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Schwieder M, Leitão PJ, Pinto JRR, Teixeira AMC, Pedroni F, Sanchez M, Bustamante MM, Hostert P. Landsat phenological metrics and their relation to aboveground carbon in the Brazilian Savanna. Carbon Balance Manag 2018; 13:7. [PMID: 29766371 PMCID: PMC5953907 DOI: 10.1186/s13021-018-0097-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/07/2017] [Accepted: 05/05/2018] [Indexed: 06/08/2023]
Abstract
BACKGROUND The quantification and spatially explicit mapping of carbon stocks in terrestrial ecosystems is important to better understand the global carbon cycle and to monitor and report change processes, especially in the context of international policy mechanisms such as REDD+ or the implementation of Nationally Determined Contributions (NDCs) and the UN Sustainable Development Goals (SDGs). Especially in heterogeneous ecosystems, such as Savannas, accurate carbon quantifications are still lacking, where highly variable vegetation densities occur and a strong seasonality hinders consistent data acquisition. In order to account for these challenges we analyzed the potential of land surface phenological metrics derived from gap-filled 8-day Landsat time series for carbon mapping. We selected three areas located in different subregions in the central Brazil region, which is a prominent example of a Savanna with significant carbon stocks that has been undergoing extensive land cover conversions. Here phenological metrics from the season 2014/2015 were combined with aboveground carbon field samples of cerrado sensu stricto vegetation using Random Forest regression models to map the regional carbon distribution and to analyze the relation between phenological metrics and aboveground carbon. RESULTS The gap filling approach enabled to accurately approximate the original Landsat ETM+ and OLI EVI values and the subsequent derivation of annual phenological metrics. Random Forest model performances varied between the three study areas with RMSE values of 1.64 t/ha (mean relative RMSE 30%), 2.35 t/ha (46%) and 2.18 t/ha (45%). Comparable relationships between remote sensing based land surface phenological metrics and aboveground carbon were observed in all study areas. Aboveground carbon distributions could be mapped and revealed comprehensible spatial patterns. CONCLUSION Phenological metrics were derived from 8-day Landsat time series with a spatial resolution that is sufficient to capture gradual changes in carbon stocks of heterogeneous Savanna ecosystems. These metrics revealed the relationship between aboveground carbon and the phenology of the observed vegetation. Our results suggest that metrics relating to the seasonal minimum and maximum values were the most influential variables and bear potential to improve spatially explicit mapping approaches in heterogeneous ecosystems, where both spatial and temporal resolutions are critical.
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Affiliation(s)
- M Schwieder
- Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099, Berlin, Germany.
| | - P J Leitão
- Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099, Berlin, Germany
- Department Landscape Ecology and Environmental System Analysis, Institute of Geoecology, Technische Universität Braunschweig, Langer Kamp 19c, 38106, Braunschweig, Germany
| | - J R R Pinto
- Departamento de Engenharia Florestal, Universidade de Brasília, Brasília, DF, 70919-970, Brazil
| | - A M C Teixeira
- Graduate Program in Botany, University of Brasília, Brasília, DF, 70919-970, Brazil
| | - F Pedroni
- Instituto de Ciências Biológicas e da Saúde, Universidade Federal de Mato Grosso, Pontal do Araguaia, MT, 78698-000, Brazil
| | - M Sanchez
- Instituto de Ciências Biológicas e da Saúde, Universidade Federal de Mato Grosso, Pontal do Araguaia, MT, 78698-000, Brazil
| | - M M Bustamante
- Departamento de Ecologia, Universidade de Brasília, Brasília, DF, 70919-970, Brazil
| | - P Hostert
- Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099, Berlin, Germany
- Integrative Research Institute on Transformations of Human-Environment Systems-IRI THESys, Humboldt-Universitätzu Berlin, Unter den Linden 6, 10099, Berlin, Germany
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