Mapping soil organic carbon in Tuscany through the statistical combination of ground observations with ancillary and remote sensing data
Geoderma, ISSN: 0016-7061, Vol: 404, Page: 115386
2021
- 23Citations
- 40Captures
Metric Options: Counts1 Year3 YearSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
The organic carbon stored in the topsoil is an essential component of the global carbon cycle which should be quantified for a variety of purposes. The current paper proposes a new approach to map the amount of organic carbon stored in the 0.3 m topsoil (SOC), based on the statistical combination of a large number of ground observations with ancillary and remote sensing data. This approach is applied and tested in Tuscany, a region of Central Italy that is characterised by extremely diversified and heterogeneous environmental features. More than 3500 soil samples were collected and made available for the purpose, together with a soil map, meteorological data, a land use map and MODIS Normalised Difference Vegetation Index (NDVI) imagery. This information was processed by advanced statistical methods to yield a final map which describes the SOC spatial distribution in the region with a spatial resolution of 250 m. The map well reproduces the SOC variability in the region, showing higher SOC values for forests with respect to grasslands and croplands and SOC peaks related to peats and acidic soils. The accuracy assessment, carried out both versus all ground observations and by a leave-one-out cross validation strategy, testifies to the high quality of the SOC map, which has a global RMSE comprised between 17.5 and 32.3 t ha −1. The map is also accompanied by per-pixel estimates of error variance which are informative on the uncertainty of SOC prediction.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S0016706121004663; http://dx.doi.org/10.1016/j.geoderma.2021.115386; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85114125900&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S0016706121004663; https://dx.doi.org/10.1016/j.geoderma.2021.115386
Elsevier BV
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know