Over het archief
Het OWA, het open archief van het Waterbouwkundig Laboratorium heeft tot doel alle vrij toegankelijke onderzoeksresultaten van dit instituut in digitale vorm aan te bieden. Op die manier wil het de zichtbaarheid, verspreiding en gebruik van deze onderzoeksresultaten, alsook de wetenschappelijke communicatie maximaal bevorderen.
Dit archief wordt uitgebouwd en beheerd volgens de principes van de Open Access Movement, en het daaruit ontstane Open Archives Initiative.
Basisinformatie over ‘Open Access to scholarly information'.
A machine learning (kNN) approach to predicting global seafloor total organic carbon
Lee, T.R.; Wood, W. T.; Phrampus, B.J. (2019). A machine learning (kNN) approach to predicting global seafloor total organic carbon. Global Biogeochem. Cycles 33(1): 37-46. https://dx.doi.org/10.1029/2018gb005992
In: Global Biogeochemical Cycles. American Geophysical Union: Washington, DC. ISSN 0886-6236; e-ISSN 1944-9224, meer
|   |
| Auteurs | | Top |
- Lee, T.R.
- Wood, W. T.
- Phrampus, B.J.
|
|
|
| Abstract |
Seafloor properties, including total organic carbon (TOC), are sparsely measured on a global scale, and interpolation (prediction) techniques are often used as a proxy for observation. Previous geospatial interpolations of seafloor TOC exhibit gaps where little to no observed data exists. In contrast, recent machine learning techniques, relying on geophysical and geochemical properties (e.g., seafloor biomass, porosity, and distance from coast), show promise in making comprehensive, statistically optimal predictions. Here we apply a nonparametric (i.e., data-driven) machine learning algorithm, specifically k-nearest neighbors (kNN), to estimate the global distribution of seafloor TOC. Our results include predictor (feature) selection specifically designed to mitigate bias and produce a statistically optimal estimation of seafloor TOC, with uncertainty, at 5 × 5-arc minute resolution. Analysis of parameter space sample density provides a guide for future sampling. One use for this prediction is to constrain a global inventory, indicating that just the upper 5 cm of the seafloor contains about 87 ± 43 gigatons of carbon (Gt C) in organic form. |
IMIS is ontwikkeld en wordt gehost door het VLIZ.
