Identifying landscape hot and cold spots of soil greenhouse gas fluxes by combining field measurements and remote sensing data
<p>Upscaling chamber measurements of soil greenhouse gas (GHG) fluxes from point scale to landscape scale remain challenging due to the high variability in the fluxes in space and time. This study measured GHG fluxes and soil parameters at selected point locations (<span class="inline-...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2023-12-01
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| Series: | Biogeosciences |
| Online Access: | https://bg.copernicus.org/articles/20/5029/2023/bg-20-5029-2023.pdf |
| _version_ | 1797385959616020480 |
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| author | E. Gachibu Wangari R. Mwangada Mwanake T. Houska D. Kraus G. M. Gettel G. M. Gettel R. Kiese L. Breuer L. Breuer K. Butterbach-Bahl K. Butterbach-Bahl |
| author_facet | E. Gachibu Wangari R. Mwangada Mwanake T. Houska D. Kraus G. M. Gettel G. M. Gettel R. Kiese L. Breuer L. Breuer K. Butterbach-Bahl K. Butterbach-Bahl |
| author_sort | E. Gachibu Wangari |
| collection | DOAJ |
| description | <p>Upscaling chamber measurements of soil greenhouse gas (GHG) fluxes from point scale to landscape scale remain challenging due to the high variability in the fluxes in space and time. This study measured GHG fluxes and soil parameters at selected point locations (<span class="inline-formula"><i>n</i>=268</span>), thereby implementing a stratified sampling approach on a mixed-land-use landscape (<span class="inline-formula">∼5.8</span> <span class="inline-formula">km<sup>2</sup></span>). Based on these field-based measurements and remotely sensed data on landscape and vegetation properties, we used random forest (RF) models to predict GHG fluxes at a landscape scale (1 m resolution) in summer and autumn. The RF models, combining field-measured soil parameters and remotely sensed data, outperformed those with field-measured predictors or remotely sensed data alone. Available satellite data products from Sentinel-2 on vegetation cover and water content played a more significant role than those attributes derived from a digital elevation model, possibly due to their ability to capture both spatial and seasonal changes in the ecosystem parameters within the landscape. Similar seasonal patterns of higher soil/ecosystem respiration (SR/ER–<span class="inline-formula">CO<sub>2</sub></span>) and nitrous oxide (<span class="inline-formula">N<sub>2</sub>O</span>) fluxes in summer and higher methane (<span class="inline-formula">CH<sub>4</sub></span>) uptake in autumn were observed in both the measured and predicted landscape fluxes. Based on the upscaled fluxes, we also assessed the contribution of hot spots to the total landscape fluxes. The identified emission hot spots occupied a small landscape area (7 % to 16 %) but accounted for up to 42 % of the landscape GHG fluxes. Our study showed that combining remotely sensed data with chamber measurements and soil properties is a promising approach for identifying spatial patterns and hot spots of GHG fluxes across heterogeneous landscapes. Such information may be used to inform targeted mitigation strategies at the landscape scale.</p> |
| first_indexed | 2024-03-08T22:01:52Z |
| format | Article |
| id | doaj.art-2d92b3e2809c437684bb1e202ae7e73f |
| institution | Directory Open Access Journal |
| issn | 1726-4170 1726-4189 |
| language | English |
| last_indexed | 2024-03-08T22:01:52Z |
| publishDate | 2023-12-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Biogeosciences |
| spelling | doaj.art-2d92b3e2809c437684bb1e202ae7e73f2023-12-19T11:09:10ZengCopernicus PublicationsBiogeosciences1726-41701726-41892023-12-01205029506710.5194/bg-20-5029-2023Identifying landscape hot and cold spots of soil greenhouse gas fluxes by combining field measurements and remote sensing dataE. Gachibu Wangari0R. Mwangada Mwanake1T. Houska2D. Kraus3G. M. Gettel4G. M. Gettel5R. Kiese6L. Breuer7L. Breuer8K. Butterbach-Bahl9K. Butterbach-Bahl10Karlsruhe Institute of Technology, Institute for Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Kreuzeckbahnstrasse 19, 82467 Garmisch-Partenkirchen, GermanyKarlsruhe Institute of Technology, Institute for Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Kreuzeckbahnstrasse 19, 82467 Garmisch-Partenkirchen, GermanyInstitute for Landscape Ecology and Resources Management (ILR), Research Centre for BioSystems, Land Use and Nutrition (iFZ), Justus Liebig University Gießen, 35392 Gießen, GermanyKarlsruhe Institute of Technology, Institute for Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Kreuzeckbahnstrasse 19, 82467 Garmisch-Partenkirchen, GermanyIHE Delft Institute for Water Education, Westvest 7, 2611 AX Delft, the NetherlandsDepartment of Ecoscience, Lake Ecology, University of Aarhus, Aarhus, DenmarkKarlsruhe Institute of Technology, Institute for Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Kreuzeckbahnstrasse 19, 82467 Garmisch-Partenkirchen, GermanyInstitute for Landscape Ecology and Resources Management (ILR), Research Centre for BioSystems, Land Use and Nutrition (iFZ), Justus Liebig University Gießen, 35392 Gießen, GermanyCentre for International Development and Environmental Research (ZEU), Justus Liebig University Gießen, Senckenbergstraße 3, 35390 Gießen, GermanyKarlsruhe Institute of Technology, Institute for Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Kreuzeckbahnstrasse 19, 82467 Garmisch-Partenkirchen, GermanyPioneer Center Land-CRAFT, Department of Agroecology, University of Aarhus, C. F. Møllers Allé 4, Building 1120, Aarhus 8000, Denmark<p>Upscaling chamber measurements of soil greenhouse gas (GHG) fluxes from point scale to landscape scale remain challenging due to the high variability in the fluxes in space and time. This study measured GHG fluxes and soil parameters at selected point locations (<span class="inline-formula"><i>n</i>=268</span>), thereby implementing a stratified sampling approach on a mixed-land-use landscape (<span class="inline-formula">∼5.8</span> <span class="inline-formula">km<sup>2</sup></span>). Based on these field-based measurements and remotely sensed data on landscape and vegetation properties, we used random forest (RF) models to predict GHG fluxes at a landscape scale (1 m resolution) in summer and autumn. The RF models, combining field-measured soil parameters and remotely sensed data, outperformed those with field-measured predictors or remotely sensed data alone. Available satellite data products from Sentinel-2 on vegetation cover and water content played a more significant role than those attributes derived from a digital elevation model, possibly due to their ability to capture both spatial and seasonal changes in the ecosystem parameters within the landscape. Similar seasonal patterns of higher soil/ecosystem respiration (SR/ER–<span class="inline-formula">CO<sub>2</sub></span>) and nitrous oxide (<span class="inline-formula">N<sub>2</sub>O</span>) fluxes in summer and higher methane (<span class="inline-formula">CH<sub>4</sub></span>) uptake in autumn were observed in both the measured and predicted landscape fluxes. Based on the upscaled fluxes, we also assessed the contribution of hot spots to the total landscape fluxes. The identified emission hot spots occupied a small landscape area (7 % to 16 %) but accounted for up to 42 % of the landscape GHG fluxes. Our study showed that combining remotely sensed data with chamber measurements and soil properties is a promising approach for identifying spatial patterns and hot spots of GHG fluxes across heterogeneous landscapes. Such information may be used to inform targeted mitigation strategies at the landscape scale.</p>https://bg.copernicus.org/articles/20/5029/2023/bg-20-5029-2023.pdf |
| spellingShingle | E. Gachibu Wangari R. Mwangada Mwanake T. Houska D. Kraus G. M. Gettel G. M. Gettel R. Kiese L. Breuer L. Breuer K. Butterbach-Bahl K. Butterbach-Bahl Identifying landscape hot and cold spots of soil greenhouse gas fluxes by combining field measurements and remote sensing data Biogeosciences |
| title | Identifying landscape hot and cold spots of soil greenhouse gas fluxes by combining field measurements and remote sensing data |
| title_full | Identifying landscape hot and cold spots of soil greenhouse gas fluxes by combining field measurements and remote sensing data |
| title_fullStr | Identifying landscape hot and cold spots of soil greenhouse gas fluxes by combining field measurements and remote sensing data |
| title_full_unstemmed | Identifying landscape hot and cold spots of soil greenhouse gas fluxes by combining field measurements and remote sensing data |
| title_short | Identifying landscape hot and cold spots of soil greenhouse gas fluxes by combining field measurements and remote sensing data |
| title_sort | identifying landscape hot and cold spots of soil greenhouse gas fluxes by combining field measurements and remote sensing data |
| url | https://bg.copernicus.org/articles/20/5029/2023/bg-20-5029-2023.pdf |
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