Using single- and multi-target regression trees and ensembles to model a compound index of vegetation condition

Dragi Kocev, Sašo Džeroski, Matt D. White, Graeme R. Newell and Peter Griffioen

Ecological Modelling, 2009, vol. 220, issue 8, 1159-1168

Abstract: An important consideration in conservation and biodiversity planning is an appreciation of the condition or integrity of ecosystems. In this study, we have applied various machine learning methods to the problem of predicting the condition or quality of the remnant indigenous vegetation across an extensive area of south-eastern Australia—the state of Victoria. The field data were obtained using the ‘habitat hectares’ approach. This rapid assessment technique produces multiple scores that describe the condition of various attributes of the vegetation at a given site. Multiple sites were assessed and subsequently circumscribed with GIS and remote-sensed data.

Keywords: Multi-target prediction; Ensemble methods; Regression trees; Indigenous vegetation; Vegetation quality/condition (search for similar items in EconPapers)
Date: 2009
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Citations: View citations in EconPapers (16)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:220:y:2009:i:8:p:1159-1168

DOI: 10.1016/j.ecolmodel.2009.01.037

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