Data for: Between boreal Siberia and arid Central Asia - stable isotope hydrology and water budget of Burabay National Nature Park ecotone (Northern Kazakhstan)
Contributors: Vadim Yapiyev, Grzegorz Skrzypek, Zhanay Sagintayev, David Macdonald, Anne Verhoef
... The dataset (n=54) represents the results of analysis for hydrogen and oxygen isotope composition of water with calculated deuterium excess (d-excess: δ^2 H=8δ^18 O+10). The samples were collected during one hydrologic year from November 2015 to November 2016 at Burabay National Nature Park (BNNP), Kazakhstan. Lake water samples (n=30) were collected approximately each month during ice-free period, groundwater (n=13) and streamwater (n=6) samples quarterly. The lake water samples were collected by grab sampling at the shoreline usually at fixed locations (if the location for a given sample for a lake was different from the fixed point it was indicated in comment column and coordinates are provided). The lake water was sampled at approximately monthly intervals, from the start of the open water season (end of April) to the first days of November 2016 (about one week before permanent ice-cover; ice-on). Snow samples (n=2) collected near Lake Shortandy were melted in a sealed container at room temperature. Rainfall samples (n=3) were collected at Kazakh State Hydrometeorological Agency (Kazhydromet) weather station near Ulken Shabakty Lake. The rainfall samples were collected during abundant precipitation events using a large plastic container and immediately transferred into the vials and sealed. Groundwater samples were collected from boreholes (GrdW1-4) using a bailer. Groundwater was sampled during the open water season at approximately three-month intervals (end of April, mid-July, and end of October 2016). Stream samples were collected at approximately the same times as groundwater samples following the same sampling procedure used for lake water samples. The samples were analyzed at the Global Institute for Water Security, McDonnell Watershed Hydrology Laboratory (Saskatchewan, Canada) on a Liquid Water Isotope Analyzer (Los Gatos Research). The analyzer uses liquid water Off-Axis Integrated-Cavity Output Spectroscopy (Off-Axis ICOS) and has an uncertainty of ≤ ±1.0 for δ2H and ±0.2 for δ18O. The following reference materials were used to normalize obtained values to VSMOW international scale: ‘Saskatoon Snow Melt Water’ (SSMW): δ2H= -200.4 ‰, δ18O = -26.1 ‰; and ‘Enriched’: δ2H=3.2 ‰, δ18O=-0.3 ‰). All values are reported as parts per thousand (‰) according to the Vienna Standard Mean Ocean Water - Standard Light Antarctic Precipitation (VSMOW-SLAP) scales. See also the Materials and Methods sections (3.2 and 3.3) of the article. The sampling points and weather station location can also be found in Google Earth geospatial data format file (Burabay isotopes paper.kmz).
Contributors: Hichem Omrani, Bilel Omrani, Benoit Parmentier, Marco Helbich
... Monitoring of air pollution is an important task in public health. Availability of data is often hindered by the paucity of the ground monitoring station network. We present here a new spatio-temporal dataset collected and processed from the Sentinel-5P remote sensing platform aiming at the monitoring of air pollution for public institutions. As an example application, we applied the full workflow to process measurements of Nitrogen dioxide (NO2) collected over the territory of mainland France from May 2018 to June 2019. The data stack generated is daily measurements at a 4×7km spatial resolution. The supplementary code package used to collect and process the data is made publicly available to ease the access and processing for any location and product. The dataset provided in this article is of value for policy-makers and health assessment.
Contributors: Gulnara Svishcheva
... These data are a matrix of diploid genotypes of 14 microsatellite loci for 18 cattle breeds of European and Asian origin. For each locus and each individual, the genotype has 6-digit code (3 digits per allele). The first sheet includes the microsatellite data in the genind. Missing data indicated by 000000.
Contributors: Gaetan Montero, Cécile Tannier
... Contributors: Gaëtan Montero, Cécile Tannier, Isabelle Thomas Date:2019-16-10 Description: This data set can be used to reproduce the analyses made by the authors in their paper “Morphological delineation of cities based on scaling properties of urban patterns: a comparison of three methods”. It contains 12 shapefiles that represent theoretical urban patterns and 4 shapefiles that can be used to delineate the morphological agglomeration of Brussels (Belgium). It also contains a R script to calculate the carrying capacity of a logistic percolation function. Description of each file 2_Figure_1: theoretical street network for testing the Natural Cities method 3_Figure_2: theoretical street network for the comparison of two variants of the Natural Cities method 4_Figure_3: theoretical street network to evaluate the effects of the spatial extent of the study area on the delineation of Natural Cities 5_Figure_5a: theoretical pattern for testing MorphoLim (building footprints) – dense urban core 6_Figure_5b: theoretical pattern for testing MorphoLim (building footprints) – less dense urban core 7_Figure_6: theoretical pattern (building footprints) to evaluate the effects of the geographic extent of the study area on the delineation with MorphoLim 8_Percolation_C_Calculation: R code to calculate the carrying capacity of a logistic function (Hierarchical Percolation) 9_Figure_7: theoretical street network for testing Hierarchical Percolation 10_Figure_8: theoretical polycentric street network for testing Hierarchical Percolation 11_Figure_9ac: theoretical urban pattern crossed by a large non built area (road intersections) 12_Figure_9b: theoretical urban pattern crossed by a large non built area (building footprints) 13_Figure_10ac: theoretical pattern where a built ribbon links two urban centres (roads intersections ) 14_Figure_10b: theoretical pattern where a built ribbon links two urban centres (building footprints) 15_Belgium_buildings: cadastral data of buildings (2D) for Belgium (© 2009 Administration Générale de la Documentation Patrimoniale) 16_Brabant_buildings: cadastral data of buildings (2D) for the province of Brabant (© 2009 Administration Générale de la Documentation Patrimoniale) 17_Belgium_roads: road network data come from the platform Geofabrik of OpenStreetMap (http://download.geofabrik.de, accessed 08/21/2018) for Belgium 18_Brabant_roads: Road network data come from the platform Geofabrik of OpenStreetMap (http://download.geofabrik.de, accessed 08/21/2018) for the province of Brabant.
Contributors: Pranav Pandya, Kartikey Hadiya, Arnava Ghatak
... Resource Mapping data was collected from field survey and all points such as markets, atms, schools were located and appropriate tags were given. Data was uploaded on Google sheets and addons of Fusion Mas and point map were installed and addons were run to form virtual maps in their own particular webpages. Source link of those webpages are determined and were added in a iframe in src link. In web html design a table was made and all three iframe are added in table. The final html was added as html element in sites.google.com to create a custom website. The website link: www.sites.google.com/site/pranavrsmap Webpage and Sheets are the most important data here. Other data are optional and are uploaded for your Geospatial Location research
Contributors: Rick J. Hogeboom, Davey de Bruin, Joep Schyns, Maarten Krol, Arjen Hoekstra
... Excelfile containing several water footprint caps, runoff and environmental flow statistics for 11,000+ river basins worldwide. Shapefile containing geometries for these basins.
Contributors: Tetsuji Okada
... DSA files of human (N to Z, by gene name) : UniProt ID is used for a protein to which no gene name is assigned.
Contributors: Tetsuji Okada
... DSA files of human (A to M, by gene name) : UniProt ID is used for a protein to which no gene name is assigned.