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Influence of plot and sample sizes on aboveground biomass estimations in plantation forests using very high resolution stereo satellite imagery

Hosseini, Zahra; Latifi, Hooman; Naghavi, Hamed; Bakhtiarvand Bakhtiari, Siavash; Fassnacht, Fabian Ewald

Abstract (englisch):
Regular biomass estimations for natural and plantation forests are important to support sustainable forestry and
to calculate carbon-related statistics. The application of remote sensing data to estimate biomass of forests has
been amply demonstrated but there is still space for increasing the efficiency of current approaches. Here, we
investigated the influence of field plot and sample sizes on the accuracy of random forest models trained with
information derived from Pléiades very high resolution (VHR) stereo images applied to plantation forests in an
arid environment. We collected field data at 311 locations with three different plot area sizes (100, 300 and
500 m2). In two experiments, we demonstrate how plot and sample sizes influence the accuracy of biomass
estimation models. In the first experiment, we compared model accuracies obtained with varying plot sizes but
constant number of samples. In the second experiment, we fixed the total area to be sampled to account for
the additional effort to collect large field plots. Our results for the first experiment show that model performance
metrics Spearman’s r, RMSErel and RMSEnor improve from 0.61, 0.70 and 0.36 at a sample size of 24–0.79, 0.51
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Originalveröffentlichung
DOI: 10.1093/forestry/cpaa028
Zugehörige Institution(en) am KIT Institut für Geographie und Geoökologie (IFGG)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2020
Sprache Englisch
Identifikator ISSN: 0015-752X, 1464-3626
KITopen-ID: 1000124332
Erschienen in Forestry
Vorab online veröffentlicht am 24.07.2020
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