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Uncertainty issues in forest monitoring: All you wanted to know about uncertainties and never dared to askAuthor(s): Michael Köhl; Charles Scott; Daniel Plugge
Source: In: Mortenson, Leif A.; Halperin, James J.; Manley, Patricia N.; Turner, Rich L., eds. Proceedings of the international workshop on monitoring forest degradation in Southeast Asia. Gen. Tech. Rep. PSW-GTR-246. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station: p. 32
Publication Series: General Technical Report (GTR)
Station: Pacific Northwest Research Station
PDF: Download Publication (139.16 KB)
DescriptionUncertainties are a composite of errors arising from observations and the appropriateness of models. An error budget approach can be used to identify and accumulate the sources of errors to estimate change in emissions between two points in time. Various forest monitoring approaches can be used to estimate the changes in emissions due to deforestation and forest degradation. Sample-based approaches often combine remotely sensed data with probabilistic field samples to develop design-based estimates. The survey designer must choose between a host of imagery sources, sampling designs, plot designs, allometric models of tree biomass, and estimators. Each choice has implications for uncertainty and cost. We describe three general areas for improvement: 1) inventory planning, sampling design optimization, 2) technological development focused on use of imagery, and 3) tree biomass estimation.
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CitationKöhl, Michael; Scott, Charles; Plugge, Daniel. 2013. Uncertainty issues in forest monitoring: All you wanted to know about uncertainties and never dared to ask. In: Mortenson, Leif A.; Halperin, James J.; Manley, Patricia N.; Turner, Rich L., eds. Proceedings of the international workshop on monitoring forest degradation in Southeast Asia. Gen. Tech. Rep. PSW-GTR-246. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station: p. 32.
Keywordsforest degradation monitoring, Southeast Asia, climate change, carbon
- Application of a Monte Carlo framework with bootstrapping for quantification of uncertainty in baseline map of carbon emissions from deforestation in Tropical Regions
- Using a Finer Resolution Biomass Map to Assess the Accuracy of a Regional, Map-Based Estimate of Forest Biomass
- Uncertainty analysis: an evaluation metric for synthesis science
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