Document Type
Article
Publication Date
2-3-2022
Abstract
Carbon monitoring is critical for the reporting and verification of carbon stocks and change. Remote sensing is a tool increasingly used to estimate the spatial heterogeneity, extent and change of carbon stocks within and across various systems. We designate the use of the term wet carbon system to the interconnected wetlands, ocean, river and streams, lakes and ponds, and permafrost, which are carbon-dense and vital conduits for carbon throughout the terrestrial and aquatic sections of the carbon cycle. We reviewed wet carbon monitoring studies that utilize earth observation to improve our knowledge of data gaps, methods, and future research recommendations. To achieve this, we conducted a systematic review collecting 1622 references and screening them with a combination of text matching and a panel of three experts. The search found 496 references, with an additional 78 references added by experts. Our study found considerable variability of the utilization of remote sensing and global wet carbon monitoring progress across the nine systems analyzed. The review highlighted that remote sensing is routinely used to globally map carbon in mangroves and oceans, whereas seagrass, terrestrial wetlands, tidal marshes, rivers, and permafrost would benefit from more accurate and comprehensive global maps of extent. We identified three critical gaps and twelve recommendations to continue progressing wet carbon systems and increase cross system scientific inquiry.
Publication Title
Environmental Research Letters
Recommended Citation
Campbell, A.,
Fatoyinbo, T.,
Charles, S.,
Bourgeau-Chavez, L.,
Goes, J.,
Gomes, H.,
Halabisky, M.,
Holmquist, S.,
Lohrenz, S.,
Mitchell, C.,
Moskal, L.,
Poulter, B.,
Qiu, H.,
Resende De Sousa, C.,
&
Sayers, M.
(2022).
A review of carbon monitoring in wet carbon systems using remote sensing.
Environmental Research Letters,
17(2).
http://doi.org/10.1088/1748-9326/ac4d4d
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/15843
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Version
Publisher's PDF
Publisher's Statement
© 2022 The Author(s). Published by IOP Publishing Ltd. Publisher’s version of record: https://doi.org/10.1088/1748-9326/ac4d4d