Uncertainties of mapping aboveground forest carbon due to plot locations using national forest inventory plot and remotely sensed data

Guangxing Wang, Maozhen Zhang, George Z. Gertner, Tonny Oyana, Ronald E. McRoberts, Hongli Ge

Research output: Contribution to journalArticle

30 Citations (Scopus)

Abstract

Forest carbon sinks significantly contribute to mitigation of atmospheric concentrations of carbon dioxide. Thus, estimating forest carbon is becoming important to develop policies for mitigating climate change and trading carbon credits. However, a great challenge is how to quantify uncertainties in estimation of forest carbon. This study investigated uncertainties of mapping aboveground forest carbon due to location errors of sample plots for Lin-An County of China. National forest inventory plot data and Landsat TM images were combined using co-simulation algorithm. The findings show that randomly perturbing plot locations within 10 distance intervals statistically did not result in biased population mean predictions of aboveground forest carbon at a significant level of 0.05, but increased root mean square errors of the maps. The perturbations weakened spatial autocorrelation of aboveground forest carbon and its correlation with spectral variables. The perturbed distances of 800 m or less did not obviously change the spatial distribution of predicted values. However, when the perturbed distances were 1600 m or larger, the correlation coefficients of the predicted values from the perturbed locations with those from the true plot locations statistically did not significantly differ from zero at a level of 0.05 and the spatial distributions became random.

Original languageEnglish (US)
Pages (from-to)360-373
Number of pages14
JournalScandinavian Journal of Forest Research
Volume26
Issue number4
DOIs
StatePublished - Aug 1 2011

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national forests
forest inventory
uncertainty
carbon
spatial distribution
carbon markets
emissions trading
carbon sink
pollution control
Landsat
autocorrelation
carbon sinks
Landsat thematic mapper
mitigation
carbon dioxide
perturbation
climate change
prediction
China
simulation

All Science Journal Classification (ASJC) codes

  • Forestry

Cite this

Uncertainties of mapping aboveground forest carbon due to plot locations using national forest inventory plot and remotely sensed data. / Wang, Guangxing; Zhang, Maozhen; Gertner, George Z.; Oyana, Tonny; McRoberts, Ronald E.; Ge, Hongli.

In: Scandinavian Journal of Forest Research, Vol. 26, No. 4, 01.08.2011, p. 360-373.

Research output: Contribution to journalArticle

Wang, Guangxing ; Zhang, Maozhen ; Gertner, George Z. ; Oyana, Tonny ; McRoberts, Ronald E. ; Ge, Hongli. / Uncertainties of mapping aboveground forest carbon due to plot locations using national forest inventory plot and remotely sensed data. In: Scandinavian Journal of Forest Research. 2011 ; Vol. 26, No. 4. pp. 360-373.
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