Facebook
TwitterHalf-mile access sheds to open access open space in the conservation areas dataset built for CA Nature. Each has been intersected to a city and county dataset to allow summarization of demographics. These were then enriched using ESRI's geoenrichment services to provide select demographics. Three layers are included:1. Half-mile access sheds from open access areas considered 30x30 Conservation Areas (GAP Code 1 and 2)2. Half-mile access sheds from open access areas in the Conservation Areas dataset (GAP Codes 1, 2, 3, 4)3. All city and county areas to provide baseline demographics for comparison. Demographic variables include:PopulationAge DistributionEducational AttainmentHousing Unit OccupancyHispanic or Latino OriginRaceHousehold income
Facebook
TwitterSEMCOG's Community Explorer tool is great for dynamically visualizing demographic and economic data in Southeast Michigan. Use this dataset to extend Community Explorer and make your own visualization.This tool has over 40 indicators across 4 geography types (County, Community, School Districts, Census Tracts). Not only are the data columns available, but we also include the Margin of Error (MOE) to better understand the reliability of each column.IndicatorsTotal PopulationPopulation Density (Persons/Acre)Median AgePercent Age 65+Percent Age 65+ Living AlonePercent Ages 5 to 17Ratio Youth to SeniorsPercent Bachelor's Degree or HigherPercent People in PovertyPercent AsianPercent BlackPercent HispanicPercent WhiteTotal HouseholdsAverage Household SizePercent Households with SeniorsPercent Households with ChildrenPercent Households with No CarPercent Households with Internet AccessTotal Households without Internet AccessPercent Households with Broadband Internet AccessTotal Households without Broadband Internet AccessPercentage Households with Computing DevicesTotal Households without a Desktop or LaptopPercent Seniors with Broadband Internet AccessPercent Children without Broadband Internet AccessPercent Children without Computing DevicesTotal Housing UnitsPercent VacantPercent Owner OccupiedPercent Renter OccupiedPercent Single FamilyPercent Multi-FamilyTotal JobsJob Density (Jobs/Acre)Unemployment RateLabor Force Participation RateMedian Household IncomePer Capita IncomeMedian Housing ValueAverage Commute Time (Minutes)Percent Drive Alone to WorkPercent Commute by Transit
Facebook
TwitterThis explorer provides sample premium information for individual ACA-compliant health insurance plans available to Iowans for 2025.
Facebook
TwitterThe Equity Explorer Tool allows users to explore census tracts throughout Los Angeles County to identify areas of the highest need based on populations disproportionately affected by COVID-19 prior to embarking on project design by either using the map or a series of filters.To use the Equity Explorer, users can leverage the following capabilities:Core COVID Filters: Apply the various COVID filters in the Core COVID Filters section of the far left pane. These filters include the COVID index scores and categories, the individual index components, HUD Qualified tract status, and other location attributes (like CSA). As filters in this section are applied, the map will update to reflect only tracts meeting the criteria and the summary statistics and table will update accordingly. To turn the filter on, toggle the radio button to the right of the filter. The filter is on when the button is blue. Thematic Filters: Apply any additional filters in the Thematic Filters section. Please note, these filters do not impact the summary statistics at the bottom of the application or the table of tracts. The corresponding layer(s) will need to be turned on using the map layer list to see the filter results. Map Selection: In addition to the above filters, tracts can also be selected directly on the map using the map select tool in the upper left corner of the map. Table Widget: Once the list of tracts has been narrowed down appropriately for the program, tracts can be exported by clicking the table widget in the upper right corner, next to the documentation button. Navigate to the COVID Index tab, click the 4 dot icon to the right of the table, and export records as a CSV. Summary Statistics: As the COVID filters are applied or a selection is made on the map, the statistics at the bottom of the screen will update. Map Layer List: To additional layers on or off the map, click the eye icon next to a layer name in the map layer list in the far right paneMap Legend: The map legend in the bottom right corner will update to show information about the layers currently being visualized on the map.For more information, please contact egis@isd.lacounty.gov or race-equity@ceo.lacounty.gov
Facebook
TwitterExplore, visualise and interact with youth-centered data. Includes data on poverty, education, employment, and demographics.
Facebook
TwitterArcGIS Experience Builder Application designed to find and download Weld County Assessor sales and account data. Sales data includes all sales in Weld County since 1/1/2010, as tracked by the Assessor's office. Account data includes one record for each account in Weld County. For accounts with multiple buildings or multiple property types, characteristics have been aggregated for the entire parcel.
Facebook
TwitterUse the American Viticultural Area (AVA) Map Explorer to view the boundaries of all established and proposed AVAs. The Map Explorer has information about each AVA, including its state and county, when it was established, what other AVAs it contains or is within, and a link to its codified official boundary description. You can even plot an address on the Map Explorer to see if that location is within an AVA. You can also download "shapefiles" for the various AVAs, which you can use with geographic information system (GIS) software.
Facebook
TwitterThis Map will now be the root map feeding a testing app for the next version of the GIS Data Explorer, 3.0
Facebook
TwitterHalf-mile access sheds to open access open space in the conservation areas dataset built for CA Nature. Each has been intersected to a city and county dataset to allow summarization of demographics. These were then enriched using ESRI's geoenrichment services to provide select demographics. Three layers are included:1. Half-mile access sheds from open access areas considered 30x30 Conservation Areas (GAP Code 1 and 2)2. Half-mile access sheds from open access areas in the Conservation Areas dataset (GAP Codes 1, 2, 3, 4)3. All city and county areas to provide baseline demographics for comparison. Demographic variables include:PopulationAge DistributionEducational AttainmentHousing Unit OccupancyHispanic or Latino OriginRaceHousehold income
Facebook
TwitterDataset is an overview of food access indicators for low-income and other census tracts using different measures of supermarket accessibility. This dataset provides food access data for populations within census tracts; and offers census-tract-level data on food access that can be used for community planning or research purposes.Data from USDA Economic Research Service (ERS) Food Access Research Atlas, 2019. Last updated 4/27/2021.See also USDA map service at https://gisportal.ers.usda.gov/server/rest/services/FARA/FARA_2019/MapServer.
Facebook
TwitterExplorer Fishing Co Limited Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Explore all the relevant socio-economic facts about Fresno County. Social Explorer Profiles takes you from raw data to meaningful stories, helps you analyze data, discover trends and gain insight into the world around you!
Facebook
TwitterState and territorial executive orders, administrative orders, resolutions, proclamations, and other official publicly available government communications are collected from government websites and cataloged and coded using Microsoft Excel by one or more coders with one or more additional coders conducting quality assurance.
Data were collected to determine when individuals in states and territories were subject to executive orders, administrative orders, resolutions, proclamations, and other official publicly available government communications related to COVID-19 banning gatherings of various sizes either (1) generally, or specified that the gathering limit applied only when social distancing was not possible, or (2) even if participants practiced social distancing.
These data are derived from on the publicly available state and territorial executive orders, administrative orders, resolutions, and proclamations (“orders”) for COVID-19 that expressly ban gatherings found by the CDC, COVID-19 Community Intervention and Critical Populations Task Force, Monitoring and Evaluation Team & CDC, Center for State, Tribal, Local, and Territorial Support, Public Health Law Program from March 11, 2020 through August 15, 2021. These data will be updated as new orders are collected. Any orders not available through publicly accessible websites are not included in these data. Only official copies of the documents or, where official copies were unavailable, official press releases from government websites describing requirements were coded, as well as official government communications such as announcements that counties have progressed through new phases of reopening pursuant to an executive order, directive, or other executive branch action, and posted to government websites; news media reports on restrictions were excluded. Recommendations and guidance documents not included or adopted by reference in an order are not included in these data. These data do not include mandatory business closures, curfews, or requirements/recommendations for people to stay in their homes. Due to limitations of the National Environmental Public Health Tracking Network Data Explorer, these data do not include tribes or cities, nor was a distinction made between county orders that applied county-wide versus those that were limited to unincorporated areas of the county. Effective and expiration dates were coded using only the date provided; no distinction was made based on the specific time of the day the order became effective or expired. These data do not necessarily represent an official position of the Centers for Disease Control and Prevention.
Facebook
TwitterThis map depicts existing and future land use conditions for Maricopa County, Arizona. The Existing Land Use data are derived from Maricopa County Assessor parcels, public land data from Arizona State Land Department, and numerous other sources.
Facebook
TwitterAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
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
Facebook
TwitterEagle Explorer C O Marinetrans Usa Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.
Facebook
TwitterFulmar Explorer Co Export Import Data. Follow the Eximpedia platform for HS code, importer-exporter records, and customs shipment details.
Facebook
TwitterSubscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.
Facebook
TwitterView details of Ford Explorer imports shipment data in January with price, HS codes, major Indian ports, countries, importers, buyers in India, quantity and more.
Facebook
TwitterMIT Licensehttps://opensource.org/licenses/MIT
License information was derived automatically
This map is used in the Heat and Health Explorer tool. It is primarily meant to be used in that application and filtered. It includes CAPA heat mapping along with several demographic and administrative layers to provide context as to who and what are in the warmest and coolest areas of King County.Questions? Contact Daaniya Iyaz, King County Heat Mitigation Strategy Specialist, at daiyaz@kingcounty.gov for more information.
Facebook
TwitterHalf-mile access sheds to open access open space in the conservation areas dataset built for CA Nature. Each has been intersected to a city and county dataset to allow summarization of demographics. These were then enriched using ESRI's geoenrichment services to provide select demographics. Three layers are included:1. Half-mile access sheds from open access areas considered 30x30 Conservation Areas (GAP Code 1 and 2)2. Half-mile access sheds from open access areas in the Conservation Areas dataset (GAP Codes 1, 2, 3, 4)3. All city and county areas to provide baseline demographics for comparison. Demographic variables include:PopulationAge DistributionEducational AttainmentHousing Unit OccupancyHispanic or Latino OriginRaceHousehold income