This link provides information and additional metadata related to the USGS National Seismic Hazard Maps. A direct shapefile download is available at https://www.sciencebase.gov/catalog/item/5db9be62e4b06957974eb5caBackground on Hazard Explorer Tool:The Hazard Explorer Tool is a web mapping application available in FEMA's Preparedness Toolkit that allows exercise planners to identify hazards that exist in their community, where their population is most vulnerable, and where their critical infrastructure/key resources are at risk.The Hazard Explorer Tool was developed under the National Exercise Program, which serves as the principal mechanism for examining the preparedness and readiness of the United States across the entire homeland security and management exercise. Communities design, coordinate, conduct, and evaluate exercises across the US as a part of their preparedness efforts.The Map Journal serves as a tool to help you identify and evaluate potential exercise scenario locations, hazard exposure, and other risk-related factors to support exercise planning. In this tool, you will identify:Which hazards exist near your location;Where your population is most vulnerable; andWhat infrastructure and resources would be most impacted in your selected scenario location.The final output of this tool is a basic PDF map of your selected scenario location, as well as links to data sources that you can share with your GIS staff to conduct more in-depth analysis for use in planning and conducting your exercise.For more information on the Hazard Explorer Tool, please visit: https://preptoolkit.fema.gov/web/hazard-explorer/hazard-explorer-tool

Use 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.

This web map references the live tiled map service from the OpenStreetMap 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 such as free satellite imagery, and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap server: http://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 and ArcGIS Explorer Online. 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.

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

California supports one of the greatest displays of biodiversity in the nation and the world. The challenge posed by the 30x30 initiative, is to plan and implement conservation strategies which allow all Californians to continue to flourish and succeed, while also ensuring that we safeguard the great abundance of species which reside in this state, and in many cases, exist nowhere else on Earth.

Maximizing the benefits of 30x30 for everyone requires, among many other factors, deliberate consideration of the landscape and the ways in which biodiversity is distributed within it. This Explorer introduces several types of biodiversity data for stakeholders to consider when engaged in conservation planning.

The Biodiversity Explorer includes dashboards for the Areas of Conservation Emphasis (ACE) and Habitat and Land Cover datasets. These allow deeper explorations of the state’s exceptional biodiversity and the current state of conservation by land cover.

The Areas of Conservation Emphasis (ACE) dashboard presents summaries of species data collected and analyzed by the California Department of Fish and Wildlife (CDFW) as part of its ongoing ACE project. ACE rolls multiple types of Species Richness into a Biodiversity Index, and also considers Connectivity, Climate Resilience, and Significant Habitats, all important factors to species and ecological health. The Habitat and Land Cover dashboard presents maps and summaries of land cover according to categories defined by the California Wildlife Habitat Relationship System (CWHR) maintained by CDFW. Conserving connected networks of all land cover types is key to conserving the species which depend upon them. The Habitat and Land Cover dashboard shows the percentage that each land cover type comprises within a county or ecoregion, and the degree to which it falls within already conserved areas.

Welcome to the Facility Explorer—a data warehouse of the Iowa Department of Natural Resources (DNR)—that brings together core environmental information in one place for easy access by DNR staff and the public.

Half-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

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).

Ground response--GIS data, June 2010. Downloadable GIS data includes: One ESRI ArcGIS 9.3 geodatabase, consisting of a set of 4 feature classes; Metadata for each feature class, in HTML format (for ease of reading outside of GIS software); One ArcGIS map document (ending in the .mxd extension), containing specifications for data presentation in ArcMap; One ArcGIS layer file for each feature class (ending in the .lyr extension), containing specifications for data presentation in the free ArcGIS Explorer (as well as ArcMap); README file

This guide will introduce the Climate Explorer and will familiarize you with key features and capabilities. The Climate Explorer provides three interactive viewers allowing users to explore predicted changes in temperature and precipitation, sea level rise and storm severity, and opportunities to implement nature-based solutions, which are actions that work with and enhance nature to help address societal challenges on California’s landscapes.

This directory contains Landsat 8 data from 2017 for two NEON sites: SJER and HARV:https://www.neonscience.org/field-sites/field-sites-map/SJERhttps://www.neonscience.org/field-sites/field-sites-map/HARVAll Landsat data files have been cropped to the boundaries of each NEON Field site. Data were downloaded from Earth Explorer by Earth Lab in Oct 2018.

Thinking Spatially Using GIS

Thinking Spatially Using GIS is a 1:1 set of instructional materials for students that use ArcGIS Online to teach basic geography concepts found in upper elementary school and above.
Each module has both a teacher and student file.

Ferdinand Magellan was the first European explorer to reach the Pacific Ocean by crossing the Atlantic Ocean when his expedition sailed through an opening, or strait, near the tip of South America in 1520. He named the ocean Mar Pacifico, which means peaceful sea. The strait, which connected the Atlantic and Pacific oceans, was later named for him.

At that point in his journey, Magellan and his fleet had been at sea for more than a year. He had lost two of his five ships. Now he would cross the Pacific Ocean with three ships, looking for the coast of Asia and the Spice Islands. However, he had no idea the Pacific Ocean would be so big!

The Thinking Spatially Using GIS home is at: http://esriurl.com/TSG

All Esri GeoInquiries can be found at http://www.esri.com/geoinquiries

Geographic Information System (GIS) analyses are an essential part of natural resource management and research. Calculating and summarizing data within intersecting GIS layers is common practice for analysts and researchers. However, the various tools and steps required to complete this process are slow and tedious, requiring many tools iterating over hundreds, or even thousands of datasets. USGS scientists will combine a series of ArcGIS geoprocessing capabilities with custom scripts to create tools that will calculate, summarize, and organize large amounts of data that can span many temporal and spatial scales with minimal user input. The tools work with polygons, lines, points, and rasters to calculate relevant summary data and combine them into a single output table that can be easily incorporated into statistical analyses. These tools are useful for anyone interested in using an automated script to quickly compile summary information within all areas of interest in a GIS dataset

This dataset contains the name and state FIPS code of all the states in the US.Use this spatial data to join data tables downloaded from the Arizona EPHT Explorer that has the "Geography" filter set to "States". 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

From the site: "This raster dataset has been created using the "Floodplains from the PA Explorer CD-ROM edition" for each county in the study area as originated by the Office of Remote Sensing for Earth Resources, Penn State University (see metadata entitled "Bucks FP.doc"). All areas designated in the shapefile were assigned a conservation value of 5. Conservation values were determined by experts gathered by Natural Lands Trust through SmartConservation®. This data set is one of several that have been combined to create an overall aquatic resources conservation value raster for the expanded piedmont ecoregion. Therefore the values were determined as a relative rank, comparable in value only to the other input aquatic resources data. Conservation value ranges from 1 - 10 with 10 being the highest value."

Fig 5: Administration data is used from Diva-GIS project (public domain) https://www.diva-gis.org/Data; Digital Elevation Model is used from USGS Earth Explorer (public domain) https://earthexplorer.usgs.gov. (RAR)

SONG, Carol X., Rosen Center for Advanced Computing, Purdue University, 155 South Grant Street, Young Hall, West Lafayette, IN 47907

Science gateways are becoming an integral component of modern collaborative research. They find widespread adoption by research groups to share data, code and tools both within a project and with the broader community. Sustainability beyond initial funding is a significant challenge for a science gateway to continue to operate, update and support the communities it serves. MyGeoHub.org is a geospatial science gateway powered by HUBzero. MyGeoHub employs a business model of hosting multiple research projects on a single HUBzero instance to manage the gateway operations more efficiently and sustainably while lowering the cost to individual projects. This model allows projects to share the gateway’s common capabilities and the underlying hardware and other connected computing resources, and continued maintenance of their sites even after the original funding has run out allowing time for acquiring new funding. MyGeoHub has hosted a number of projects, ranging from hydrologic modeling and data sharing, plant phenotyping, global and local sustainable development, climate variability impact on crops, and most recently, modeling of industry processes to improve reuse and recycling of materials. The shared need to manage, visualize and process geospatial data across the projects has motivated the Geospatial Data Building Blocks (GABBs) development funded by NSF DIBBs. GABBs provides a “File Explorer” type user interface for managing geospatial data (no coding is needed), a builder for visualizing and exploring geo-referenced data without coding, a Python map library and other toolkits for building geospatial analysis and computational tools without requiring GIS programming expertise. GABBs can be added to an existing or new HUBzero site, as is the case on MyGeoHub. Teams use MyGeoHub to coordinate project activities, share files and information, publish tools and datasets (with DOI) to provide not only easy access but also improved reuse and reproducibility of data and code as the interactive online tools and workflows can be used without downloading or installing software. Tools on MyGeoHub have also been used in courses, training workshops and summer camps. MyGeoHub is supporting more than 8000 users annually.

COTREX Trails and Trailheads Added in February 2019, the Colorado Trail System, now titled the Colorado Trail Explorer (COTREX), endeavors to map every trail in the state of Colorado. Currently there are nearly 40,000 miles of trails mapped. Trails come from a variety of sources (USFS, BLM, local parks & recreation departments, local governments) and are compiled by CPW contractor Natural Atlas. Responsibility for accuracy of the data rests with the source.

CPW Trail Segments Recognizing that an all-inclusive, spatially-aware model of trails Colorado State Park is a useful management tool and a valuable public resource this geodatabase is designed to accomplish three objectives. 1. Inventorying all designated trails Colorado Parks & Wildlife maintain in Colorado State associate each trail segment with 38 applicable attributes. (length, width, surface, difficulty, etc.)

1. Determine and track if the following 11 uses are permitted on each trail segment: 1:Hiking, 2:Biking, 3: Equestrian 4:Pets, 5:Snowshoeing. 6: Cross Country Skiing, 7: Snowmobiling, 8: Grooming, 9: OHV 10: Other Power Driven Mobility Devices (OPDMD), 11:Wheelchair friendliness (Not ADA accessibility)

2. Model Colorado State Park Trail system in a spatially aware three dimensional space and associate each trail segment to 38 attributes that can be used to producing a set of standardized trail maps for public and internal use.

The Colorado Trail System, now titled the Colorado Trail Explorer (COTREX), endeavors to map every trail in the state of Colorado. Currently their are nearly 40,000 miles of trails mapped. Trails come from a variety of sources (USFS, BLM, local parks & recreation departments, local governments). Responsibility for accuracy of the data rests with the source.These data were last updated on 2/5/2019

Downloadable Zip File (GIS Data 444K). Link Function: 375-- download.