My GeoServer WFSThis is a description of your Web Feature Server. The GeoServer is a full transactional Web Feature Server, you may wish to limit GeoServer to a Basic service level to prevent modificaiton of your geographic data.WFS, WMS, GEOSERVERhttp://geoserver.sourceforge.net/html/index.phpNONENONEgeonode:10minThis dataset contains 10 minutes walking distances from the planned Turku tramway stops. This dataset was created by calculating a 10-minute journey along the Digiroad network at a speed of 4 km/h. This dataset was produced to be used in web-map created for MAAN7771 geo-visualization challenge group work.features, 10minEPSG:3067geonode:services_onroadThis dataset includes after-school service points such as “Uimahallit” (swimming pools), “Uimapaikat” (swimming areas), “Jäähallit” (ice rinks), “Liikuntasalit ja palloiluhallit” (sports halls), “Kuntosalit” (gyms), “Urheilukentät” (sports fields), “Stadionit” (stadiums), “Nuorisotilat ja -keskukset” (youth facilities and centres), and “Kirjastot” (libraries). The service point data were downloaded from the Lounaistieto open data portal and clipped to the Turku metropolitan area, which includes the municipalities of Turku, Kaarina, Lieto, Naantali, Raisio, and Rusko. A 15-minute walking distance (1,250 m) buffer was calculated around each school, and the number of after-school services within these buffers is this dataset. This dataset represents the resulting spatial layer showing after-school services located within the 15-minute walking areas from schools, providing a basis for accessibility and service distribution analysis in the Turku region."Public services", "Walkability", "After-school services", features, "Turku metropolitan area", "opendata", services_onroad, "Accessibility", "Service points"EPSG:3067geonode:archipelago_development_preferences4006c3889fc7This dataset contains information about development preferences in the Archipelago Sea area. The data was collected during summer 2022 with Maptionnaire online platform. Development preferences were ready given options and respondents mapped as points places where they identify a specific development preference. Participants had the opportunity to locate as many points as they wanted. Document contains attribute metadata of respondents, development preferences and coordinates. The data was produced by the University of Turku, Department of Geography and Geology in collaboration with Metsähallitus and the Archipelago Sea Biosphere Reserve. This data covers geographically Archipelago Sea area and its municipalities.archipelago_development_preferences4006c3889fc7, participatory mapping, features, Development preference, Archipelago Sea National Park, Archipelago Sea, PPGISEPSG:4326geonode:archipelago_landscape_values_3b633c2a37562d2a1f4f986fe7241a4cThis dataset contains information about landscape values in the Archipelago Sea area. The data was collected during summer 2022 with Maptionnaire online platform. Values were ready given options and respondents mapped as points places where they identify a specific landscape value. Participants had the opportunity to locate as many points as they wanted. Document contains attribute metadata of respondents, values and coordinates. The data was produced by the University of Turku, Department of Geography and Geology in collaboration with Metsähallitus and the Archipelago Sea Biosphere Reserve. This data covers geographically Archipelago Sea area and its municipalities.PPGIS, Landscape values, Archipelago Sea, archipelago_landscape_values_3b633c2a37562d2a1f4f986fe7241a4c, participatory mapping, features, Archipelago Sea National ParkEPSG:4326geonode:bankfull_model_of_tana_catchment_river_networkThis dataset contains the simulated area that corresponds to bankfull stage in the main Tana River stem and principal tributaries. This area is obtained thanks to the FluvialCorridor toolbox for ArcGIS that can be found in the following link: https://github.com/EVS-GIS/Fluvial-Corridor-Toolbox-ArcGISTenojoki, bankfull, Tana River, features, bankfull_model_of_tana_catchment_river_networkEPSG:5048geonode:finnic_branch_9c4ec3f9281ac95263d4946c31b229ddThis file include the distribution of the Uralic languages grouped as Finnic branch. This dataset is produced by Timo Rantanen in the project BEDLAN (https://bedlan.net/) and published in the spatial data platform curated by URKO (https://sites.utu.fi/urko/).1900, traditional, finnic_branch_9c4ec3f9281ac95263d4946c31b229dd, features, uralic languages, Finnic branchEPSG:3857geonode:finnish_dialect_areasTraditional Finnish language area in the beginning of the 1900s. This dataset is produced by Timo Rantanen in the project BEDLAN (https://bedlan.net/) and published in the spatial data platform curated by URKO (https://sites.utu.fi/urko/).finnish language, features, 1900, traditional, dialects, finnish_dialect_areas, Finnic branchEPSG:3857geonode:hospitals_by_walking_fixedThe dataset contains hospital accessibility layer by walking in Southwest Finland. The layer represents travel time lengths from hospital service points within a one-hour distance, at five-minute intervals. The calculation of travel times utilized the road network provided by Digiroad, as well as the service point data from Lounaistieto.features, hospitals_by_walking_fixedEPSG:3067geonode:hospitals_by_car_fixedThe dataset contains hospital accessibility layer by car in Southwest Finland. The layer represents travel time lengths from hospital service points within a one-hour distance, at five-minute intervals. The calculation of travel times utilized the road and speed limit network provided by Digiroad, as well as the service point data from Lounaistieto.features, hospitals_by_car_fixedEPSG:3067geonode:hospital_points_fixedThe dataset contains service point information of hospitals in Southwest Finland. The data was modified from Lounaistieto service point dataset. The service points were reduced to include only those hospitals that are operational in 2025. The attribute table contains information about the locations, addresses, opening hours, and contact details of the service points.features, hospital_points_fixedEPSG:3067geonode:karelian_languageCurrent distribution of Karelian language. This dataset is produced by Timo Rantanen in the project BEDLAN (https://bedlan.net/) and published in the spatial data platform curated by URKO (https://sites.utu.fi/urko/).features, karelian_language, current, 2000, karelian language, Finnic branchEPSG:3857geonode:kigogo_climate_stressor_experiences_2023This vector layer represents local community members' climate stressor experiences in Kigogo, Dar es Salaam. Local communities in Tandale and Kigogo wards shared their local knowledge on where they have most often encountered floods, extreme heat and air pollution via participatory mapping campaign conducted in October 2023. Their experiences were mapped with Maptionnaire-tool by Resilience Academy alumni students from Ardhi University. features, participatory mapping, kigogo_climate_stressor_experiences_2023EPSG:4326geonode:lahti_temperature_differences_2014_2016ac5f07809c5eDataset includes temperature information measured from 8 locations during 1.6.2014-31.5.2016. Data includes temperature measurement for situations when the temperature difference between the measured points has been the largest. Dataset also includes the coordinates for each temperature logger in EPSG:3067. Some environmental details are also included regarding the loggers´ position. Environmental details are form SLICES2010 land usage dataset and 25m resolution DEM elevation model. Temperature measurements are done using Hobo U23-001 Pro V2 temperature and moisture loggers, measuring every 30mins, located 3m above ground level.Climate, features, Urban heat island, Temperature, lahti_temperature_differences_2014_2016ac5f07809c5eEPSG:5048geonode:landscape_service_and_lulc_grid_information_from_ie8368b27bc98The dataset consists of variables calculated in to 500 times 500 meters grid cells from landscape service point data and LULC polygon data. The data set covers approximately the same spatial extent as was used in the participatory mapping data collection campaign during February and March 2016. This data set was created for the purpose to study the spatial distribution and density of provisioning landscape services in the village landscape. For more information on the variables included and their calculation see the associated article: https://doi.org/10.1016/j.ecoser.2019.101056features, Tanzania, Landscape services, landscape_service_and_lulc_grid_information_from_ie8368b27bc98, participatory mapping, ecosystem services, SUSLANDEPSG:32736geonode:landscape_service_and_lulc_grid_information_from_l9d2e914448daThe dataset consists of variables calculated in to 500 times 500 meters grid cells from landscape service point data and LULC polygon data. The data set covers approximately the same spatial extent as was used in the participatory mapping data collection campaign during February and March 2016. This data set was created for the purpose to study the spatial distribution and density of provisioning landscape services in the village landscape. For more information on the variables included and their calculation see the associated article: https://doi.org/10.1016/j.ecoser.2019.101056SUSLAND, Landscape services, features, participatory mapping, landscape_service_and_lulc_grid_information_from_l9d2e914448da, Tanzania, Lulanzi_grid_SUSLAND, ecosystem servicesEPSG:32736geonode:landscape_service_and_lulc_grid_information_from_t4f2dfabeab62The dataset consists of variables calculated in to 500 times 500 meters grid cells from landscape service point data and LULC polygon data. The data set covers approximately the same spatial extent as was used in the participatory mapping data collection campaign during February and March 2016. This data set was created for the purpose to study the spatial distribution and density of provisioning landscape services in the village landscape. For more information on the variables included and their calculation see the associated article: https://doi.org/10.1016/j.ecoser.2019.101056Tanzania, participatory mapping, features, SUSLAND, landscape_service_and_lulc_grid_information_from_t4f2dfabeab62, ecosystem services, Landscape servicesEPSG:32736geonode:ludic_language_1900Distribution of Ludic language at the beginning of the 20th century. This dataset is produced by Timo Rantanen in the project BEDLAN (https://bedlan.net/) and published in the spatial data platform curated by URKO (https://sites.utu.fi/urko/).1900, traditional, features, ludic_language_1900, Finnic branch, ludic languageEPSG:3857geonode:lulanzi_servicepointsLandscape service (provisioning and cultural) point locations from Lulanzi village located at the Southern highlands of Tanzania. This data was produced in a participatory mapping campaign and it was organized in Tanzania from February to March 2016.participatory mapping, ecosystem services, features, Landscape services, Lulanzi_Servicepoints, Tanzania, SUSLAND, lulanzi_servicepointsEPSG:32736geonode:mansi_languageCurrent distribution of Mansi language. This dataset is produced by Timo Rantanen in the project BEDLAN (https://bedlan.net/) and published in the spatial data platform curated by URKO (https://sites.utu.fi/urko/).mansi branch, 2000, features, mansi_language, current, mansi languageEPSG:3857geonode:measurements_of_water_properties_with_ysi_multipar8bb181df8d5dThe data are based on the seasonal development of five surface-layer water variables (temperature, salinity, Secchi depth, chlorophyll and acidity) and the persistence of their geographical patterns at the Archipelago Seagradient, features, monitoring, measurements_of_water_properties_with_ysi_multipar8bb181df8d5d, persistence, water qualityEPSG:5048geonode:pemba_buildings_2004_cd759cbb7e13bf70fb93f41f65a3a8f0No abstract providedfeatures, pemba_buildings_2004_cd759cbb7e13bf70fb93f41f65a3a8f0EPSG:21037geonode:pemba_roads_2004No abstract providedfeatures, pemba_roads_2004EPSG:21037geonode:healthcare_service_points_ws_satakuntaThis dataset contains Information about public health service point locations in Southwest Finland and Satakunta. Each point contins information about the municipality, region, type, website link and the opening hours. The purpose of the dataset is to identify large gaps between care needs and the accessibility or availability of care services. The dataset was produced as a practical for the course Geospatial Data Management and Visualization in the University of Turku (2025) by the group Mapmaniacs. All public health care centres in the areas were mapped, that were active at the data collecting time.features, healthcare_service_points_ws_satakuntaEPSG:4326geonode:pulmanki_river_ecological_and_soil_survey_autumn_2016The data are based on a field survey of sub-arctic Pulmanki river valley vegetation and soil in September 2016, field measurements of topography, bathymetry and flow and water level during 2009-2016 and hydraulic modelling. The data are discussed in detail in Nylén et al. 2019. The owner of this dataset is Tua Nylén (tua.nylen@utu.fi) and Fluvial and Coastal Research Group, University of Turku.Lichen, Unit stream power, Species richness, Bryophyte, Sub-arctic, Species distribution, Disturbance, Riverine, features, Lapland, Elevation model, pulmanki_river_ecological_and_soil_survey_autumn_2016, Vascular plant, River valley, LitterEPSG:3067geonode:paavo_sw_f_2024This Dataset shows the current share (2024) of elderly people in each municipality of SW Finland. The distribution of the age groups that are 65 years old or even older are mapped in form of Polygones. The Polygones displays the percentage of the elderly people relative to the total elderly population across the study area. This dataset was produced under the visualization challange of the course MAAN 7771 Geospatial Data Management and Visualization at the University of Turku and aims to help urban planners to understand today’s spatial distribution of aging populations and existing health care access. Data derived from Statistics Finland datasets.features, paavo_sw_f_2024, 2024EPSG:3067geonode:medservice_exp3067This Dataset contains information about the location of health care services, divided into Hospitals, Private and Public Health Care Service Points. The point data aims to display the current distribution of health care service points in SW Finland for the year 2024. This dataset was produced under the visualization challange of the course "MAAN 7771 Geospatial Data Management and Visualization" at the University of Turku. Data derived from Lounaistieto service points.features, medservice_exp3067EPSG:3067geonode:paavo_sw_f_2045This Dataset contains information about the change of the elderly population in the future (2045) in each municipality of SW Finland. The projected increase or decrease in the elderly population is mapped in form of Polygones. The Polygones displays the percentage of increase or decrease of elderly residents. This dataset was produced under the visualization challange of the course "MAAN 7771 Geospatial Data Management and Visualization" at the University of Turku and aims to highlight future hotspots of demographic pressure and areas where demand for care services is expected to grow most. Data derived from Statistics Finland datasets.2045, features, paavo_sw_f_2045EPSG:3067geonode:saami_branchThe distribution of the Uralic languages grouped as Saami branch. This dataset is produced by Timo Rantanen in the project BEDLAN (https://bedlan.net/) and published in the spatial data platform curated by URKO(https://sites.utu.fi/urko/).1900, traditional, features, uralic languages, saami_branch, saami branchEPSG:3857geonode:saami_branch_allDistribution of Saami language branch at the beginning of the 20th century (updated). This dataset is produced by Timo Rantanen in the project BEDLAN (https://bedlan.net/) and published in the spatial data platform curated by URKO (https://sites.utu.fi/urko/).1900, saami_branch_all, traditional, features, uralic languages, saami branchEPSG:3857geonode:schools_total_serv_7f5e5b063ede73f97378c8471cdd03fcThis dataset contains basic education level school points within the Turku metropolitan area, including the municipalities of Turku, Kaarina, Lieto, Naantali, Raisio, and Rusko. The basic education school data were originally uploaded from the Lounaistieto open data portal and clipped using the Digiroad network for accessibility analyses and therefore the schoolpoints now lay on their closest road and not on the original places. features, schools_total_serv_7f5e5b063ede73f97378c8471cdd03fc, "Schools", After-school services, Accessibility, DigiroadEPSG:3067geonode:healthcare_service_areas_ws_satakuntaThis dataset contains the servce areas around public health care services offering primary and emergency care in the wellbeing services counties of Southwest Finland and Satakunta. The service areas have been calculated with four intervals (2 km, 5 km, 10 km, 20 km) with the distances being along roads. Service area polygons were each calculated around one health centre, and same distance polygons have then been merged. Polygons were clipped by healtcare region areas and islands without health care center and road connection to mainland were clipped out. The purpose of the dataset is to provide an overview of the availability of healthcare in the counties of southwest Finland. The dataset was produced as a practical for the course Geospatial Data Management and Visualization in the University of Turku (2025) by the group Mapmaniacs.features, healthcare_service_areas_ws_satakuntaEPSG:4326geonode:turclim_data__august_2006_and_2007The data are based on a temperature measuring points in the Turku region. In addition to points, data contains information about environmental variables. Environmental variables can be used to explain the average temperatures of temperature points. Data were collected in August 2006 and 2007 The owner of this dataset is Juuso Suomi (juusuo@utu.fi), University of Turku.Land use, features, TURCLIM, turclim_data__august_2006_and_2007, Mean temperature, Urban heat islandEPSG:3067geonode:tandale_climate_stressor_experiences_2023This vector layer represents local community members' climate stressor experiences in Tandale, Dar es Salaam. Local communities in Tandale and Kigogo wards shared their local knowledge on where they have most often encountered floods, extreme heat and air pollution via participatory mapping campaign conducted in October 2023. Their experiences were mapped with Maptionnaire-tool by Resilience Academy alumni students from Ardhi University. features, participatory mapping, tandale_climate_stressor_experiences_2023EPSG:4326geonode:testdatasetNo abstract providedtestdataset, featuresEPSG:4326geonode:testdataset_kmzkNo abstract providedfeatures, testdataset_kmzkEPSG:4326geonode:the_land_use__land_cover_data_from_iboya_tanzania_9c76f216c392The Land Use & Land Cover (LULC) data from the Iboya region of Tanzania. There are six LULC-categories in this data (Scrubland, arable land, wetland, homestead, forest and grassland). This data was produced in a participatory mapping campaign and it was organized in Tanzania from February to March 2016. The owner of this dataset is Joni Koskinen (jonkosk@utu.fi), University of Turku.Tanzania, landscape service, participatory mapping, landscape sustainability challenge, SUSLAND, the_land_use__land_cover_data_from_iboya_tanzania_9c76f216c392, features, LULCEPSG:32736geonode:the_land_use__land_cover_data_from_lulanzi_tanzanibd0d6a3b85ccThe Land Use & Land Cover (LULC) data from the Lulanzi region of Tanzania. There are six LULC-categories in this data (Scrubland, arable land, wetland, homestead, forest and grassland). This data was produced in a participatory mapping campaign and it was organized in Tanzania from February to March 2016. The owner of this dataset is Joni Koskinen (jonkosk@utu.fi), University of Turku.landscape sustainability challenge, participatory mapping, the_land_use__land_cover_data_from_lulanzi_tanzanibd0d6a3b85cc, features, landscape service, Tanzania, SUSLAND, LULCEPSG:32736geonode:the_land_use__land_cover_data_from_tungamalenga_taff6b71b1dd93The Land Use & Land Cover (LULC) data from the Tungamalenga region of Tanzania. There are six LULC-categories in this data (Scrubland, arable land, wetland, homestead, forest and grassland). This data was produced in a participatory mapping campaign and it was organized in Tanzania from February to March 2016. The owner of this dataset is Joni Koskinen (jonkosk@utu.fi), University of Turku.Tanzania, landscape service, participatory mapping, the_land_use__land_cover_data_from_tungamalenga_taff6b71b1dd93, SUSLAND, landscape sustainability challenge, features, LULCEPSG:32736geonode:the_distribution_of_glacial_meltwater_routes_and_ac8999af5199cThe dataset contains different types of subglacial meltwater routes and the related distribution of murtoos in the Finnish part of Fennoscandian Ice Sheet.features, subglacial hydrology, the_distribution_of_glacial_meltwater_routes_and_ac8999af5199c, subglacial meltwater routes, Fennoscandian ice sheet, LiDAR, Geomorphological mapping, murtoosEPSG:5048geonode:tungamalenga_servicepointsLandscape service (provisioning and cultural) point locations from Tungamalenga village located at the Southern highlands of Tanzania. This data was produced in a participatory mapping campaign and it was organized in Tanzania from February to March 2016.Tanzania, tungamalenga_servicepoints, Landscape services, Tungamalenga_Servicepoints, participatory mapping, SUSLAND, ecosystem services, 1000, featuresEPSG:32736geonode:raitiotielinjausThis dataset contains information about the planned Turku tramway. This dataset includes the planned tramline.features, raitiotielinjausEPSG:3877geonode:pysakitThis dataset contains information about the planned Turku tramway. This dataset includes the planned tramstops. This dataset was originally created by city of Turku and it is edited to be used in accessibility analysis relating to the planned tramway.features, pysakitEPSG:3857geonode:uralic_languages_branch_labelsBranch labels of the Uralic languages. This dataset is produced by Timo Rantanen in the project BEDLAN (https://bedlan.net/) and published in the spatial data platform curated by URKO (https://sites.utu.fi/urko/).features, 1900, traditional, uralic_languages_branch_labels, uralic languagesEPSG:3857geonode:uralic_branchesDistribution of Uralic branch at the beginning of the 20th century. The branches are visualised without overlapping extents. Map is based on the state-of-the-art distributions modified by the language experts. Branch labels of the Uralic languages. This dataset is produced by Timo Rantanen in the project BEDLAN (https://bedlan.net/) and published in the spatial data platform curated by URKO (https://sites.utu.fi/urko/).uralic_branches, features, 1900, traditional, uralic languagesEPSG:3857geonode:uralic_languagesDistribution of the Uralic languages at the beginning of the 20th century. This dataset is produced by Timo Rantanen in the project BEDLAN (https://bedlan.net/) and published in the spatial data platform curated by URKO (https://sites.utu.fi/urko/).uralic_languages, 1900, traditional, uralic languages, featuresEPSG:3857geonode:uralic_languages_labelsLabels for the Uralic languages. This dataset is produced by Timo Rantanen in the project BEDLAN (https://bedlan.net/) and published in the spatial data platform curated by URKO (https://sites.utu.fi/urko/).uralic_languages_labels, features, uralic languages, labelsEPSG:3857geonode:veps_language_1900Distribution of Veps language at the beginning of the 20th century. This dataset is produced by Timo Rantanen in the project BEDLAN (https://bedlan.net/) and published in the spatial data platform curated by URKO (https://sites.utu.fi/urko/).veps_language_1900, 1900, traditional, features, veps language, Finnic branchEPSG:3857geonode:walking_path_slipping_risk_in_turku30462480cf82This dataset contains information about slipping risk of the walking pathways in Turku and Kaarina. It is based on dataset "Turun ja Kaarinan ylläpitämät katualueet" (Road areas in Turku and Kaarina) https://www.avoindata.fi/data/fi/dataset/turun-ja-kaarinan-yllapitamat-katualueet. The original dataset has been modified in two ways. Firstly by adding nine attributes that describe slipping risk for pedestrians. Secondly, only walking pathways in the original dataset are included. This dataset is heavily based on other datasets in "Slippery datasets " group and is also part of the Bachelor's thesis of Iiro Seppä.Human health and safety, Slipping, Elderly person, slipperiness, Population distribution — demography, walking_path_slipping_risk_in_turku30462480cf82, Transport networks, features, PedestriansEPSG:3067geonode:wintertime_sedimentation_in_the_coastal_area_of_the_northern_bData describe sediment accumulation rate, organic and minerogenic matter, carbon and nitrogen content and their ratio (C/N) and mean sediment particle size (D50). Data have been collected during two perpendicular winter seasons in the Halikonlahti Bay, coastal area of the Northern Baltic Sea in 2018 - 2020. Data are based on sediment trapping and discussed more detailed in Salmela et al. 2021. Data ownership belongs to Fluvial and Coastal Research Group (https://sites.utu.fi/fcrg), Department of Geography and Geology, University of Turku. For more detailed information, please contact Jouni Salmela (jouni.salmela@utu.fi).Sedimentation, Baltic Sea, wintertime_sedimentation_in_the_coastal_area_of_the_northern_b, featuresEPSG:5048geonode:adna_data_points_3ed3d738471797002beabe40f991c267Genetic data collection locations from Uralic and neighbouring areas. This dataset is compiled by Anne-Mai Ilumäe from several resources and published in the spatial data platform curated by URKO (https://sites.utu.fi/urko/). Additional references are found in the point information.adna_data_points_3ed3d738471797002beabe40f991c267, genetics, ancient DNA, featuresEPSG:4326geonode:aanaar_saami_language_1900features, aanaar_saami_language_1900EPSG:3857geonode:akkala_saami_language_1900features, akkala_saami_language_1900EPSG:3857geonode:birch_event_date_a9ccb31aae8023dc111b1c01bbba3b2efeatures, birch_event_date_a9ccb31aae8023dc111b1c01bbba3b2eEPSG:2393geonode:bronze_age_bone_artefacts_4f111719bfa01539b7fa6ce289d1e96afeatures, bronze_age_bone_artefacts_4f111719bfa01539b7fa6ce289d1e96aEPSG:2393geonode:bronze_age_bone_classified_e4c46b053358d6bda792170fe578ead3features, bronze_age_bone_classified_e4c46b053358d6bda792170fe578ead3EPSG:2393geonode:bronze_age_bronze_artefactsfeatures, bronze_age_bronze_artefactsEPSG:2393geonode:bronze_age_clay_artefacts_ca91bd4c705a028b8a9e03086a39aa27features, bronze_age_clay_artefacts_ca91bd4c705a028b8a9e03086a39aa27EPSG:2393geonode:bronze_age_pottery_artefacts_0dcd2d0aa5f9d08a7642a3a4cb04b9aefeatures, bronze_age_pottery_artefacts_0dcd2d0aa5f9d08a7642a3a4cb04b9aeEPSG:2393geonode:bronze_age_pottery_artefacts_e07aef1f3649c003646dd062b197c225features, bronze_age_pottery_artefacts_e07aef1f3649c003646dd062b197c225EPSG:2393geonode:bronze_age_pottery_classified_dce188b31ffd43b5059b58875b9b23dffeatures, bronze_age_pottery_classified_dce188b31ffd43b5059b58875b9b23dfEPSG:2393geonode:bronze_age_pottery_main_f61b37fb934b4de897042aad434b8086features, bronze_age_pottery_main_f61b37fb934b4de897042aad434b8086EPSG:3857geonode:bronze_age_stone_tools_artefactsc6b9730e7e4efeatures, bronze_age_stone_tools_artefactsc6b9730e7e4eEPSG:2393geonode:bronze_age_stone_tools_classified41c0fc32c406features, bronze_age_stone_tools_classified41c0fc32c406EPSG:2393geonode:buildingsaoifeatures, buildingsaoiEPSG:32737geonode:courland_livonian_villages_4f781e558aa57ec4a8df34cfa0e307b9features, courland_livonian_villages_4f781e558aa57ec4a8df34cfa0e307b9EPSG:3857geonode:cumulative_yearly_hdd_and_cdd_in_iran_over_a_time__period_fromfeatures, cumulative_yearly_hdd_and_cdd_in_iran_over_a_time__period_fromEPSG:4326geonode:east_khanty_languagefeatures, east_khanty_languageEPSG:3857geonode:east_khanty_language_1900features, east_khanty_language_1900EPSG:3857geonode:east_mansi_language_1900features, east_mansi_language_1900EPSG:3857geonode:eastern_arc_forests_modelfeatures, eastern_arc_forests_modelEPSG:32737geonode:eastern_mari_language_1900features, eastern_mari_language_1900EPSG:3857geonode:erzya_and_moksha_language_1900features, erzya_and_moksha_language_1900EPSG:3857geonode:erzya_language_1900features, erzya_language_1900EPSG:3857geonode:finnic_dialect_labels_0ccc8314235f83d7747145a847622e22features, 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