Assessing the effect of ensemble learning algorithms and validation approach on estimating forest aboveground biomass: a case study of natural secondary forest in Northeast China

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Pubblicato in:	Geo-Spatial Information Science vol. 28, no. 2 (Apr 2025), p. 609
Autore principale:	Jin, Hungil
Altri autori:	Zhao, Yinghui, Pak, Unil, Zhen, Zhen, So, Kumryong
Pubblicazione:	Taylor & Francis Ltd.
Soggetti:	China Carbon cycle Accuracy Landsat Artificial neural networks Climate change Biomass Machine learning Decision trees Airborne lasers Forest biomass Support vector machines Prediction models National forests Algorithms Ensemble learning Estimation Remote sensing Regional analysis Environmental
Accesso online:	Citation/Abstract Full Text - PDF
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