This data set includes maps of permafrost extent, permafrost temperature, the permafrost boundary, and ground ice thickness for all of Russia. The maps are ESRI Shapefiles, which were digitized from paper maps taken from the World Atlas of Snow and Ice Resources, 1997, Institute of Geography, Russian Academy of Sciences, Moscow, Russia. The scale of the source maps range from 1:20,000,000 to 1:40,000,000. Polygons were assigned attributes based on the classes used in the legends of the paper map.These data were extracted from a larger collection entitled Land Resources of Russia. Data and documentation © 2002 copyright International Institute for Applied Systems Analysis and the Russian Academy of Sciences.

Mapping Russian Wetlands and Estimating Methane Fluxes

Introduction

Wetlands are crucial in regulating the Earth’s climate, acting as both carbon sinks and significant methane sources. Russian wetlands represent one of the largest and most diverse wetland complexes globally, extending across biomes from Arctic tundra to boreal forests. Despite their importance, these wetlands remain underexplored, particularly in terms of their spatial distribution and greenhouse gas contributions. This dataset provides a detailed typological map of Russian wetlands and accompanying methane flux estimates, representing the most comprehensive methane emissions dataset for Russian wetlands to date. The maps and calculations were developed in Google Earth Engine (GEE) through a combination of multi-seasonal Landsat composites, PALSAR radar imagery, and extensive field-based validation data from peatland sites across Western Siberia.

Data Overview

Input Layers

The wetland mapping relied on seasonal Landsat composites (spring, summer, fall) and PALSAR radar data to capture the distinct structural and hydrological characteristics of each wetland type. Additional layers, such as GMTED topographic slope and Hansen’s TreeCover, were included to exclude non-wetland areas and to enhance the classification by distinguishing forested from non-forested wetlands.

Training Points

A comprehensive training site database was created, integrating field knowledge, high-resolution imagery, and georeferenced photos. Approximately 2,450 representative points were selected to capture 12 primary wetland types across Russia, with each point validated against high-resolution imagery to ensure accuracy. Points were collected to represent the wide-ranging wetland ecosystems in Russia, from open water and patterned bogs to swampy and forested fens, providing robust ground-truth data for training the classification model.

Random Forest Classifier

The random forest classifier was chosen for its capacity to handle large datasets and complex relationships among input layers. Optimized for Landsat and PALSAR inputs, the classifier used over 100 trees, each making independent predictions based on subsets of data, which were averaged to produce the final classification. This ensemble approach minimized overfitting, a crucial factor for the varied ecological regions across Russia.

Russian Wetlands Map

The final Russian Wetlands Map encompasses 12 wetland types, detailing their distribution and extent across the country:

• Total Wetland Area: 173.96 million hectares of mapped wetlands, capturing diverse ecosystems, including bogs, fens, and swampy areas.

• Open Water Area: Lakes, rivers, and smaller water bodies within wetland zones were separately mapped, totaling 42.6 million hectares.

Emission Modeling and Ecosite Analysis

Ecosite Proportions for Methane Emission Modeling

Each wetland type was further divided into ecosite units representing distinct, smaller areas with uniform hydrological and geochemical properties. This level of detail enabled precise methane emission estimates by capturing the variability within complex wetland ecosystems. For instance, ridges and hollows within patterned bogs exhibit unique methane emission dynamics due to differences in vegetation and water levels. Ecosite proportions for methane emission were calculated from 20-30 representative field sites per wetland type, capturing the typical area breakdown of each wetland type across Russia.

Methane Emission Period Calculation

To estimate seasonal methane emission periods across Russia’s climatic zones, the average summer temperature (Bio10) parameter from WorldClim data was used. Bio10 values reflect seasonal variation in emission potential, correlating with longer and warmer summers in southern regions versus shorter, cooler summers in the north. Using these data, an emission period was calculated for each 50 km x 50 km grid cell based on a regression model derived from Western Siberia data:
Emission Period (hours) = 303 * Bio10 – 675

This equation, which explained 98% of the variation in emission duration, provided a dynamic method for estimating emission periods across Russia’s diverse landscape.

Methane Emission Estimates

Calculation Approach

Methane emission estimates were derived from a multi-step approach that incorporated ecosystem-specific emission factors, ecosystem area, and the estimated emission period:

1. Ecosystem Area Calculation: Area estimates for each ecosite type were derived from field-based proportions applied to the classified wetland map.

2. Emission Period: Calculated for each grid cell based on Bio10 data, varying continuously across climatic zones.

3. Methane Flux Values: Based on quantiles from field measurements within three main zones (Tundra, Northern Taiga, and Southern Taiga) to account for natural variability in methane emissions.

Using this approach, methane emissions were calculated for each 50 km per 50 km grid cell, factoring in the unique emission characteristics of each wetland type and zone. This produced a spatially detailed estimate of methane fluxes, reflective of the temperature and vegetation gradients across Russia.

Resulting National Estimate

• Total Annual Methane Emissions: 11.39 MtCH₄ per year from all mapped wetland areas.

• Open Water Contributions: 2.54 MtCH₄ per year from open water bodies, including intra-wetland lakes and rivers.

Data Highlights

• High-resolution wetland classification covering 173.96 million hectares across diverse wetland ecosystems.

• Detailed methane emission data derived from multi-year field measurements and validated against climatic data, providing spatially continuous methane flux estimates across Russia.

• 50x50 km² grid cell calculations, accounting for methane emission rates, emission periods, and ecosystem proportions for each cell.

This dataset serves as an essential tool for environmental scientists, climate modelers, and conservationists, supporting further research into wetland carbon dynamics, climate mitigation strategies, and regional land-use planning. The high resolution data availbale at url: https://code.earthengine.google.com/d6a9d4045255fd84298777e56a38ae03

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Contains:World HillshadeWorld Street Map (with Relief) - Base LayerLarge Scale International Boundaries (v11.3)World Street Map (with Relief) - LabelsDoS Country Labels DoS Country LabelsCountry (admin 0) labels that have been vetted for compliance with foreign policy and legal requirements. These labels are part of the US Federal Government Basemap, which contains the borders and place names that have been vetted for compliance with foreign policy and legal requirements.Source: DoS Country Labels - Overview (arcgis.com)Large Scale International BoundariesVersion 11.3Release Date: December 19, 2023DownloadFor more information on the LSIB click here: https://geodata.state.gov/ A direct link to the data is available here: https://data.geodata.state.gov/LSIB.zipAn ISO-compliant version of the LSIB metadata (in ISO 19139 format) is here: https://geodata.state.gov/geonetwork/srv/eng/catalog.search#/metadata/3bdb81a0-c1b9-439a-a0b1-85dac30c59b2 Direct inquiries to internationalboundaries@state.govOverviewThe Office of the Geographer and Global Issues at the U.S. Department of State produces the Large Scale International Boundaries (LSIB) dataset. The current edition is version 11.3 (published 19 December 2023). The 11.3 release contains updates to boundary lines and data refinements enabling reuse of the dataset. These data and generalized derivatives are the only international boundary lines approved for U.S. Government use. The contents of this dataset reflect U.S. Government policy on international boundary alignment, political recognition, and dispute status. They do not necessarily reflect de facto limits of control.National Geospatial Data AssetThis dataset is a National Geospatial Data Asset managed by the Department of State on behalf of the Federal Geographic Data Committee's International Boundaries Theme.DetailsSources for these data include treaties, relevant maps, and data from boundary commissions and national mapping agencies. Where available and applicable, the dataset incorporates information from courts, tribunals, and international arbitrations. The research and recovery process involves analysis of satellite imagery and elevation data. Due to the limitations of source materials and processing techniques, most lines are within 100 meters of their true position on the ground.Attribute StructureThe dataset uses thefollowing attributes:Attribute NameCC1COUNTRY1CC2COUNTRY2RANKSTATUSLABELNOTES These attributes are logically linked:Linked AttributesCC1COUNTRY1CC2COUNTRY2RANKSTATUS These attributes have external sources:Attribute NameExternal Data SourceCC1GENCCOUNTRY1DoS ListsCC2GENCCOUNTRY2DoS ListsThe eight attributes listed above describe the boundary lines contained within the LSIB dataset in both a human and machine-readable fashion. Other attributes in the release include "FID", "Shape", and "Shape_Leng" are components of the shapefile format and do not form an intrinsic part of the LSIB."CC1" and "CC2" fields are machine readable fields which contain political entity codes. These codes are derived from the Geopolitical Entities, Names, and Codes Standard (GENC) Edition 3 Update 18. The dataset uses the GENC two-character codes. The code ‘Q2’, which is not in GENC, denotes a line in the LSIB representing a boundary associated with an area not contained within the GENC standard.The "COUNTRY1" and "COUNTRY2" fields contain human-readable text corresponding to the name of the political entity. These names are names approved by the U.S. Board on Geographic Names (BGN) as incorporated in the list of Independent States in the World and the list of Dependencies and Areas of Special Sovereignty maintained by the Department of State. To ensure the greatest compatibility, names are presented without diacritics and certain names are rendered using commonly accepted cartographic abbreviations. Names for lines associated with the code ‘Q2’ are descriptive and are not necessarily BGN-approved. Names rendered in all CAPITAL LETTERS are names of independent states. Other names are those associated with dependencies, areas of special sovereignty, or are otherwise presented for the convenience of the user.The following fields are an intrinsic part of the LSIB dataset and do not rely on external sources:Attribute NameMandatoryContains NullsRANKYesNoSTATUSYesNoLABELNoYesNOTESNoYesNeither the "RANK" nor "STATUS" field contains null values; the "LABEL" and "NOTES" fields do.The "RANK" field is a numeric, machine-readable expression of the "STATUS" field. Collectively, these fields encode the views of the United States Government on the political status of the boundary line.Attribute NameValueRANK123STATUSInternational BoundaryOther Line of International Separation Special Line A value of "1" in the "RANK" field corresponds to an "International Boundary" value in the "STATUS" field. Values of "2" and "3" correspond to "Other Line of International Separation" and "Special Line", respectively.The "LABEL" field contains required text necessarily to describe the line segment. The "LABEL" field is used when the line segment is displayed on maps or other forms of cartographic visualizations. This includes most interactive products. The requirement to incorporate the contents of the "LABEL" field on these products is scale dependent. If a label is legible at the scale of a given static product a proper use of this dataset would encourage the application of that label. Using the contents of the "COUNTRY1" and "COUNTRY2" fields in the generation of a line segment label is not required. The "STATUS" field is not a line labeling field but does contain the preferred description for the three LSIB line types when lines are incorporated into a map legend. Using the "CC1", "CC2", or "RANK" fields for labeling purposes is prohibited.The "NOTES" field contains an explanation of any applicable special circumstances modifying the lines. This information can pertain to the origins of the boundary lines, any limitations regarding the purpose of the lines, or the original source of the line. Use of the "NOTES" field for labeling purposes is prohibited.External Data SourcesGeopolitical Entities, Names, and Codes Registry: https://nsgreg.nga.mil/GENC-overview.jspU.S. Department of State List of Independent States in the World: https://www.state.gov/independent-states-in-the-world/U.S. Department of State List of Dependencies and Areas of Special Sovereignty: https://www.state.gov/dependencies-and-areas-of-special-sovereignty/The source for the U.S.—Canada international boundary (NGDAID97) is the International Boundary Commission: https://www.internationalboundarycommission.org/en/maps-coordinates/coordinates.phpThe source for the “International Boundary between the United States of America and the United States of Mexico” (NGDAID82) is the International Boundary and Water Commission: https://catalog.data.gov/dataset?q=usibwcCartographic UsageCartographic usage of the LSIB requires a visual differentiation between the three categories of boundaries. Specifically, this differentiation must be between:- International Boundaries (Rank 1);- Other Lines of International Separation (Rank 2); and- Special Lines (Rank 3).Rank 1 lines must be the most visually prominent. Rank 2 lines must be less visually prominent than Rank 1 lines. Rank 3 lines must be shown in a manner visually subordinate to Ranks 1 and 2. Where scale permits, Rank 2 and 3 lines must be labeled in accordance with the “Label” field. Data marked with a Rank 2 or 3 designation does not necessarily correspond to a disputed boundary.Additional cartographic information can be found in Guidance Bulletins (https://hiu.state.gov/data/cartographic_guidance_bulletins/) published by the Office of the Geographer and Global Issues.ContactDirect inquiries to internationalboundaries@state.gov.CreditsThe lines in the LSIB dataset are the product of decades of collaboration between geographers at the Department of State and the National Geospatial-Intelligence Agency with contributions from the Central Intelligence Agency and the UK Defence Geographic Centre.Attribution is welcome: U.S. Department of State, Office of the Geographer and Global Issues.Changes from Prior ReleaseThe 11.3 release is the third update in the version 11 series.This version of the LSIB contains changes and accuracy refinements for the following line segments. These changes reflect improvements in spatial accuracy derived from newly available source materials, an ongoing review process, or the publication of new treaties or agreements. Notable changes to lines include:• AFGHANISTAN / IRAN• ALBANIA / GREECE• ALBANIA / KOSOVO• ALBANIA/MONTENEGRO• ALBANIA / NORTH MACEDONIA• ALGERIA / MOROCCO• ARGENTINA / BOLIVIA• ARGENTINA / CHILE• BELARUS / POLAND• BOLIVIA / PARAGUAY• BRAZIL / GUYANA• BRAZIL / VENEZUELA• BRAZIL / French Guiana (FR.)• BRAZIL / SURINAME• CAMBODIA / LAOS• CAMBODIA / VIETNAM• CAMEROON / CHAD• CAMEROON / NIGERIA• CHINA / INDIA• CHINA / NORTH KOREA• CHINA / Aksai Chin• COLOMBIA / VENEZUELA• CONGO, DEM. REP. OF THE / UGANDA• CZECHIA / GERMANY• EGYPT / LIBYA• ESTONIA / RUSSIA• French Guiana (FR.) / SURINAME• GREECE / NORTH MACEDONIA• GUYANA / VENEZUELA• INDIA / Aksai Chin• KAZAKHSTAN / RUSSIA• KOSOVO / MONTENEGRO• KOSOVO / SERBIA• LAOS / VIETNAM• LATVIA / LITHUANIA• MEXICO / UNITED STATES• MONTENEGRO / SERBIA• MOROCCO / SPAIN• POLAND / RUSSIA• ROMANIA / UKRAINEVersions 11.0 and 11.1 were updates to boundary lines. Like this version, they also contained topology fixes, land boundary terminus refinements, and tripoint adjustments. Version 11.2 corrected a few errors in the attribute data and ensured that CC1 and CC2 attributes are in alignment with an updated version of the Geopolitical Entities, Names, and Codes (GENC) Standard, specifically Edition 3 Update 17.LayersLarge_Scale_International_BoundariesTerms of

The mission of the Humanitarian Information Unit (HIU) is to serve as a U.S. Government interagency center to identify, collect, analyze, and disseminate all-source information critical to U.S. Government decision-makers and partners in preparation for and response to humanitarian emergencies worldwide, and to promote innovative technologies and best practices for humanitarian information management.

This data set is a vector coverage of the Map of Natural Landscape and Permafrost Zones and the Net of Soil Temperature Meteorological Stations in Russia and Middle Asian Mountains (scale 1:4000000), published by the Russian Academy of Sciences Earth Cryosphere Institute and Institute for Phytochemical and Biological Problems in Earth Science The original map was compiled by E. Melnikov and D.A. Gilichinsky. The digital map was created in Geograph, which is a Geographic Information System developed by the GIS Research Center, Institute of Geography, Russian Academy of Sciences. Data are available through FTP.

Over 1.2 million refugees from Ukraine due to the Russian invasion fled to Germany as of April 2025. Furthermore, the second-highest number was recorded in Russia. In total, around 6.4 million Ukrainian refugees were registered across Europe and 6.9 million worldwide as of April 2025. Most of them fled the country by crossing the border with Poland. Ukrainian refugees in Germany As of January 2025, over 1.2 million refugees from Ukraine were recorded in Germany. The first increases in the number of Ukrainian refugees were registered in March and April 2022. At the end of January 2023, over one million refugees were officially counted by the authorities. Germany had the highest monthly financial allowance for Ukrainians who fled the war compared to other European countries as of June 2022. Temporary protection for Ukrainian refugees in the EU European Union (EU) members implemented the Temporary Protection Directive (TPD), which guaranteed access to accommodation, welfare, and healthcare to refugees from Ukraine. People fleeing the war had a right to a residence permit in the EU, enter the labor market, and enroll children in educational institutions. The protection is granted until March 4, 2026, but it can be extended in the future depending on the situation in the country.

Case data from 03-22-2020 to 08-16-2020, this data repository stores COVID-19 virus case data for Russia, including daily case data, summary data, and base map. Each zip file contains weekly case data from Monday to Sunday.

This data set was edited from the data collected by the Alaska Department of Natural Resources and the ESRI Russia dataset. The files were clipped to show only the three Alaskan and three Russian communities. Original shapefiles were obtained through the Alaska State Geo-Spatial Data Clearinghouse (http://www.asgdc.state.ak.us) and Geocommunity (http://www.geocomm.com). The community spatial data and base Alaska and Russian maps were obtained and clipped for the use of the Berin Sea Sub-Network (BSSN) map.

Generalized schematic maps and state of water pollution based on integrated satellite and ground data. Period - 2013

The CD-ROM and online access present the spatial and attribute databases and the technical reports produced during the execution of the Mapping of Soil and Terrain Vulnerability in Central and Eastern Europe (SOVEUR) project (GCP/RER/107/NET) between February 1997 and April 2000.

The project activities were implemented under a contractual service agreement with the International Soil Reference and Information Centre (ISRIC) which included letters of agreement with national institutes in the participating countries. The project was technically backstopped by the Land and Plant Nutrient Management Service (AGLL).

The spatial and attribute databases contain: (1) a harmonized soil and terrain database for 13 countries in eastern Europe at 1:2.5 million scale, compiled following the SOTER principles, including georeferenced soil profile data; (2) a database and associated maps on the status of soil degradation in the region including an evaluation of the extent, type, severity, causes and trends; (3) a database and associated maps on the vulnerability to pollution, in particular by 11 metals: Cd, Mn, Ni, Co, Zn, Cu, Cr, Pb, Hg, Fe and Al.

The 13 countries covered by this project are: Belarus, Bulgaria, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Moldova, Poland, Romania, Russia, Slovakia, and Ukraine. All the coverages are in Geographic Projection (Latitude/Longitude), while the maps given as Images are in Lambert projection (Central Meridian 25 0 0, 1st Standard parallel 60 0 0, 2nd Standard Parallel 40 0 0; units metres).

All the coverages presented are either in PC Arc/Info or in Arc/Info export format with no compression.

The technical reports included cover the various technical documentation and guidelines prepared for the compilation of the various spatial databases. They also contain proceedings of two workshops held by the SOVEUR project.

A Shareware directory on the CD contains subdirectories with executable files that permit downloading of shareware versions of ACROBAT 4.0 and the ACDSee graphics viewer. These programs are needed to consult the enclosed technical reports (PDF files) and the image (JPG) files that show selected map outputs of the SOVEUR project.

Soil and Terrain Database, Land Degradation Status and Soil Vulnerability Assessment for Central and Eastern Europe, Version 1.0 (1:2.5 Million Scale) is provided on CD-ROM by the FAO, Land and Water Digital Media Series (Number 10). The CD-ROM can be purchased from FAO, Sales and Marketing Group, Viale delle Terme di Caracalla 0100 Rome, Italy (Fax: +39-06-5705-3360 E-mail: publications-sales@fao.org) (Price: US$40).

This data set consists of maps of various soil characteristics for all of Russia. The maps are available as ESRI Shapefiles and they are accompanied by databases of soil profiles and related characteristics. The soil classification Shapefile was generalized from the standard 1:2,500,000 soil map of Russia (Fridland, 1988). Several different soil classifications are presented as well as detailed soil characteristics. Additionally, investigators compiled two databases (.dbf files) of detailed soil characteristics from 234 measured soil profiles. These data were extracted from a larger collection entitled Land Resources of Russia. Data and documentation © 2002 copyright International Institute for Applied Systems Analysis and the Russian Academy of Sciences.

The Soil and Physiographic Database for Northern and Central Eurasia (1:5 Million Scale) CD-ROM contains reports, databases, and digital maps for North and Central Eurasia region [covering China (including the Taiwan Province of China), Mongolia, and all countries of the former Soviet Union (CIS and Baltic States)]. The database was prepared by the Food and Agriculture Organization of the United Nations (FAO) and the International Institute for Applied Systems Analysis (IIASA) in co-operation with the Dokuchaiev Institute of Soil Science, Moscow, Russia and the Institute of Soil Science, Academia Sinica, Nanjing, China. The preparation of this database is part of a larger FAO programme that aims to produce a systematic update of the soil and terrain database for the whole world. This effort is supported by a number of international institutes and organizations such as the United Nations Environment Programme (UNEP), the International Soil Resources Information Centre (ISRIC), and the European Soil Bureau (ESB), and is only possible through contribution of national soil institutes worldwide.

The soil information in this database has been derived from several sources, in particular the 1:2.5 Million Soil Map of the Former Soviet Union prepared by Friedland in the Dokuchaiev Institute, Moscow, and the Soil Map of China at 1:4 million scale prepared by the Institute of Soil Science of the Academia Sinica in Nanjing. All soil information has been correlated with the Revised Legend of the Soil Map of the World.

For Mongolia and the countries of the CIS and Baltic States, the physiographic coverage was prepared by the Dokuchaiev Institute according to the principles developed for soil and terrain databases (SOTER) by ISRIC, FAO and UNEP. For China, the physiographic layer was prepared as part of a larger project assessing land degradation in Asia according to the same principles.

For the Russian Federation and China, an integration of the soil and physiographic layer has been carried out; for the other areas, both layers have been prepared separately and no correlation has been attempted.

Apart from selected examples in the report on soils of China, the database does not contain any soil profile description nor soil analytical results. Documentation on the soils of the Russian Federation, the physiography of the CIS and Baltic States, and on soils of China is included on the CD-ROM.

The results presented on the CD-ROM are in part provisional, as efforts are under way to produce a full SOTER database for Eastern Europe at 1:2.5 million scale. This will improve the information available for the European part of the Russian Federation, Ukraine, and Belarus (Byelarus). In addition, more recent and more detailed regional soil information exists on the Russian Federation and on China.

Soil and Physiographic Database for North and Central Eurasia at 1:5 Million Scale is provided on CD-ROM by the FAO, Land and Water Digital Media Series (Number 7). The CD-ROM can be purchased (Price: US$40) from FAO, Sales and Marketing Group, Viale delle Terme di Caracalla 0100 Rome, Italy (Fax: +39-06-5705-3360 E-mail: publications-sales@fao.org).

This polygon shapefile is an index to the map series, '浦潮近傍 二万五千分一圖 -- Urajio kinbō 1:25,000.' This map series was originally produced by the Japanese Land Survey Department of the General Staff Headquarters [1919-1920]. Stanford University Libraries holds a large collection of Japanese military and imperial maps, referred to as gaihōzu, or 'maps of outer lands.' These maps were produced starting in the early Meiji (1868-1912) era and the end of World War II by the Land Survey Department of the General Staff Headquarters, the former Japanese Army. The Library is in the process of scanning and making available all of the maps in the collection.

The Oil and Gas Infrastructure Mapping (OGIM) database is a global, spatially explicit, and granular dataset of oil and gas infrastructure. It is developed by Environmental Defense Fund (EDF) (www.edf.org) and MethaneSAT, LLC (www.methanesat.org), a wholly owned subsidiary of EDF. The OGIM database helps fill a crucial geospatial data need, by supporting the quantification and source characterization of oil and gas methane emissions. The database is developed via acquisition, analysis, curation, integration, and quality-assurance (performed at EDF) of publicly available geospatial data sources. These oil and gas facility datasets are reported by governments, industry, academics, and other non-government entities.

OGIM is a collection of data tables within a GeoPackage. Each data table within the GeoPackage includes locations and facility attributes of oil and gas infrastructure types that are important sources of methane emissions, including: oil and gas production wells, offshore production platforms, natural gas compressor stations, oil and natural gas processing facilities, liquefied natural gas facilities, crude oil refineries, and pipelines. OGIM v2.7 includes approximately 6.7 million features, including 4.5 million point locations of oil and gas wells and over 1.2 million kilometers of oil and gas pipelines.

Please see the PDF document in the “Files” section of this page for more information about this version, including attribute column definitions, key changes since the previous version, and more. Full details on database development and related analytics can be found in the following Earth System Science Data (ESSD) journal paper. Please cite this paper when using any version of the database:

Omara, M., Gautam, R., O'Brien, M., Himmelberger, A., Franco, A., Meisenhelder, K., Hauser, G., Lyon, D., Chulakadabba, A., Miller, C., Franklin, J., Wofsy, S., and Hamburg, S.: Developing a spatially explicit global oil and gas infrastructure database for characterizing methane emission sources at high resolution, Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-15-3761-2023, 2023.

Important note: While the results section of this manuscript is specific to v1 of the OGIM, the methods described therein are the same methods used to develop and update v2.7. Additionally, while we describe our data sources in detail in the manuscript above, and include maps of all acquired datasets, this open-access version of the OGIM database does not include the locations of about 300 natural gas compressor stations in Russia. Future updates may include these locations when appropriate permissions to make them publicly accessible are obtained.

OGIM v2.7 is based on public-domain datasets reported in February 2025 or prior. Each record in OGIM indicates a date (SRC_DATE) when the original source of the record was published or last updated. Some records may contain out-of-date information, for example, if a facility’s status has changed since we last visited a data source. We anticipate updating the OGIM database on a regular cadence and are continually including new public domain datasets as they become available.

Point of Contact at Environmental Defense Fund and MethaneSAT, LLC: Madeleine O’Brien (maobrien@methanesat.org) and Mark Omara (momara@edf.org).

This layer can be used for watershed analysis and planning in the Russian River region of California.

This dataset is a 1:15 million scale map of forest stand carbon for the land area of Russia (Stone et al., 2000). The objective was to create a first approximation of the forest stand carbon reserves of Russia. Data include continuous estimates of forest stand carbon in units of metric tons/ha of carbon (C) and categorized data depicting rages of forest stand carbon. The resulting maps show forest stand C by region in a spatially explicit form. It is the first map of its type for Russia of which we are aware. The mapped C represents 96% of the total of 26.1 Pg forest tree stand C described by Alexeyev and Birdsey (1994) and Alexeyev et al. (1995). Of the remaining 4%, nearly half was due to bushes, which were assumed not to be mapped in the 1973 forest cover map.The source data for the forest stand carbon map were acquired by map digitization from the Atlas of Forests for the Soviet Union (State Committee on Forests, 1973) and spatial application and arithmetic manipulation of carbon storage data from Alexeyev and Birdsey (1998).

Double-sided satellite image and topographic map of Beaver Lake, Antarctica. These maps were produced for the Australian Antarctic Division by AUSLIG (now Geoscience Australia) Commercial, in Australia, in 1990. Both maps are at a scale of 1:100 000. The satellite image map was produced from SPOT 1 and LANDSAT 5 TM scenes. It is projected on a Transverse Mercator projection, and shows glaciers/ice shelves, stations/bases and gives some historical text information. The map has both geographical and UTM co-ordinates. Contours on the topographic map were derived from Russian maps (values have not been verified.) This map is also projected on a transverse mercator projection, and shows traverses/routes/foot track charts, bases/stations, glaciers/ice shelves, survey marks, and gives some historical text information.

Important Note: This item is in mature support as of July 2021. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.World Street Map includes highways, major roads, minor roads, one-way arrow indicators, railways, water features, cities, parks, landmarks, building footprints, and administrative boundaries, overlaid on shaded relief for added context.This basemap is compiled from a variety of authoritative sources from several data providers, including the U.S. Geological Survey (USGS), U.S. Environmental Protection Agency (EPA), U.S. National Park Service (NPS), Food and Agriculture Organization of the United Nations (FAO), Department of Natural Resources Canada (NRCAN), HERE, and Esri. Data for select areas is sourced from OpenStreetMap contributors. Specific country list and documentation of Esri's process for including OSM data is available to view. Additionally, data for the World Street Map is provided by the GIS community through the Community Maps Program. For details on data sources contributed by the GIS community in this map, view the list of Contributors for the World Street Map.CoverageThe map provides coverage for the world down to ~1:72k and street-level data down to ~1:4k across the United States; most of Canada; Japan; Europe; much of Russia; Australia and New Zealand; India; most of the Middle East; Pacific Island nations; South America; Central America; and Africa. Coverage in select urban areas is provided down to ~1:1k.UseYou can add this layer to the ArcGIS Online Map Viewer, ArcGIS Desktop, or ArcGIS Pro. To view this layer in a web map, see this Streets basemap.

This polygon shapefile is an index to 1:200,000 scale maps of Japan, Kuril Islands (Russia), Taiwan, titled 'Nijūmanbun no ichi teikokuzu -- Teikokuzu -- 二十万分一帝國圖 -- 帝國圖.’ This map series was originally produced by the Japanese Land Survey Department of the General Staff Headquarters between 1906 and 1944. Stanford University Libraries holds a large collection of Japanese military and imperial maps, referred to as gaihōzu, or "maps of outer lands." These maps were produced starting in the early Meiji (1868-1912) era and the end of World War II by the Land Survey Department of the General Staff Headquarters, the former Japanese Army. The Library is in the process of scanning and making available all of the maps in the collection. To create this index, footprints were generated using the fishnet tool, and metadata were supplied for the digitized paper maps by Stanford University Libraries. After the footprints were created, the shapefile was trimmed and labeled according to the sources.