SCIDB BASED FRAMEWORK FOR STORAGE AND ANALYSIS OF REMOTE SENSING BIG DATA

Decomposition rates for Sphagnum mosses, the main peat-forming plants in northern peatlands, are often derived from litterbag experiments. Here, we estimate initial leaching losses from available Sphagnum litterbag experiments and analyze how decomposition rates are biased when initial leaching losses are ignored. Our analyses indicate that initial leaching losses range between 3 to 18 mass-% and that this may result in overestimated mass losses when extrapolated to several decades.

Spatial proxies, such as coordinates and distances, are often used as predictors in random forest models for predictive mapping. In a simulation and two case studies, we investigated the conditions under which their use is appropriate. We found that spatial proxies are not always beneficial and should not be used as a default approach without careful consideration. We also provide insights into the reasons behind their suitability, how to detect them, and potential alternatives.

The Holocene Peatland Model (HPM) is a widely used peatland model to understand and predict long-term peatland dynamics. Here, we test whether the HPM can predict Sphagnum litterbag decomposition rates from oxic to anoxic conditions. Our results indicate that decomposition rates change more gradually from oxic to anoxic conditions and may be underestimated under anoxic conditions, possibly because the effect of water table fluctuations on decomposition rates is not considered.

An emissions inventory is a compilation of the mass of pollutants released by different sources. The quantification of vehicular emissions is difficult because these sources are in movement across streets. Also, emissions processes are multiple and complex. In this paper, we present an open-source software for calculating spatial vehicular emissions, including exhaust, evaporation and wear, named VEIN. The software is an R package available at https://github.com/atmoschem/vein.