The Environmental Data Explorer is the authoritative source for data sets used by UNEP and its partners in the Global Environment Outlook (GEO) report and other integrated environment assessments. Its online database holds more than 500 different variables, as national, subregional, regional and global statistics or as geospatial data sets (maps), covering themes like Freshwater, Population, Forests, Emissions, Climate, Disasters, Health and GDP. Display them on-the-fly as maps, graphs, data tables or download the data in different formats. By using the GetCapabilities request, one can see the whole list of available data layers.

Summary

Geojson files used to visualize geospatial layers relevant to identifying and assessing trucking fleet decarbonization opportunities with the MIT Climate & Sustainability Consortium's Geospatial Trucking Industry Decarbonization Explorer (Geo-TIDE) tool.

Relevant Links

Link to the online version of the tool (requires creation of a free user account).

Link to GitHub repo with source code to produce this dataset and deploy the Geo-TIDE tool locally.

Funding

This dataset was produced with support from the MIT Climate & Sustainability Consortium.

Original Data Sources

These geojson files draw from and synthesize a number of different datasets and tools. The original data sources and tools are described below:

Filename(s) Description of Original Data Source(s) Link(s) to Download Original Data License and Attribution for Original Data Source(s)

faf5_freight_flows/*.geojson

trucking_energy_demand.geojson

highway_assignment_links_*.geojson

infrastructure_pooling_thought_experiment/*.geojson

Regional and highway-level freight flow data obtained from the Freight Analysis Framework Version 5. Shapefiles for FAF5 region boundaries and highway links are obtained from the National Transportation Atlas Database. Emissions attributes are evaluated by incorporating data from the 2002 Vehicle Inventory and Use Survey and the GREET lifecycle emissions tool maintained by Argonne National Lab.

Shapefile for FAF5 Regions

Shapefile for FAF5 Highway Network Links

FAF5 2022 Origin-Destination Freight Flow database

FAF5 2022 Highway Assignment Results

Attribution for Shapefiles: United States Department of Transportation Bureau of Transportation Statistics National Transportation Atlas Database (NTAD). Available at: https://geodata.bts.gov/search?collection=Dataset.

License for Shapefiles: This NTAD dataset is a work of the United States government as defined in 17 U.S.C. § 101 and as such are not protected by any U.S. copyrights. This work is available for unrestricted public use.

Attribution for Origin-Destination Freight Flow database: National Transportation Research Center in the Oak Ridge National Laboratory with funding from the Bureau of Transportation Statistics and the Federal Highway Administration. Freight Analysis Framework Version 5: Origin-Destination Data. Available from: https://faf.ornl.gov/faf5/Default.aspx. Obtained on Aug 5, 2024. In the public domain.

Attribution for the 2022 Vehicle Inventory and Use Survey Data: United States Department of Transportation Bureau of Transportation Statistics. Vehicle Inventory and Use Survey (VIUS) 2002 [supporting datasets]. 2024. https://doi.org/10.21949/1506070

Attribution for the GREET tool (original publication): Argonne National Laboratory Energy Systems Division Center for Transportation Research. GREET Life-cycle Model. 2014. Available from this link.

Attribution for the GREET tool (2022 updates): Wang, Michael, et al. Summary of Expansions and Updates in GREET® 2022. United States. https://doi.org/10.2172/1891644

grid_emission_intensity/*.geojson

Emission intensity data is obtained from the eGRID database maintained by the United States Environmental Protection Agency.

eGRID subregion boundaries are obtained as a shapefile from the eGRID Mapping Files database.

eGRID database

Shapefile with eGRID subregion boundaries

Attribution for eGRID data: United States Environmental Protection Agency: eGRID with 2022 data. Available from https://www.epa.gov/egrid/download-data. In the public domain.

Attribution for shapefile: United States Environmental Protection Agency: eGRID Mapping Files. Available from https://www.epa.gov/egrid/egrid-mapping-files. In the public domain.

US_elec.geojson

US_hy.geojson

US_lng.geojson

US_cng.geojson

US_lpg.geojson

Locations of direct current fast chargers and refueling stations for alternative fuels along U.S. highways. Obtained directly from the Station Data for Alternative Fuel Corridors in the Alternative Fuels Data Center maintained by the United States Department of Energy Office of Energy Efficiency and Renewable Energy.

US_elec.geojson

US_hy.geojson

US_lng.geojson

US_cng.geojson

US_lpg.geojson

Attribution: U.S. Department of Energy, Energy Efficiency and Renewable Energy. Alternative Fueling Station Corridors. 2024. Available from: https://afdc.energy.gov/corridors. In the public domain.

These data and software code ("Data") are provided by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC ("Alliance"), for the U.S. Department of Energy ("DOE"), and may be used for any purpose whatsoever.

daily_grid_emission_profiles/*.geojson

Hourly emission intensity data obtained from ElectricityMaps.

Original data can be downloaded as csv files from the ElectricityMaps United States of America database

Shapefile with region boundaries used by ElectricityMaps

License: Open Database License (ODbL). Details here: https://www.electricitymaps.com/data-portal

Attribution for csv files: Electricity Maps (2024). United States of America 2022-23 Hourly Carbon Intensity Data (Version January 17, 2024). Electricity Maps Data Portal. https://www.electricitymaps.com/data-portal.

Attribution for shapefile with region boundaries: ElectricityMaps contributors (2024). electricitymaps-contrib (Version v1.155.0) [Computer software]. https://github.com/electricitymaps/electricitymaps-contrib.

gen_cap_2022_state_merged.geojson

trucking_energy_demand.geojson

Grid electricity generation and net summer power capacity data is obtained from the state-level electricity database maintained by the United States Energy Information Administration.

U.S. state boundaries obtained from this United States Department of the Interior U.S. Geological Survey ScienceBase-Catalog.

Annual electricity generation by state

Net summer capacity by state

Shapefile with U.S. state boundaries

Attribution for electricity generation and capacity data: U.S. Energy Information Administration (Aug 2024). Available from: https://www.eia.gov/electricity/data/state/. In the public domain.

electricity_rates_by_state_merged.geojson

Commercial electricity prices are obtained from the Electricity database maintained by the United States Energy Information Administration.

Electricity rate by state

Attribution: U.S. Energy Information Administration (Aug 2024). Available from: https://www.eia.gov/electricity/data.php. In the public domain.

demand_charges_merged.geojson

demand_charges_by_state.geojson

Maximum historical demand charges for each state and zip code are derived from a dataset compiled by the National Renewable Energy Laboratory in this this Data Catalog.

Historical demand charge dataset

The original dataset is compiled by the National Renewable Energy Laboratory (NREL), the U.S. Department of Energy (DOE), and the Alliance for Sustainable Energy, LLC ('Alliance').

Attribution: McLaren, Joyce, Pieter Gagnon, Daniel Zimny-Schmitt, Michael DeMinco, and Eric Wilson. 2017. 'Maximum demand charge rates for commercial and industrial electricity tariffs in the United States.' NREL Data Catalog. Golden, CO: National Renewable Energy Laboratory. Last updated: July 24, 2024. DOI: 10.7799/1392982.

eastcoast.geojson

midwest.geojson

la_i710.geojson

h2la.geojson

bayarea.geojson

saltlake.geojson

northeast.geojson

Highway corridors and regions targeted for heavy duty vehicle infrastructure projects are derived from a public announcement on February 15, 2023 by the United States Department of Energy.

The shapefile with Bay area boundaries is obtained from this Berkeley Library dataset.

The shapefile with Utah county boundaries is obtained from this dataset from the Utah Geospatial Resource Center.

Shapefile for Bay Area country boundaries

Shapefile for counties in Utah

Attribution for public announcement: United States Department of Energy. Biden-Harris Administration Announces Funding for Zero-Emission Medium- and Heavy-Duty Vehicle Corridors, Expansion of EV Charging in Underserved Communities (2023). Available from https://www.energy.gov/articles/biden-harris-administration-announces-funding-zero-emission-medium-and-heavy-duty-vehicle.

Attribution for Bay area boundaries: San Francisco (Calif.). Department Of Telecommunications and Information Services. Bay Area Counties. 2006. In the public domain.

Attribution for Utah boundaries: Utah Geospatial Resource Center & Lieutenant Governor's Office. Utah County Boundaries (2023). Available from https://gis.utah.gov/products/sgid/boundaries/county/.

License for Utah boundaries: Creative Commons 4.0 International License.

incentives_and_regulations/*.geojson

State-level incentives and regulations targeting heavy duty vehicles are collected from the State Laws and Incentives database maintained by the United States Department of Energy's Alternative Fuels Data Center.

Data was collected manually from the State Laws and Incentives database.

Attribution: U.S. Department of Energy, Energy Efficiency and Renewable Energy, Alternative Fuels Data Center. State Laws and Incentives. Accessed on Aug 5, 2024 from: https://afdc.energy.gov/laws/state. In the public domain.

These data and software code ("Data") are provided by the National Renewable Energy Laboratory ("NREL"), which is operated by the Alliance for Sustainable Energy, LLC ("Alliance"), for the U.S. Department of Energy ("DOE"), and may be used for any purpose whatsoever.

costs_and_emissions/*.geojson

diesel_price_by_state.geojson

trucking_energy_demand.geojson

Lifecycle costs and emissions of electric and diesel trucking are evaluated by adapting the model developed by Moreno Sader et al., and calibrated to the Run on Less dataset for the Tesla Semi collected from the 2023 PepsiCo Semi pilot by the North American Council for Freight Efficiency.

In

A geospatial interface will be developed using ArcIMS software. The interface will provide a means of accessing information stored in the SOFIA database and the SOFIA data exchange web site through a geospatial query. The spatial data will be served using the ArcSDE software, which provides a mechanism for storing spatial data in a relational database. A spatial database will be developed from existing data sets, including national USGS data sets, the Florida Geographic Digital Library, and other available data sets. Additional data sets will be developed from the published data sets available from PBS and other projects.

The South Florida restoration effort requires multidisciplinary information relating to present and historical conditions for use in responsible decision-making. The South Florida Information Access (SOFIA) database is the cornerstone of information management for the South Florida place-based science program. Currently, the SOFIA web site and database have a minimal geospatial interface which relies on the Geo-Data Explorer (GeoDE) system developed by the USGS Energy Resources Program in Reston. A geospatial interface using currently available commercial software (ArcIMS) is needed to develop a more easily maintained and user-friendly interface. Developing an interface that is directly connected to the SOFIA website and database will provide a more stable long term solution to providing a geospatial interface.

Welcome to Pennsylvania Conservation Explorer—a one stop shop for conservation planning and PNDI environmental review. The Explorer provides conservation information on biological diversity, protected lands, streams and other natural resources for planning purposes and also allows users to screen a project area for potential impacts to threatened, endangered, and special concern species.Conservation Planning: The Explorer allows users to access conservation planning information without having to log in. Here, users will see locations of natural heritage areas, protected lands and high quality streams. Users can prepare a conservation report for use in local planning or project specific assessment. Click here for Conservation Planning.PNDI Environmental Review: To access Pennsylvania Natural Diversity Inventory (PNDI) information for environmental review purposes, users will be required to register and login. To register, click on Create new account. After logging in, users will be able to view the same information as Conservation Planning, but they will also see PNDI species and habitat information. After viewing information in their project area, users can screen their project for potential impacts to PNDI species and obtain a PNDI Receipt with conservation measures, avoidance measures and next steps. If users obtain a PNDI receipt, a convenience charge of $40 per project using Visa, MasterCard or Discover Card will be applied. Click here for PNDI Environmental Review.

The Saudi Arabian geospatial analytics market, valued at $400 million in 2025, is poised for significant growth, exhibiting a Compound Annual Growth Rate (CAGR) of 9.22% from 2025 to 2033. This expansion is driven by several key factors. Firstly, substantial investments in infrastructure development, including smart city initiatives and digital transformation across various sectors, are fueling the demand for sophisticated geospatial analytics solutions. Secondly, the Kingdom's strategic focus on Vision 2030, which emphasizes diversification and technological advancement, is creating a favorable environment for the adoption of geospatial technologies across sectors such as agriculture, utilities, defense, and real estate. The increasing availability of high-resolution satellite imagery, coupled with advancements in data analytics and artificial intelligence (AI), further enhances the market's growth trajectory. Government initiatives promoting data sharing and open data platforms are also playing a crucial role. Segmentation reveals that network analysis and geovisualization are experiencing the fastest growth, driven by their applications in urban planning, resource management, and emergency response. Key players, including established technology giants like Microsoft and Esri, as well as specialized geospatial firms, are actively competing in this dynamic market, contributing to innovation and service diversification. Despite the promising outlook, challenges remain. Data security and privacy concerns related to handling sensitive geospatial data pose a significant restraint. Furthermore, the lack of skilled professionals proficient in geospatial analytics and data interpretation could hinder market growth in the short term. Nevertheless, ongoing investments in education and training programs should mitigate this issue. The overall market landscape indicates substantial potential for growth, particularly in leveraging geospatial analytics for sustainable development and effective resource allocation across Saudi Arabia's diverse sectors. The forecast period, spanning from 2025 to 2033, projects substantial market expansion, driven by consistent technological innovation and governmental support for digital transformation. Recent developments include: May 2023: Microsoft introduced three new functions for geospatial analysis in Azure Data Explorer, geo_point_buffer, geo_line_buffer, and geo_polygon_buffer. These functions allow users to create polygonal buffers around geospatial points, lines, or polygons, respectively, and return the resulting geometry. Users can use these functions to perform spatial operations such as intersection, containment, distance, or proximity on user geospatial data or to visualize data on maps., October 2022: ROSHN, the Kingdom of Saudi Arabia's nationwide real estate developer, backed by the government's Public Investment Fund (PIF), supported government efforts to improve homeownership rates while delivering sophisticated living standards. The Saudi Arabia designer built communities that looked to the nation's heritage and evolving resident aspirations. To support its vision and ongoing regional projects, ROSHN signed a memorandum of understanding (MOU) with Esri, the global player in location intelligence., . Key drivers for this market are: Increasing in Demand for Location Intelligence, Advancements of Big Data Analytics. Potential restraints include: Increasing in Demand for Location Intelligence, Advancements of Big Data Analytics. Notable trends are: Geovisualization is Expected to Hold Significant Share of the Market.

This dataset contains Arizona county boundaries for use in joining EPHT Data Explorer data to county-level geography using the "GeogID" column.Update Frequency: N/A

This web map supports the NOAA Ocean Exploration Data Atlas. The NOAA Ocean Exploration Data Atlas is a map-based data access portal.This web map, the Data Atlas, and the underlying geospatial data services are maintained by the NOAA National Centers for Environmental Information (NCEI). For a more comprehensive list of NCEI-maintained, ocean exploration geospatial data services, please visit the NOAA Ocean Exploration Data (NCEI) GeoPlatform group.Please provide any feedback or questions to OER.info.mgmt@noaa.gov.

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The data consists of: Scanned Capture of 450,000 pages and maps, including all of GSI principal datasets, (Mineral Exploration Reports-Open File, Geotechnical Reports, boreholes & tests, Historic 6":1 mile and 1":1 mile Geological Maps, GSI Publications, Bulletins, Published and Unpublished Reports, Groundwater Well Hydrographs, Marine Maps, Airborne Geophysical Maps, Mineral Locality Reports and Mine Record Reports and Maps).

This dataset defines the geographical information system (GIS) used to note the Council District boundaries for the City of Mesa, AZ. A geographic information system (GIS) is a conceptualized framework that provides the ability to capture and analyze spatial and geographic data. Dataset is used by the Capital Projects Explorer application (https://cip.mesaaz.gov).

This web map references the live tiled map service from the OpenStreetMap (OSM) project. OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap server: https://www.OpenStreetMap.org. See that website for additional information about OpenStreetMap. It is made available as a basemap for GIS work in ESRI products under a Creative Commons Attribution-ShareAlike license. Tip: This service is one of the basemaps used in the ArcGIS.com map viewer. Simply click one of those links to launch the interactive application of your choice, and then choose Open Street Map from the Basemap control to start using this service. You'll also find this service in the Basemap gallery in ArcGIS Explorer Desktop and ArcGIS Desktop 10. Tip: Here are some well known locations as they appear in this web map, accessed by launching the web map with a URL that contains location parameters: Athens, Cairo, Jakarta, Moscow, Mumbai, Nairobi, Paris, Rio De Janeiro, Shanghai

This dataset contains the name and geography ID of all the basins (groundwater) in Arizona.Use this spatial data to join data tables downloaded from the Arizona EPHT Explorer that has the "Geography" filter set to "Groundwater". This feature contains groundwater basin boundaries and provide base information for use in GIS systems to aid in assessment for a variety of planning and analysis purposes and to provide a geographic view with corresponding data. These data do not represent a legal record. Geography data was provided by Arizona Department of Water Resources (ADWR).Environmental Public Health Tracking (EPHT) is a tool to help Arizonans learn about environmental hazards in the state that could impact their health. EPHT was built on the idea that health and environmental problems are not always separate issues with unrelated solutions. EPHT has gathered data from national and local sources in order to view both environmental and health outcome data in one easily accessible place. For example, Arizonans can review air quality information and compare the information with respiratory issues such as asthma. Dataset and web based maps display a variety of topics in the Environmental Public Health Tracking network. For more information about where to download the data tables and how, feel free to visit the Arizona EPHT Explorer or the Environmental Public Health Tracking webpage. Last Update: June 2023Update Frequency: N/A

This map contains services collected from a variety of sources that will be used in the Northeast Region Ocean Council's (NROC) spatial prioritization process. The Biology group consists of suitability data and coral observations from the Marine Cadastre, marine mammal data from Duke University, and coral model areas from the Northeast Ocean Data Portal (NEODP).The Fisheries group contains lobster management areas from NOAA GARFO and coral protection area and commercial fishing management areas from NEODP.The Geoforms/Seascapes groups contains bathymetry from the Marine Cadastre, Seascape data from OCM, and survey and backscatter data from NEODP.The Geography group contains data from the Marine Cadastre, NEODP, and the Coastal Zone Management Gulf of Maine viewer (CZM GOM).The Geology and Infrastructure groups contains data from Marine Cadastre, NROC Data Explorer, and CZM GOM.The Navigation group contains data from the Marine Cadastre and NEODP.The Research and Permitting group contains data from the Bureau of Ocean Energy Management and the NROC Data Explorer.The Seafloor Hazards group contains data from the Marine Cadastre.