Fragilariopsis kerguelensis images from sediment core PS1768-8

Background: Light microscopic analysis of diatom frustules is widely used both in basic and applied research, notably taxonomy, morphometrics, water quality monitoring and paleo-environmental studies. In these applications, usually large numbers of frustules need to be identified and / or measured. Although there is a need for automation in these applications, and image processing and analysis methods supporting these tasks have previously been developed, they did not become widespread in diatom analysis. While methodological reports for a wide variety of methods for image segmentation, diatom identification and feature extraction are available, no single implementation combining a subset of these into a readily applicable workflow accessible to diatomists exists. Results: The newly developed tool SHERPA offers a versatile image processing workflow focused on the identification and measurement of object outlines, handling all steps from image segmentation over object identification to feature extraction, and providing interactive functions for reviewing and revising results. Special attention was given to ease of use, applicability to a broad range of data and problems, and supporting high throughput analyses with minimal manual intervention. Conclusions: Tested with several diatom datasets from different sources and of various compositions, SHERPA proved its ability to successfully analyze large amounts of diatom micrographs depicting a broad range of species. SHERPA is unique in combining the following features: application of multiple segmentation methods and selection of the one giving the best result for each individual object; identification of shapes of interest based on outline matching against a template library; quality scoring and ranking of resulting outlines supporting quick quality checking; extraction of a wide range of outline shape descriptors widely used in diatom studies and elsewhere; minimizing the need for, but enabling manual quality control and corrections. Although primarily developed for analyzing images of diatom valves originating from automated microscopy, SHERPA can also be useful for other object detection, segmentation and outline-based identification problems.

ROCADA: Romanian daily gridded climatic dataset (1961-2013) V1.0

Daily records of nine meteorological variables covering the interval 1961-2013 were used in order to create a state-of-the-art homogenized climatic dataset over Romania at a spatial resolution of 0.1°. All meteorological stations with full data records, as well as stations with up to 30 % missing data, were used for the following variables: air pressure (150 stations); minimum, maximum, and average air temperature (150 stations); soil temperature (127 stations); precipitation (188 stations); sunshine hours (135 stations); cloud cover (104 stations); relative humidity (150 stations). For each parameter, the data series were first homogenized with the software MASH (Multiple Analysis of Series for Homogenization); then, the data series were gridded by means of the software MISH (Meteorological Interpolation based on Surface Homogenized Data).