Articles | Volume 20, issue 24
https://doi.org/10.5194/bg-20-5029-2023
https://doi.org/10.5194/bg-20-5029-2023
Research article
 | 
19 Dec 2023
Research article |  | 19 Dec 2023

Identifying landscape hot and cold spots of soil greenhouse gas fluxes by combining field measurements and remote sensing data

Elizabeth Gachibu Wangari, Ricky Mwangada Mwanake, Tobias Houska, David Kraus, Gretchen Maria Gettel, Ralf Kiese, Lutz Breuer, and Klaus Butterbach-Bahl

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Cited articles

Adjuik, T. A. and Davis, S. C.: Machine learning approach to simulate soil CO2 fluxes under cropping systems, Agronomy, 12, 197, https://doi.org/10.3390/agronomy12010197, 2022. 
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Barton, L., McLay, C. D. A., Schipper, L. A., and Smith, C. T.: Annual denitrification rates in agricultural and forest soils: a review, Aust. J. Soil Res., 37, 1073–1094, https://doi.org/10.1071/SR99009, 1999. 
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Short summary
Agricultural landscapes act as sinks or sources of the greenhouse gases (GHGs) CO2, CH4, or N2O. Various physicochemical and biological processes control the fluxes of these GHGs between ecosystems and the atmosphere. Therefore, fluxes depend on environmental conditions such as soil moisture, soil temperature, or soil parameters, which result in large spatial and temporal variations of GHG fluxes. Here, we describe an example of how this variation may be studied and analyzed.
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