In order to use the standard color legend for Romanian soil type maps in the ESRI ArcMap-10 electronic format, a dataset consisting a shapefile set (.dbf, .shp, .shx, .sbn, and .sbx files), four different .lyr files, and three different .style files have been prepared (ESRI, 2016). The shapefile set is not a “real” georeferenced layer/coverage; it is designed only to handle all the instants of soil types from the standard legend. This legend contains 67 standard items: 63 proper colors (different color hues, each of them having, generally, 2 - 4 degrees of lightness and/or chroma, four shades of grey, and white color), and four hatching patterns on white background (ESRI, 2016). The “color difference DE*ab” between any two legend colors, calculated with the color perceptually-uniform model CIELAB , is greater than 10 units, thus ensuring acceptably-distinguishable colors in the legend. The 67 standard items are assigned to 60 main soils existing in Romania, four main nonsoils, and three special cases of unsurveyed land. The soils are specified in terms of the current Romanian system of soil taxonomy, SRTS-2012+, and of the international soil classification system WRB-2014. The four different .lyr files presented here are: legend_soilcode_srts_wrb.lyr, legend_soilcode_wrb.lyr, legend_colourcode_srts_wrb.lyr, and legend_colourcode_wrb.lyr. The first two of them are built using as value field the ‘Soil_codes’ field, and as labels (explanation texts) the ‘Soil_name’ field (storing the soil types according to SRTS/WRB classification), respectively, the ‘WRB’ field (the soil type according to WRB classification), while the last two .lyr files are built using as value field the ‘colour_code’ field (storing the color codes) and as labels the soil name in SRTS and WRB, respectively, in WRB classification. In order to exemplify how the legend is displayed, two .jpg files are also presented: legend_soil_srts_wrb.jpg and legend_colour_wrb.jpg. The first displays the legend (symbols and labels) according to the SRTS classification order, the second according to the WRB classification. The three different .style files presented here are: soil_symbols.style, wrb_codes.style, and colour_codes.style. They use as name the soil acronym in SRTS classification, soil acronym in WRB classification, and, respectively, the color code.

Download high-quality, up-to-date Romania shapefile boundaries (SHP, projection system SRID 4326). Our Romania Shapefile Database offers comprehensive boundary data for spatial analysis, including administrative areas and geographic boundaries. This dataset contains accurate and up-to-date information on all administrative divisions, zip codes, cities, and geographic boundaries, making it an invaluable resource for various applications such as geographic analysis, map and visualization, reporting and business intelligence (BI), master data management, logistics and supply chain management, and sales and marketing. Our location data packages are available in various formats, including Shapefile, GeoJSON, KML, ASC, DAT, CSV, and GML, optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Companies choose our location databases for their enterprise-grade service, reduction in integration time and cost by 30%, and weekly updates to ensure the highest quality.

Baza de date Romania 1:1000 000, realizata de Esri Romania si oferita gratuit spre a fi utilizata in scop educational.

In order to use the Romanian color standard for soil type map legends, a dataset of ESRI ArcMap-10 files, consisting of a shapefile set (.dbf, .shp, .shx, .sbn, and .sbx files), four different .lyr files, and three different .style files (https://desktop.arcgis.com/en/arcmap/10.3/map/ : saving-layers-and-layer-packages, about-creating-new-symbols, what-are-symbols-and-styles-), have been prepared. The shapefile set is not a “real” georeferenced layer/coverage; it is designed only to handle all the instants of soil types from the standard legend.

This legend contains 67 standard items: 63 proper colors (different color hues, each of them having, generally, 2 - 4 degrees of lightness and/or chroma, four shades of grey, and white color), and four hatching patterns on white background. The “color difference DE*ab” between any two legend colors, calculated with the color perceptually-uniform model CIELAB, is greater than 10 units, thus ensuring acceptably-distinguishable colors in the legend. The 67 standard items are assigned to 60 main soils existing in Romania, four main nonsoils, and three special cases of unsurveyed land. The soils are specified in terms of the current Romanian system of soil taxonomy, SRTS-2012+, and of the international system WRB-2014.

The four different .lyr files presented here are: legend_soilcode_srts_wrb.lyr, legend_soilcode_wrb.lyr, legend_colorcode_srts_wrb.lyr, and legend_colorcode_wrb.lyr. The first two of them are built using as value field the “Soil_codes” field, and as labels (explanation texts) the “Soil_name” field (storing the soil types according to SRTS/WRB classification), respectively, the “WRB” field (the soil type according to WRB classification), while the last two .lyr files are built using as value field the “color_code” field (storing the color codes) and as labels the soil name in SRTS and WRB, respectively, in WRB classification.

In order to exemplify how the legend is displayed, two .jpg files are also presented: legend_soil_srts_wrb.jpg and legend_color_wrb.jpg. The first displays the legend (symbols and labels) according to the SRTS classification order, the second according to the WRB classification.

The three different .style files presented here are: soil_symbols.style, wrb_codes.style, and color_codes.style. They use as name the soil acronym in SRTS classification, soil acronym in WRB classification, and, respectively, the color code.

The presented file set may be used to directly implement the Romanian color standard in digital soil type map legends, or may be adjusted/modified to other specific requirements.

INFP, CRMD and UCL have developed a framework capable of analyzing the implications of natural hazards on transportation networks, also in a time-dependent manner. This is currently embedded into an ArcGIS toolbox entitled Network-risk, which has been successfully tested for Bucharest, contributing to an insightful evaluation of emergency intervention times for ambulances and firefighters, in the case of an earthquake. The files and the user manual allow a replication of our recent analysis in Toma-Danila et al. (2022) and a download of results (such as affected roads and unaccesible areas in Bucharest), in various formats. Some of the results are also presented in an ArcGIS Online app, called "Riscul seismic al Bucurestiului" (The seismic risk of Bucharest), available at https://tinyurl.com/yt32aeyx. In the files you can find: - the Bucharest road network used in the article; - facilities for Bucharest and Ilfov, such as hospitals, firestations, buildings with seismic risk or tramway lines accesible by emergency vehicles - results of the analysis: unaccesible roads and areas, service areas around facilities, closest facilities for representative points - Excel calculator for Z elevation from OpenStreetMap data - the user manual and a ArcGIS toolbox.

Main citation: - Toma-Danila D., Tiganescu A., D'Ayala D., Armas I., Sun L. (2022) Time-Dependent Framework for Analyzing Emergency Intervention Travel Times and Risk Implications due to Earthquakes. Bucharest Case Study. Frontiers in Earth Science, https://doi.org/10.3389/feart.2022.834052

Previous references: - Toma-Danila D., Armas I., Tiganescu A. (2020) Network-risk: an open GIS toolbox for estimating the implications of transportation network damage due to natural hazards, tested for Bucharest, Romania. Natural Hazards and Earth System Sciences, 20(5): 1421-1439, https://doi.org/10.5194/nhess-20-1421-2020 - Toma-Danila D. (2018) A GIS framework for evaluating the implications of urban road network failure due to earthquakes: Bucharest (Romania) case study. Natural Hazards, 93, 97-111, https://link.springer.com/article/10.1007/s11069-017-3069-y

Limitele ariilor protejate SPA din Romania, 2011-10-20.ESRI Romania

Our Romania zip code Database offers comprehensive postal code data for spatial analysis, including postal and administrative areas. This dataset contains accurate and up-to-date information on all administrative divisions, cities, and zip codes, making it an invaluable resource for various applications such as address capture and validation, map and visualization, reporting and business intelligence (BI), master data management, logistics and supply chain management, and sales and marketing. Our location data packages are available in various formats, including CSV, optimized for seamless integration with popular systems like Esri ArcGIS, Snowflake, QGIS, and more. Product features include fully and accurately geocoded data, multi-language support with address names in local and foreign languages, comprehensive city definitions, and the option to combine map data with UNLOCODE and IATA codes, time zones, and daylight saving times. Companies choose our location databases for their enterprise-grade service, reduction in integration time and cost by 30%, and weekly updates to ensure the highest quality.

Mineral resource occurrence data covering the world, most thoroughly within the U.S. This database contains the records previously provided in the Mineral Resource Data System (MRDS) of USGS and the Mineral Availability System/Mineral Industry Locator System (MAS/MILS) originated in the U.S. Bureau of Mines, which is now part of USGS. The MRDS is a large and complex relational database developed over several decades by hundreds of researchers and reporters. While database records describe mineral resources worldwide, the compilation of information was intended to cover the United States completely, and its coverage of resources in other countries is incomplete. The content of MRDS records was drawn from reports previously published or made available to USGS researchers. Some of those original source materials are no longer available. The information contained in MRDS was intended to reflect the reports used as sources and is current only as of the date of those source reports. Consequently MRDS does not reflect up-to-date changes to the operating status of mines, ownership, land status, production figures and estimates of reserves and resources, or the nature, size, and extent of workings. Information on the geological characteristics of the mineral resource are likely to remain correct, but aspects involving human activity are likely to be out of date.

Limitele parcurilor nationale din Romania - 2011-06-02

Harta a fost realizată în cadrul proiectului „Restaurarea zonelor umede și turbăriilor din Regiunea de Nord-Vest” (NWPEAT), derulat în intervalul 16 decembrie 2021 – 30 aprilie 2024. Promotor de proiect - Facultatea de Geografie din cadrul Universității Babeș-Bolyai; Partener 1 - Norwegian Institute for Nature Research.

Proiectul este finanțat printr-un grant acordat de Islanda, Liechtenstein și Norvegia, Programul RO-Mediu „Mediu, Adaptare la Schimbările Climatice și Ecosisteme”, Apelul de propuneri Restaurarea zonelor umede și turbăriilor, al cărui Operator de Program este Ministerul Mediului, Apelor și Pădurilor.

You can find here GIS and spreadsheet data of firestations in Bucharest city and Ilfov county (Romania), according to official sources, geocoded and manually verified. Although we tried to make it as precise as we can, we don't guarantee that all attributes are accurrate so we don't decline any responsability in using this dataset as an authoritive data source.

This dataset has been compiled and used in various studies: - Toma-Danila D., Tiganescu A., D’Ayala D., Armas I., Sun L. (2022) Time-Dependent Framework for Analyzing Emergency Intervention Travel Times and Risk Implications due to Earthquakes. Bucharest Case Study. Frontiers in Earth Science 10:834052, doi: 10.3389/feart.2022.834052 (please use this as main citation, given that is significantly different than previous versions) - Toma-Danila D., Armas I., Tiganescu A. (2020) Network-risk: an open GIS toolbox for estimating the implications of transportation network damage due to natural hazards, tested for Bucharest, Romania. Natural Hazards and Earth System Sciences, 20(5):1421-1439, doi: 10.5194/nhess-20-1421-2020 - Toma-Danila D. (2018) A GIS framework for evaluating the implications of urban road network failure due to earthquakes: Bucharest (Romania) case study. Natural Hazards, 93, 97-111

If you are also interested in using the dataset as a feature service, it's on ArcGIS online, at https://services8.arcgis.com/SXiEEy1skwB5SrYh/arcgis/rest/services/Bucharest_Ilfov_firestations/FeatureServer

You can find here a list of hospitals in Bucharest city and Ilfov county (Romania), according to free data, joined and post-processed. Although we tried to make it as precise as we can, given the limitations of public datasets we don't guarantee that all attributes are accurrate so we don't decline any responsability in using this dataset as an authoritive data source, especially since subjective classifications of importance or seismic vulnerability are included.

This dataset has been compiled and used in various studies: - Toma-Danila D., Tiganescu A., D’Ayala D., Armas I., Sun L. (2022) Time-Dependent Framework for Analyzing Emergency Intervention Travel Times and Risk Implications due to Earthquakes. Bucharest Case Study. Frontiers in Earth Science 10:834052, doi: 10.3389/feart.2022.834052 (please use this as main citation, given that is significantly different than previous versions) - Toma-Danila D., Armas I., Tiganescu A. (2020) Network-risk: an open GIS toolbox for estimating the implications of transportation network damage due to natural hazards, tested for Bucharest, Romania. Natural Hazards and Earth System Sciences, 20(5):1421-1439, doi: 10.5194/nhess-20-1421-2020 - Toma-Danila D. (2018) A GIS framework for evaluating the implications of urban road network failure due to earthquakes: Bucharest (Romania) case study. Natural Hazards, 93, 97-111

If you are also interested in using the dataset as a feature service, it's on ArcGIS online, at https://services8.arcgis.com/SXiEEy1skwB5SrYh/arcgis/rest/services/Bucharest_Ilfov_hospitals/FeatureServer

The map shows the twenty-sixth highest Ozone (O3) value in Europe based on daily max 8-hour averages with at least 75% of valid measurements, in µg/m3 (source: EEA, AirBase v.8 & AQ e-Reporting)Thresholds used in the map for the twenty-sixth highest 8-hour max and other annual values [µg/m3]:≤ 80> 80 ≤ 100: (100 µg/m3, limit value for 8 hour mean, as set out in the WHO air quality guideline for O3)> 100 ≤ 120: (120 µg/m3, limit value and long term objective for human health, as set out in the Air Quality Directive, 2008/50/EC)> 120 ≤ 140> 140Source: AirBase v.8 & AQ e-ReportingAirBase is the European air quality database maintained by the EEA through its European topic centre on Air pollution and Climate Change mitigation. It contains air quality monitoring data and information submitted by participating countries throughout Europe.The air quality database consists of a multi-annual time series of air quality measurement data and statistics for a number of air pollutants. It also contains meta-information on those monitoring networks involved, their stations and their measurements.The database covers geographically all EU Member States, the EEA member countries and some EEA collaborating countries. The EU Member States are bound under Decision 97/101/EC to engage in a reciprocal exchange of information (EoI) on ambient air quality. The EEA engages with its member and collaborating countries to collect the information foreseen by the EoI Decision because air pollution is a pan European issue and the EEA is the European body which produces assessments of air quality, covering the whole geographical area of Europe.

The map shows the annual mean concentrations of Sulphur Dioxide (SO2) in Europe based on daily averages with at least 75% of valid measurements, in µg/m3 (source: EEA, AirBase v.8 & AQ e-Reporting)Thresholds used in the map for annual values [µg/m3]:≤ 5> 5 ≤ 10> 10 ≤ 20: (20 μg/m3, limit value for protection of vegetation, as set out in the Air Quality Directive, 2008/50/EC)> 20 ≤ 25> 25Source: AirBase v.8 & AQ e-ReportingAirBase is the European air quality database maintained by the EEA through its European topic centre on Air pollution and Climate Change mitigation. It contains air quality monitoring data and information submitted by participating countries throughout Europe.The air quality database consists of a multi-annual time series of air quality measurement data and statistics for a number of air pollutants. It also contains meta-information on those monitoring networks involved, their stations and their measurements.The database covers geographically all EU Member States, the EEA member countries and some EEA candidate countries. The EU Member States are bound under Decision 97/101/EC to engage in a reciprocal exchange of information (EoI) on ambient air quality. The EEA engages with its member and collaborating countries to collect the information foreseen by the EoI Decision because air pollution is a pan European issue and the EEA is the European body which produces assessments of air quality, covering the whole geographical area of Europe.

The map shows annual mean concentrations of Particulate Matter (PM10) in Europe based on daily averages with at least 75% of valid measurements, in µg/m3 (source: EEA, AirBase v.8 & AQ e-Reporting) Thresholds used in the map for annual values [µg/m3]: ≤ 20: (20 μg/m3, as set out in the WHO air quality guideline for PM10)> 20 ≤ 31: (31 μg/m3, a statistically derived level corresponding to the 24‑hour limit value, as set out in the Air Quality Directive, 2008/50/EC)> 31 ≤ 40: (40 μg/m3, limit value as set out in the Air Quality Directive, 2008/50/EC)> 40 ≤ 50> 50Source: AirBase v.8 & AQ e-ReportingAirBase is the European air quality database maintained by the EEA through its European topic centre on Air pollution and Climate Change mitigation. It contains air quality monitoring data and information submitted by participating countries throughout Europe.The air quality database consists of a multi-annual time series of air quality measurement data and statistics for a number of air pollutants. It also contains meta-information on those monitoring networks involved, their stations and their measurements.The database covers geographically all EU Member States, the EEA member countries and some EEA collaborating countries. The EU Member States are bound under Decision 97/101/EC to engage in a reciprocal exchange of information (EoI) on ambient air quality. The EEA engages with its member and collaborating countries to collect the information foreseen by the EoI Decision because air pollution is a pan European issue and the EEA is the European body which produces assessments of air quality, covering the whole geographical area of Europe.

At present, NATO has 29 members. In 1949, there were 12 founding members of the Alliance: Belgium, Canada, Denmark, France, Iceland, Italy, Luxembourg, the Netherlands, Norway, Portugal, the United Kingdom and the United States. The other member countries are: Greece and Turkey (1952), Germany (1955), Spain (1982), the Czech Republic, Hungary and Poland (1999), Bulgaria, Estonia, Latvia, Lithuania, Romania, Slovakia and Slovenia (2004), Albania and Croatia (2009), and Montenegro (2017).

Archive with analysis results for a study "The Effects of Water on Fog Occurrence" in Romania. Archive contain following subdirectories:

01_GIS-rasters (input, temporary and output rasters in geotiff format)

02_GIS-vector (domain and administrative borders in ESRI Shapefile format)

03_tables (results of the processed analysis)

EPSG:32635 (WGS 84 / UTM zone 35N)

Published paper: https://doi.org/10.1016/j.scitotenv.2021.150799

2011-10-20, protecția naturii, limite SCIESRI Romania

Limitele ariilor protejate de importanta avifaunistica din Romania, 2011-10-20.

The map shows the annual mean Nitrogen Dioxide (NO2) concentrations in Europe based on daily averages with at least 75% of valid measurements, in µg/m3 (source: EEA, AirBase v.8 & AQ e-Reporting)Thresholds used in the map for the annual values [µg/m3]:≤ 20> 20 ≤ 30> 30 ≤ 40: (40 µg/m3, limit value for human health as set out in the Air Quality Directive, 2008/50/EC, as well as the WHO's limit value for the annual mean)> 40 ≤ 50> 50Source: AirBase v.8 & AQ e-ReportingAirBase is the European air quality database maintained by the EEA through its European topic centre on Air pollution and Climate Change mitigation. It contains air quality monitoring data and information submitted by participating countries throughout Europe.The air quality database consists of a multi-annual time series of air quality measurement data and statistics for a number of air pollutants. It also contains meta-information on those monitoring networks involved, their stations and their measurements.The database covers geographically all EU Member States, the EEA member countries and some EEA candidate countries. The EU Member States are bound under Decision 97/101/EC to engage in a reciprocal exchange of information (EoI) on ambient air quality. The EEA engages with its member and collaborating countries to collect the information foreseen by the EoI Decision because air pollution is a pan European issue and the EEA is the European body which produces assessments of air quality, covering the whole geographical area of Europe.