGB of Guinea-Bissau, West Africa, using synthetic aperture radar data and measurements of tree size collected in field campaigns. Several methods were attempted, from linear regression to different variants and techniques of Genetic Programming (GP), including the cutting edge geometric semantic GP approach. The results were compared between each other in terms of root mean square error and correlation between predicted and expected values of AGB. None of the methods was able to produce a model that generalizes well to unseen data or significantly outperforms the model obtained by the state-of-the-art methodology, and the latter was also not better than a simple linear model. We conclude that the AGB prediction is a difficult problem, aggravated by the small size of the available data set.

Original languageEnglish
Title of host publicationApplications of Evolutionary Computation - 16th European Conference, EvoApplications 2013, Proceedings
Pages407-417
Number of pages11
DOIs
Publication statusPublished - 5 Apr 2013
Event16th European Conference on Applications of Evolutionary Computation, EvoApplications 2013 - Vienna, Austria
Duration: 3 Apr 20135 Apr 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7835 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th European Conference on Applications of Evolutionary Computation, EvoApplications 2013
CountryAustria
CityVienna
Period3/04/135/04/13

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