This dataset contains useful vector maps to work with with Goode's Homolosine projection. The list of files included are:

CounterDomain.geojson - a polygonal approximation of the Homolosine projection counter-domain. This can be used to fix vectors wrongly projected by programmes that consider the counter-domain to be infinite. It can also be used to represent the seas in global mapping.

ParallelsMeridians.geojson - a set of meridians and parallels to be used in the creation of global maps.

Homolosine.crs - the PROJ string defining the Homolosine projection (referenced by the GeoJSON slides)

LICENCE - full text of the licence (EUPL-1.2)

These datasets were generated with the open souce programme homolosine-vectors, available at: https://gitlab.com/ldesousa/homolosine-vectors

Projected changes in habitat suitability for 33 marine species on the Northeast US shelf. Changes in habitat suitability are calculated based on species distribution models fit to bottom trawl survey data from the NOAA Northeast Fisheries Science Center. Positive values indicate an increase in habitat suitability by 2040-2050 relative to historical (1963-2005). The spatial resolution of projections is 0.25 x 0.25 degrees. access_formats=.htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson acquisition_description=The following methods are excerpted from Rogers et al. (in press):
Bottom trawl data from the NOAA Northeast Fisheries Science Center (NEFSC) fall (1963-2014) surveys were used to characterize the realized thermal niches of species. At each survey station, fish of each species were counted and weighed, and surface and bottom temperature measurements were taken. Correction factors were applied to standardize catch rates for changes in vessel and gear type. A total of 33 species were selected based on their near continuous presence in the survey as well as relative importance to commercial fisheries. For 4 species, data from 1972 onwards were used because observations were irregular prior to that year.

Generalized Additive Models were used to estimate the realized thermal niches of species. We restricted k (number of knots) to 4 or 6 for each of our covariates to ensure biologically meaningful responses. Our response variable was probability of occurrence in a trawl haul, and we used a binomial response with logit transform:

p(occur\u1d67,\u2c7c) ~ logit-1 (s(ST\u1d67,\u2c7c)+s(BT\u1d67,\u2c7c)+s(meanbiomass\u1d67)+s(rugosity\u2c7c))

where ST\u1d67,\u2c7c and BT\u1d67,\u2c7c are sea surface temperature and bottom temperature measured at each haul location j in year y, and meanbiomass\u1d67 is the average annual catch across all hauls to account for interannual changes in abundance due to, e.g., fishing. Rugosity\u1d67 is a measure of benthic habitat roughness, measured as the Terrain Ruggedness Index, using the GEBCO 2014 30-arcsecond bathymetry data (downloaded 4 Feb 2015 from http://www.gebco.net/). The resulting estimated smooth functions describing the relationship between probability of occurrence and temperature can be interpreted as realized thermal niches.

For each species, the change in predicted probability of occurrence under future (2040-2050) projected climate conditions was compared to historical (1963-2005) conditions for each cell within a 0.25\u00b0x0.25\u00b0 spatial grid. Because the modeled probability of occurrence included a component of catchability, values for each species were scaled by dividing by the maximum observed or predicted probability of occurrence across the study area. Positive values for a grid square indicated a projected increase in probability of occurrence, whereas negative values indicated a projected decrease in probability of occurrence.

See related dataset for\u00a0NEFSC bottom trawl data:\u00a0"%5C%22https://www.bco-%0Admo.org/dataset/753142%5C%22">https://www.bco- dmo.org/dataset/753142\u00a0(doi:\u00a010.1575/1912/bco-dmo.753142.1) awards_0_award_nid=559955 awards_0_award_number=OCE-1426891 awards_0_data_url=http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1426891 awards_0_funder_name=NSF Division of Ocean Sciences awards_0_funding_acronym=NSF OCE awards_0_funding_source_nid=355 awards_0_program_manager=Michael E. Sieracki awards_0_program_manager_nid=50446 cdm_data_type=Other comment=Projected changes in habitat suitability PIs: Lauren Rogers & Malin Pinsky Version date: 22-April-2019 Conventions=COARDS, CF-1.6, ACDD-1.3 data_source=extract_data_as_tsv version 2.3 19 Dec 2019 defaultDataQuery=&time<now doi=10.1575/1912/bco-dmo.765386.1 Easternmost_Easting=-64.875 geospatial_lat_max=44.875 geospatial_lat_min=33.625 geospatial_lat_units=degrees_north geospatial_lon_max=-64.875 geospatial_lon_min=-76.875 geospatial_lon_units=degrees_east infoUrl=https://www.bco-dmo.org/dataset/765386 institution=BCO-DMO keywords_vocabulary=GCMD Science Keywords metadata_source=https://www.bco-dmo.org/api/dataset/765386 Northernmost_Northing=44.875 param_mapping={'765386': {'lat': 'master - latitude', 'lon': 'master - longitude'}} parameter_source=https://www.bco-dmo.org/mapserver/dataset/765386/parameters people_0_affiliation=Rutgers University people_0_person_name=Malin Pinsky people_0_person_nid=554708 people_0_role=Principal Investigator people_0_role_type=originator people_1_affiliation=Stanford University people_1_person_name=Lauren Rogers people_1_person_nid=765425 people_1_role=Principal Investigator people_1_role_type=originator people_2_affiliation=Stanford University people_2_person_name=Robert Griffin people_2_person_nid=768380 people_2_role=Co-Principal Investigator people_2_role_type=originator people_3_affiliation=Rutgers University people_3_person_name=Kevin St. Martin people_3_person_nid=559961 people_3_role=Co-Principal Investigator people_3_role_type=originator people_4_affiliation=Princeton University people_4_person_name=Emma Fuller people_4_person_nid=748888 people_4_role=Scientist people_4_role_type=originator people_5_affiliation=Rutgers University people_5_person_name=Talia Young people_5_person_nid=752628 people_5_role=Scientist people_5_role_type=originator people_6_affiliation=National Oceanic and Atmospheric Administration - Alaska Fisheries Science Center people_6_affiliation_acronym=NOAA-AFSC people_6_person_name=Lauren Rogers people_6_person_nid=765425 people_6_role=Contact people_6_role_type=related people_7_affiliation=Woods Hole Oceanographic Institution people_7_affiliation_acronym=WHOI BCO-DMO people_7_person_name=Shannon Rauch people_7_person_nid=51498 people_7_role=BCO-DMO Data Manager people_7_role_type=related project=CC Fishery Adaptations projects_0_acronym=CC Fishery Adaptations projects_0_description=Description from NSF award abstract: Climate change presents a profound challenge to the sustainability of coastal systems. Most research has overlooked the important coupling between human responses to climate effects and the cumulative impacts of these responses on ecosystems. Fisheries are a prime example of this feedback: climate changes cause shifts in species distributions and abundances, and fisheries adapt to these shifts. However, changes in the location and intensity of fishing also have major ecosystem impacts. This project's goal is to understand how climate and fishing interact to affect the long-term sustainability of marine populations and the ecosystem services they support. In addition, the project will explore how to design fisheries management and other institutions that are robust to climate-driven shifts in species distributions. The project focuses on fisheries for summer flounder and hake on the northeast U.S. continental shelf, which target some of the most rapidly shifting species in North America. By focusing on factors affecting the adaptation of fish, fisheries, fishing communities, and management institutions to the impacts of climate change, this project will have direct application to coastal sustainability. The project involves close collaboration with the National Oceanic and Atmospheric Administration, and researchers will conduct regular presentations for and maintain frequent dialogue with the Mid-Atlantic and New England Fisheries Management Councils in charge of the summer flounder and hake fisheries. To enhance undergraduate education, project participants will design a new online laboratory investigation to explore the impacts of climate change on fisheries, complete with visualization tools that allow students to explore inquiry-driven problems and that highlight the benefits of teaching with authentic data. This project is supported as part of the National Science Foundation's Coastal Science, Engineering, and Education for Sustainability program - Coastal SEES. The project will address three questions: 1) How do the interacting impacts of fishing and climate change affect the persistence, abundance, and distribution of marine fishes? 2) How do fishers and fishing communities adapt to species range shifts and related changes in abundance? and 3) Which institutions create incentives that sustain or maximize the value of natural capital and comprehensive social wealth in the face of rapid climate change? An interdisciplinary team of scientists will use dynamic range and statistical models with four decades of geo-referenced data on fisheries catch and fish biogeography to determine how fish populations are affected by the cumulative impacts of fishing, climate, and changing species interactions. The group will then use comprehensive information on changes in fisher behavior to understand how fishers respond to changes in species distribution and abundance. Interviews will explore the social, regulatory, and economic factors that shape these strategies. Finally, a bioeconomic model for summer flounder and hake fisheries will examine how spatial distribution of regulatory authority, social feedbacks within human communities, and uncertainty affect society's ability to maintain natural and social capital. projects_0_end_date=2018-08 projects_0_geolocation=Northeast US Continental Shelf Large Marine Ecosystem projects_0_name=Adaptations of fish and fishing communities to rapid climate change projects_0_project_nid=559948 projects_0_start_date=2014-09 sourceUrl=(local files) Southernmost_Northing=33.625 standard_name_vocabulary=CF Standard Name Table v55 version=1 Westernmost_Easting=-76.875 xml_source=osprey2erddap.update_xml() v1.3

The UNI-CEN Digital Boundary File Series facilitates the mapping of UNI-CEN census data tables. Boundaries are provided in multiple formats for different use cases: Esri Shapefile (SHP), geoJson, and File Geodatabase (FGDB). SHP and FGDB files are provided in two projections: NAD83 CSRS for print cartography and WGS84 for web applications. The geoJson version is provided in WGS84 only. The UNI-CEN Standardized Census Data Tables are readily merged to these boundary files. For more information about file sources, the methods used to create them, and how to use them, consult the documentation at https://borealisdata.ca/dataverse/unicen_docs. For more information about the project, visit https://observatory.uwo.ca/unicen.

#Données of the 2022 Hydroclimatic Atlas ## #Description The Hydroclimatic Atlas describes the current and future water regime of southern Quebec in order to support the implementation of water management practices that are resilient to climate change. These data are from the most recent version of the Hydroclimatic Atlas. ## #Nouveautés * Improvement of the spatial resolution of the hydrographic network; * Greater spatial coverage; * Addition of the CliMEX and CORDEX-NA sets, in addition to the scenarios in the CMIP5 set; * Use of six hydrological platforms; * * Addition of indicators, especially annual ones. * Etc. ## #Liste data available * Link to the new Hydroclimatic Atlas website. * Map of the 24,604 river sections of the Hydroclimatic Atlas with their attributes, available in GeoJSON and shapefile format. To facilitate download and display, the map is divided into 11 GeoJSON files: ABIT (Abitibi and Lac Abitibi region), CND west (North Shore A and B regions), CND east (North Shore regions C, D and E), GASP (North Shore regions C, D and E), GASP (Gaspésie), MONT (Gaspesie), MONT (Montégérie), OUTM (Outaouais Upstream), OUTV (Outaouais Downstream), OUTV (Outaouais Downstream), SAGU (Saguenay), SLNO (St-Laurent Nord-Ouest), SLSO (St-Laurent Sud-Ouest), and VAUD (Vaudreuil). * The CSV tables (“Magnitude...”) for each of the 76 hydrological indicators describing the amplement, the direction and the dispersion for RCP 4.5 and RCP8.5, for the three future horizons (see the documentation for details). * The CSV tables (“Projected indicator...”) for each of the 76 hydrological indicators detailing the flow values with their uncertainty for the historical period and the three future horizons (RCP4.5 and 8.5). See the documentation for more details. * A PDF with the metadata and a more detailed description of the data. ## #Note The 2018 version data is archived on Data Quebec for reference, for example for old reports or analyses referring to this version of the data. Any new study or analysis should use the most recent data available below or on the Atlas website.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

The UNI-CEN Digital Boundary File Series facilitates the mapping of UNI-CEN census data tables. Boundaries are provided in multiple formats for different use cases: Esri Shapefile (SHP), geoJson, and File Geodatabase (FGDB). SHP and FGDB files are provided in two projections: NAD83 CSRS for print cartography and WGS84 for web applications. The geoJson version is provided in WGS84 only. The UNI-CEN Standardized Census Data Tables are readily merged to these boundary files. For more information about file sources, the methods used to create them, and how to use them, consult the documentation at https://borealisdata.ca/dataverse/unicen_docs. For more information about the project, visit https://observatory.uwo.ca/unicen.

This layer presents the Universal Transverse Mercator (UTM) zones of the world. The layer symbolizes the 6-degree wide zones employed for UTM projection.To download the data for this layer as a layer package for use in ArcGIS desktop applications, refer to World UTM Zones Grid.

The UNI-CEN Digital Boundary File Series facilitates the mapping of UNI-CEN census data tables. Boundaries are provided in multiple formats for different use cases: Esri Shapefile (SHP), geoJson, and File Geodatabase (FGDB). SHP and FGDB files are provided in two projections: NAD83 CSRS for print cartography and WGS84 for web applications. The geoJson version is provided in WGS84 only. The UNI-CEN Standardized Census Data Tables are readily merged to these boundary files. For more information about file sources, the methods used to create them, and how to use them, consult the documentation at https://borealisdata.ca/dataverse/unicen_docs. For more information about the project, visit https://observatory.uwo.ca/unicen.

MetNotes are a geo- and time-referenced, free form polygon product issued by MSC that complement today's location-based dissemination systems. The concise text of a MetNote (similar to a Tweet) is consistent with communication today where people are seeking information at a glance. Meteorologists will issue a MetNote to add contextual and/or impact information to complement the public forecast that is valid over a specific area, for a specific time range.

Transport and Infrasutcture Parking meters for Dublin City. Includes location, code, No of spaces per street (PD-Pay and Display D Disc Parking), exact location, data install, tariff (cost per hour), nearest location of pay and display, clearway, if clearway conditions in operation (No parking or stopping during the hours indicated on the street sign), further information, finished, x coordinate, y coordinate, tariff zone (see map) and Parking Voucher outlets and locations Spatial projection: IG

The Public Standard Forecast Zones layer is a collection of public program forecast location zone polygons that represents bounded measurable locations at the Public program Standard level. The public program standard level is used in most forecasts, warnings, watches, advisories and special weather statement. With the exception of the Manitoba Lakes, the layer is made up of mostly the land kind of polygons. The layer is made up of four depictions, cartographic detailed (with proper shorelines and high resolution polygons), cartographic coarse (with generalized shorelines and low resolution polygons), digital exaggerated (with exaggerated shorelines and low resolution polygons) and the hybrid (mix of cartographic detail and exaggerated). The digital layer (exaggerated) is a collection of polygons where shoreline boundaries are stretched offshore for the land polygons and inland for the water polygons. In this "Exaggerated" layer, the boundaries are made smooth to reduce the number of polygon vertices. Boundaries of the forecast regions of this hybrid set are derived from the polygon boundaries of both the exaggerated digital, and the cartographic detailed set. Polygon boundaries along the shoreline of this set follow the exaggerated boundaries while the inland boundaries follow the detailed lines. The Public Standard Forecast Zones layer is presented in the polygon package in two coordinate systems, "Projected" (Lambert Conformal Conic) and "Unprojected" (Geographical Coordinated System).

#Archive data from the 2018 Hydroclimatic Atlas ## #Description The Hydroclimatic Atlas describes the current and future water regime in southern Quebec in order to support the implementation of water management practices that are resilient to climate change. ## #Avertissement The 2018 version of the Atlas is now replaced by a more recent version on the website. Data from the 2018 version is archived on Data Québec for reference, for example for old reports or analyses referring to this version of the data. Any new study or analysis should use the most recent data available on Data Quebec (Hydroclimatic Atlas 2022) or on the Atlas website (www.cehq.gouv.qc.ca/atlas-hydroclimate-). ## #Liste of available data * Map of river sections from the Hydroclimatic Atlas with their attributes (available in GeoJSON and shapefile format). * CSV tables (“Magnitude...”) for each of the 28 hydrological indicators describing the amplem and direction for RCP4.5 and RCP8.5, for the three future horizons (see documentation for details). * CSV tables (“Projected indicator”). * CSV tables (“Projected indicator”)...”) for each of the 28 hydrological indicators detailing the flow values with their uncertainty for the historical period and the three future horizons (RCP4.5 and 8.5). See documentation for more details. * A more detailed PDF with metadata and description of the data.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

GeoJSON: Uganda Electricity Distribution Lines, 2018 (UMEME & REA) Source: Energy GIS Working Group (energy-gis.ug) for the NEW file (link below): Projection: EPSG 4326 (unprojected)GeoJSON Uganda MEME (UMEME) Rural Electrification Agency National Power Distribution Lines 2018