Selected Aspects of Carbon Stock Assessment in Aboveground Biomass

Vilém Pechanec, Lenka Štěrbová, Jan Purkyt, Marcela Prokopová, Renata Včeláková, Ondřej Cudlín, Pavel Vyvlečka, Emil Cienciala and Pavel Cudlín
Additional contact information
Vilém Pechanec: Department of Geoinformatics, Faculty of Science, Palacký University Olomouc, 17. listopadu 50, 771 46 Olomouc, Czech Republic
Lenka Štěrbová: Global Change Research Institute of the Czech Academy of Sciences Lipová 1789/9, 370 05 České Budějovice, Czech Republic
Jan Purkyt: Global Change Research Institute of the Czech Academy of Sciences Lipová 1789/9, 370 05 České Budějovice, Czech Republic
Marcela Prokopová: Global Change Research Institute of the Czech Academy of Sciences Lipová 1789/9, 370 05 České Budějovice, Czech Republic
Renata Včeláková: Global Change Research Institute of the Czech Academy of Sciences Lipová 1789/9, 370 05 České Budějovice, Czech Republic
Ondřej Cudlín: Global Change Research Institute of the Czech Academy of Sciences Lipová 1789/9, 370 05 České Budějovice, Czech Republic
Pavel Vyvlečka: Department of Geoinformatics, Faculty of Science, Palacký University Olomouc, 17. listopadu 50, 771 46 Olomouc, Czech Republic
Emil Cienciala: Global Change Research Institute of the Czech Academy of Sciences Lipová 1789/9, 370 05 České Budějovice, Czech Republic
Pavel Cudlín: Global Change Research Institute of the Czech Academy of Sciences Lipová 1789/9, 370 05 České Budějovice, Czech Republic

Land, 2022, vol. 11, issue 1, 1-16

Abstract: Given the significance of national carbon inventories, the importance of large-scale estimates of carbon stocks is increasing. Accurate biomass estimates are essential for tracking changes in the carbon stock through repeated assessment of carbon stock, widely used for both vegetation and soil, to estimate carbon sequestration. Objectives: The aim of our study was to determine the variability of several aspects of the carbon stock value when the input matrix was (1) expressed either as a vector or as a raster; (2) expressed as in local (1:10,000) or regional (1:100,000) scale data; and (3) rasterized with different pixel sizes of 1, 10, 100, and 1000 m. Method: The look-up table method, where expert carbon content values are attached to the mapped landscape matrix. Results: Different formats of input matrix did not show fundamental differences with exceptions of the biggest raster of size 1000 m for the local level. At the regional level, no differences were notable. Conclusions: The results contribute to the specification of best practices for the evaluation of carbon storage as a mitigation measure, as well as the implementation of national carbon inventories.

Keywords: carbon stock; degree of data detail; different space resolution; rasterization (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
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