Template scripts on Google Earth Engine to detect green tides on the foreshores of beaches using Landsat archive

This github data repository gives access to template scripts to detect and monitor green tides on the foreshores of beaches using Landsat archive. The template provide examples for beaches in Northern Brittany, France. Two templates show how to estimate the green tide surfaces using Google Earth Engine Javascript. One template focuses on retrieving spectral signatures for certain point of interest on one image and export them in a chart. <br

Template scripts on Google Earth Engine to detect green tides on the foreshores of beaches using Landsat archive

This github data repository gives access to template scripts to detect and monitor green tides on the foreshores of beaches using Landsat archive. The template provide examples for beaches in Northern Brittany, France. Two templates show how to estimate the green tide surfaces using Google Earth Engine Javascript. One template focuses on retrieving spectral signatures for certain point of interest on one image and export them in a chart. <br

Hyperspectral plastics dataset supplementary to the paper ‘Advancing floating plastic detection from space using hyperspectral imagery’

This database is the supplementary material of Tasseron et al., (2021): Advancing floating plastic detection from space using hyperspectral imagery.More information about the contents of this dataset can be found in the enclosed readme - userguide file. </div

Dataset on green tide surfaces over Brittany using Landsat imagery for 35 years of monitoring

This dataset details all data used for a manuscript submission entitled "Spotting green tides over Brittany from space: three decades of monitoring with Landsat imagery". It presents data derived from Earth observation detection on the macroalgae surface on four studied sites in Brittany, France. These estimates were made using Landsat 5 and 8 satellite imagery, using the Google Earth Engine environment. Spectral signatures of natural features found on the study sites (sand, water and algae) are also presented. Additional datasets include 1) green macroalgae surface estimates made by an external source, CEVA (French Algae Technology and Innovation Center) and derived from aerial photography. This data was used for comparison with our results 2) nitrogen concentrations for four water stations close to the study sites. Nitrogen is considered the main physico-chemical factor controlling algae growth

Climatology-based Adjustments for Radar Rainfall in an OperaTional Setting: Adjustment factors for the Netherlands

This dataset contains gridded adjustment factors for correction of the Quantitative Precipitation Estimations (QPE) of the two operational C-band weather radars operated by the Royal Netherlands Meteorological Institute (KNMI). The factors are based on the CARROTS (Climatology-based Adjustments for Radar Rainfall in an OperaTional Setting) method, described in Imhoff et al. (2021). The factors are available for every yearday (temporal resolution of one day) and are based on ten years (2009 - 2018) of radar and reference rainfall data, as distributed by KNMI. For the derivation of the factors, both the operational radar QPE (https://doi.org/10.4121/uuid:05a7abc4-8f74-43f4-b8b1-7ed7f5629a01) and a reference rainfall dataset of KNMI (https://dataplatform.knmi.nl/catalog/datasets/index.html?x-dataset=rad_nl25_rac_mfbs_em_5min&&x-dataset-version=2.0) are used. The reference is not available in real time, but becomes available with a one to two month delay and was therefore available for this climatological factor derivation.The derivation method was as follows per grid cell in the radar domain (Imhoff et al., 2021):1. For every day in the period 2009--2018, an accumulation took place of all 5-min rainfall sums (of both the unadjusted radar QPE and the reference) within a moving window of 15 days prior to and 15 days after the day of interest. 2. For every yearday, the accumulations (per day) from the previous step were averaged over the ten years.3. Gridded climatological adjustment factors (Fclim) were calculated per yearday as: Fclim(i,j) = RA(i,j) / RU(i,j). In this equation, RA(i,j) is the reference rainfall sum for the ten years and RU(i,j) the operationally available unadjusted radar QPE sum, based on the previous two steps, at grid cell (i, j).For more details about the method, see Imhoff et al. (2021). For more information about the reference dataset, which consists of the radar QPE spatially adjusted with observations from 31 automatic and 325 manual rain gauges, see Overeem et al. (2009a,b). <br

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ABSTRACT. Two new 14C reference materials have been developed for international use, filling a gap in the present C1-C6 series available from the IAEA. By mixing a modern and a synthetic substance, 150 kg of C7 (ca. 50 pMC activity) and C8 (ca. 15 pMC activity), respectively, were obtained