This layer shows census tracts that meet the following definitions: Census tracts with median household incomes at or below 80 percent of the statewide median income or with median household incomes at or below the threshold designated as low income by the Department of Housing and Community Development’s list of state income limits adopted under Healthy and Safety Code section 50093 and/or Census tracts receiving the highest 25 percent of overall scores in CalEnviroScreen 4.0 or Census tracts lacking overall scores in CalEnviroScreen 4.0 due to data gaps, but receiving the highest 5 percent of CalEnviroScreen 4.0 cumulative population burden scores or Census tracts identified in the 2017 DAC designation as disadvantaged, regardless of their scores in CalEnviroScreen 4.0 or Lands under the control of federally recognized Tribes.Data downloaded in May 2022 from https://webmaps.arb.ca.gov/PriorityPopulations/.

1. Zip code boundaries change, in ways small and large - these are not a stable analysis unit. Data you received keyed to zip codes may have used an earlier and very different boundary for your zip codes of interest.
2. Historically, the United States Postal Service has not published zip code boundaries, and instead, boundary datasets are compiled by third party vendors from address data. That means that the boundary data are not authoritative, and any data you have keyed to zip codes may use a different, vendor-specific method for generating boundaries from the data here.
3. Zip codes are designed to optimize mail delivery, not social, environmental, or demographic characteristics. Analysis using zip codes is subject to create issues with the Modifiable Areal Unit Problem that will bias any results because your units of analysis aren't designed for the data being studied.

Counties in California intended for the NEVI Map.Data downloaded in May 2021 from https://www.census.gov/geographies/mapping-files/time-series/geo/tiger-line-file.2021.html#list-tab-VGDZBC72KXZ7CWIQNY.

Use Constraints:This mapping tool is for reference and guidance purposes only and is not a binding legal document to be used for legal determinations. The data provided may contain errors, inconsistencies, or may not in all cases appropriately represent the current boundaries of PWSs in California. The data in this map are subject to change at any time and should not be used as the sole source for decision making. By using this data, the user acknowledges all limitations of the data and agrees to accept all errors stemming from its use.Description:This mapping tool provides a representation of the general PWS boundaries for water service, wholesaler and jurisdictional areas. The boundaries were created originally by collection via crowd sourcing by CDPH through the Boundary Layer Tool, this tool was retired as of June 30, 2020. State Water Resources Control Board – Division of Drinking Water is currently in the process of verifying the accuracy of these boundaries and working on a tool for maintaining the current boundaries and collecting boundaries for PWS that were not in the original dataset. Currently, the boundaries are in most cases have not been verified. Map Layers· Drinking Water System Areas – representation of the general water system boundaries maintained by the State Water Board. This layer contains polygons with associated data on the water system and boundary the shape represents.· LPA office locations – represents the locations of the Local Primacy Agency overseeing the water system in that county. Address and contact information are attributes of this dataset.· LPA office locations – represents the locations of the Local Primacy Agency overseeing the water system in that county. Address and contact information are attributes of this dataset· California Senate Districts – represents the boundaries of the senate districts in California included as a reference layer in order to perform analysis with the Drinking Water System Boundaries layers.· California Senate Districts – represents the boundaries of the assembly districts in California included as a reference layer in order to perform analysis with the Drinking Water System Boundaries layers.· California County – represents the boundaries of the counties in California included as a reference layer in order to perform analysis with the Drinking Water System Boundaries layers.Informational Pop-up Box for Boundary layer· Water System No. – unique identifier for each water system· Water System Name – name of water system· Regulating Agency – agency overseeing the water system· System Type – classification of water system.· Population the approximate population served by the water system· Boundary Type – the type of water system boundary being displayed· Address Line 1 – the street or mailing address on file for the water system· Address Line 2 – additional line for street or mailing address on file for the water system, if applicable· City – city where water system located or receives mail· County – county where water system is located· Verification Status – the verification status of the water system boundary· Verified by – if the boundary is verified, the person responsible for the verification Date Created and Sources:This web app was most recently updated on July, 21, 2021. Each layer has a data created date and data source is indicated in the overview/metadata page and is valid up to the date provided.

Link to landing page referenced by identifier. Service Protocol: Link to landing page referenced by identifier. Link Function: information-- dc:identifier.

For the past several censuses, the Census Bureau has invited people to self-respond before following up in-person using census takers. The 2010 Census invited people to self-respond predominately by returning paper questionnaires in the mail. The 2020 Census allows people to self-respond in three ways: online, by phone, or by mail. The 2020 Census self-response rates are self-response rates for current census geographies. These rates are the daily and cumulative self-response rates for all housing units that received invitations to self-respond to the 2020 Census. The 2020 Census self-response rates are available for states, counties, census tracts, congressional districts, towns and townships, consolidated cities, incorporated places, tribal areas, and tribal census tracts. The Self-Response Rate of Los Angeles County is 65.1% for 2020 Census, which is slightly lower than 69.6% of California State rate. More information about these data are available in the Self-Response Rates Map Data and Technical Documentation document associated with the 2020 Self-Response Rates Map or review our FAQs. Animated Self-Response Rate 2010 vs 2020 is available at ESRI site SRR Animated Maps and can explore Census 2020 SRR data at ESRI Demographic site Census 2020 SSR Data. Following Demographic Characteristics are included in this data and web maps to visualize their relationships with Census Self-Response Rate (SRR)..1. Population Density2. Poverty Rate3. Median Household income4. Education Attainment5. English Speaking Ability6. Household without Internet Access7. Non-Hispanic White Population8. Non-Hispanic African-American Population9. Non-Hispanic Asian Population10. Hispanic Population

Web map containing various layers to be used as reference in Experience Builder. It will serve as a one-stop tool for waste hauler contractors working with Los Angeles County Department of Public Works, Environmental Programs Division, to identify customers that are eligible for fee waivers due to their property falling within areas deemed to be too low in population or too high in elevation; these are conditions used to identify areas that may be too prohibitively costly to provide organics recovery programs due to them being in rural or remote areas.The Experience Builder page, https://experience.arcgis.com/experience/df8689f7d5964f48a5390f6f937533d2 (that references this web map), was created to cross-reference qualifying low-population/high elevation census tracts with various residential franchise, garbage disposal district, and commercial franchise waste collection service areas in Los Angeles County and to assist haulers in providing Public Works with the number of waste generators that are located on each census tract. This information will assist Public Works with applying for SB1383 low population and/or high elevation waivers for these census tracts. More information regarding SB1383 can be found at California Legislative Information (https://leginfo.legislature.ca.gov/faces/billNavClient.xhtml?bill_id=201520160SB1383)For inquiries about how SB 1383 impacts Los Angeles County, please contact Kawsar Vazifdar, (626) 458-3514.

US Census American Community Survey (ACS) 2021, 5-year estimates of the key demographic characteristics of Census Tracts geographic level in Orange County, California. The data contains 105 fields for the variable groups D01: Sex and age (universe: total population, table X1, 49 fields); D02: Median age by sex and race (universe: total population, table X1, 12 fields); D03: Race (universe: total population, table X2, 8 fields); D04: Race alone or in combination with one or more other races (universe: total population, table X2, 7 fields); D05: Hispanic or Latino and race (universe: total population, table X3, 21 fields), and; D06: Citizen voting age population (universe: citizen, 18 and over, table X5, 8 fields). The US Census geodemographic data are based on the 2021 TigerLines across multiple geographies. The spatial geographies were merged with ACS data tables. See full documentation at the OCACS project GitHub page (https://github.com/ktalexan/OCACS-Geodemographics).

Population estimates for Grey County and it's lower tier municipalities between 2011 and 2041. Data is broken up by municipality, year, gender, and age. This data reflects estimates of population and may contain errors. Please contact Grey County Planning for more information.Take census data and enrich a dataset. Used to make the predictions for later years like 2041, most of the non-census data was provided (via AGOL enrichment) from Environics. https://doc.arcgis.com/en/esri-demographics/latest/regional-data/canada.htm

The site suitability criteria included in the techno-economic land use screens are listed below. As this list is an update to previous cycles, tribal lands, prime farmland, and flood zones are not included as they are not technically infeasible for development. The techno-economic site suitability exclusion thresholds are presented in table 1. Distances indicate the minimum distance from each feature for commercial scale wind developmentAttributes: Steeply sloped areas: change in vertical elevation compared to horizontal distancePopulation density: the number of people living in a 1 km2 area Urban areas: defined by the U.S. Census. Water bodies: defined by the U.S. National Atlas Water Feature Areas, available from Argonne National Lab Energy Zone Mapping Tool Railways: a comprehensive database of North America's railway system from the Federal Railroad Administration (FRA), available from Argonne National Lab Energy Zone Mapping Tool Major highways: available from ESRI Living Atlas Airports: The Airports dataset including other aviation facilities as of July 13, 2018 is part of the U.S. Department of Transportation (USDOT)/Bureau of Transportation Statistics's (BTS's) National Transportation Atlas Database (NTAD). The Airports database is a geographic point database of aircraft landing facilities in the United States and U.S. Territories. Attribute data is provided on the physical and operational characteristics of the landing facility, current usage including enplanements and aircraft operations, congestion levels and usage categories. This geospatial data is derived from the FAA's National Airspace System Resource Aeronautical Data Product. Available from Argonne National Lab Energy Zone Mapping Tool Active mines: Active Mines and Mineral Processing Plants in the United States in 2003Military Lands: Land owned by the federal government that is part of a US military base, camp, post, station, yard, center, or installation. Table 1 Wind Steeply sloped areas >10o Population density >100/km2 Capacity factor <20% Urban areas <1000 m Water bodies <250 m Railways <250 m Major highways <125 m Airports <5000 m Active mines <1000 m Military Lands <3000m For more information about the processes and sources used to develop the screening criteria see sources 1-7 in the footnotes. Data updates occur as needed, corresponding to typical 3-year CPUC IRP planning cyclesFootnotes:[1] Lopez, A. et. al. “U.S. Renewable Energy Technical Potentials: A GIS-Based Analysis,” 2012. https://www.nrel.gov/docs/fy12osti/51946.pdf[2] https://greeningthegrid.org/Renewable-Energy-Zones-Toolkit/topics/social-environmental-and-other-impacts#ReadingListAndCaseStudies[3] Multi-Criteria Analysis for Renewable Energy (MapRE), University of California Santa Barbara. https://mapre.es.ucsb.edu/[4] Larson, E. et. al. “Net-Zero America: Potential Pathways, Infrastructure, and Impacts, Interim Report.” Princeton University, 2020. https://environmenthalfcentury.princeton.edu/sites/g/files/toruqf331/files/2020-12/Princeton_NZA_Interim_Report_15_Dec_2020_FINAL.pdf.[5] Wu, G. et. al. “Low-Impact Land Use Pathways to Deep Decarbonization of Electricity.” Environmental Research Letters 15, no. 7 (July 10, 2020). https://doi.org/10.1088/1748-9326/ab87d1.[6] RETI Coordinating Committee, RETI Stakeholder Steering Committee. “Renewable Energy Transmission Initiative Phase 1B Final Report.” California Energy Commission, January 2009.[7] Pletka, Ryan, and Joshua Finn. “Western Renewable Energy Zones, Phase 1: QRA Identification Technical Report.” Black & Veatch and National Renewable Energy Laboratory, 2009. https://www.nrel.gov/docs/fy10osti/46877.pdf.[8]https://www.census.gov/cgi-bin/geo/shapefiles/index.php?year=2019&layergroup=Urban+Areas[9]https://ezmt.anl.gov/[10]https://www.arcgis.com/home/item.html?id=fc870766a3994111bce4a083413988e4[11]https://mrdata.usgs.gov/mineplant/Credits Title: Techno-economic screening criteria for utility-scale wind energy installations for Integrated Resource Planning Purpose for creation: These site suitability criteria are for use in electric system planning, capacity expansion modeling, and integrated resource planning. Keywords: wind energy, resource potential, techno-economic, IRP Extent: western states of the contiguous U.S. Use Limitations The geospatial data created by the use of these techno-economic screens inform high-level estimates of technical renewable resource potential for electric system planning and should not be used, on their own, to guide siting of generation projects nor assess project-level impacts.Confidentiality: Public ContactEmily Leslie Emily@MontaraMtEnergy.comSam Schreiber sam.schreiber@ethree.com Jared Ferguson Jared.Ferguson@cpuc.ca.govOluwafemi Sawyerr femi@ethree.com

The Census Designated Places 2020 (CDP 2020) boundary usually is defined by the Census Bureau in cooperation with state, local or tribal officials. The boundaries are updated prior to each decennial census. These boundaries, which usually coincide with visible features or the boundary of an adjacent incorporated place or another legal entity boundary, have no legal status, nor do these places have officials elected to serve traditional municipal functions. CDP boundaries may change from one decennial census to the next with changes in the settlement pattern; a CDP with the same name as in an earlier census does not necessarily have the same boundary. CDPs must be contained within a single state and may not extend into an incorporated place. There are no population size requirements for CDPs. incorporatedCDP data is download from Census Bureau's TIGER 2020 website (https://www2.census.gov/geo/tiger/TIGER2020/PLACE/) and extracted for Los Angeles County. This data includes LA County 88 incorporated cities and 54 CDPs.

CAL FIRE has a legal responsibility to provide fire protection on all State Responsibility Area (SRA) lands, which are defined based on land ownership, population density and land use. For example, CAL FIRE does not have responsibility for densely populated areas, incorporated cities, agricultural lands, or lands administered by the federal government. The SRA dataset provides areas of legal responsibility for fire protection, including State Responsibility Areas (SRA), Federal Responsibility Areas (FRA), and Local Responsibility Areas (LRA). SRA designations undergo a thorough 5 year review cycle, as well as annual updates for incorporations/annexations, error fixes, and ownership changes (automatic changes that do not require Board of Forestry approval). This service represents the latest official version, and is updated when new versions are released. As of November 15th, 2024, this represents SRA 25_1. Changes from SRA24_1 include those resulting from acquisitions and disposals of federal lands transmitted through the yearly California Wildfire Coordinating Group (CWCG) Direct Protection Area (DPA) agreement process, from city annexations and de-annexations, from changes in county parcel boundaries, as well as corrections to any data errors discovered during the editing process.

Human population density in 2000, by terrestrial ecoregion.

We summarized human population density by ecoregion using the Gridded Population of the World database and projections for 2015 (CIESIN et al. 2005). The mean for each ecoregion was extracted using a zonal statistics algorithm.

These data were derived by The Nature Conservancy, and were displayed in a map published in The Atlas of Global Conservation (Hoekstra et al., University of California Press, 2010). More information at http://nature.org/atlas.

Data derived from:

Center for International Earth Science Information Network (CIESIN), Columbia University; and Centro Internacional de Agricultura Tropical (CIAT). 2005. Gridded Population of the World Version 3 (GPWv3). Socioeconomic Data and Applications Center (SEDAC), Columbia University Palisades, New York. Available at http://sedac.ciesin.columbia.edu/gpw. Digital media.

United Nations Population Division (UNPD). 2007. Global population, largest urban agglomerations and cities of largest change. World Urbanization Prospects: The 2007 Revision Population Database. Available at http://esa.un.org/unup/index.asp.

For more about The Atlas of Global Conservation check out the web map (which includes links to download spatial data and view metadata) at http://maps.tnc.org/globalmaps.html. You can also read more detail about the Atlas at http://www.nature.org/science-in-action/leading-with-science/conservation-atlas.xml, or buy the book at http://www.ucpress.edu/book.php?isbn=9780520262560

This layer features tropical storm (hurricanes, typhoons, cyclones) tracks, positions, and observed wind swaths from the past hurricane season for the Atlantic, Pacific, and Indian Basins. These are products from the National Hurricane Center (NHC) and Joint Typhoon Warning Center (JTWC). They are part of an archive of tropical storm data maintained in the International Best Track Archive for Climate Stewardship (IBTrACS) database by the NOAA National Centers for Environmental Information.Data SourceNOAA National Hurricane Center tropical cyclone best track archive.Update FrequencyWe automatically check these products for updates every 15 minutes from the NHC GIS Data page.The NHC shapefiles are parsed using the Aggregated Live Feeds methodology to take the returned information and serve the data through ArcGIS Server as a map service.Area CoveredWorldWhat can you do with this layer?Customize the display of each attribute by using the ‘Change Style’ option for any layer.Run a filter to query the layer and display only specific types of storms or areas.Add to your map with other weather data layers to provide insight on hazardous weather events.Use ArcGIS Online analysis tools like ‘Enrich Data’ on the Observed Wind Swath layer to determine the impact of cyclone events on populations.Visualize data in ArcGIS Insights or Operations Dashboards.This map is provided for informational purposes and is not monitored 24/7 for accuracy and currency. Always refer to NOAA or JTWC sources for official guidance.If you would like to be alerted to potential issues or simply see when this Service will update next, please visit our Live Feed Status Page!

This map shows the count (shown with size) and percent (shown with color) of people age 65 and over - often referred to as seniors. Many service-providing organizations such as Meals on Wheels and AARP have specific outreach to the senior population. Also, seniors are often more vulnerable than the general population during disasters and crisis situations. Knowing where seniors reside, and how concentrated they are, can help inform the allocation of resources. This map is multi-scale, with data for counties and tracts. This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.

This is the last boundary change until the next redistricting following the 2030 Census. All of the districts now reflect the 2021 Citizens Redistricting Commission(CRC) plan. The only thing that will change is the members' names and parties as elections are held, appointments are made, or party affiliations change.