esri Australia is a Proprietary Company that generates the majority of its income from the Computer System Design Services industry.

This layer shows median household income by race and by age of householder. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Median income and income source is based on income in past 12 months of survey. This layer is symbolized to show median household income. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B19013B, B19013C, B19013D, B19013E, B19013F, B19013G, B19013H, B19013I, B19049, B19053Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

All adopted revenue budgets from FY2012 through the latest, most current FY. Started in FY2017, this was implemented to conserve space and to ensure that the data is presented in a consistent manner.

Global Energy Storage for Renewable Energy Grid Integration - ESRI market size 2025 is $12984.1 Million whereas according out published study it will reach to $24693.8 Million by 2033. Energy Storage for Renewable Energy Grid Integration - ESRI market will be growing at a CAGR of 8.367% during 2025 to 2033.

This is a single data set from a larger study. The full study is titled "Socio-Economic Impact of Outer Continental Shelf Wind Energy Development on Fishing in the U.S. Atlantic". Each quarter square km (500 m) cell has been summed for the mean correlated economic value over the six year period analyzed (2007-2012). This information was created for each state, gear type, Fishery Management Plan (FMP), top 30 exposed ports and top 30 exposed species. This was calculated using Vessel Trip Reports (VTR), Cumulative Distribution Function (CDF) which estimates radial distance within which fishing activity is likely to occur, and a 500 m raster cell output. The raster data shown here is a summation of all the state revenues by all gear types and all species. The mean annual revenue value for all years is represented for the entire area. The data is classified in the legend first by using a Natural Breaks algorithm for 8 classes, and then by reclassifying those results to the closest 50, 100, or 1000 interval. The value is in US dollars for 2012 representing the sum of the mean values for all six years, and then classified into one of the 8 classes. You may still hover over the raster value in ArcGIS if map tips are turned on, to get the value of each cell.

© NOAA Fisheries Social Sciences Branch & Bureau of Ocean Energy Management This layer is a component of BOEM Layers.

MarineCadastre.gov map service hosted for BOEM. Layers in this service are temporarily being hosted in for BOEM until the layers are hosted through their server found here: http://gis.boemre.gov/arcgis/rest/services/BOEM_BSEE/MMC_Layers/MapServer/ or within the National Geoplatform. Please refer to the services links found in MarineCadastre.gov Data Registry for the most recent web service links for the layers found within this service. This map service presents spatial information for Coastal and Marine Spatial Planning. The service is maintained by National Oceanic and Atmospheric Administration (NOAA) Office for Coastal Management (OCM), in partnership with Department of the Interior (DOI) Bureau of Ocean Energy Management (BOEM). More information about this product can be found at www.MarineCadastre.gov. This map service presents spatial information about MarineCadastre.gov services across the United States and Territories in the Web Mercator projection. The service was developed by the National Oceanic and Atmospheric Administration (NOAA), but may contain data and information from a variety of data sources, including non-NOAA data. NOAA provides the information “as-is” and shall incur no responsibility or liability as to the completeness or accuracy of this information. NOAA assumes no responsibility arising from the use of this information. The NOAA Office for Coastal Management will make every effort to provide continual access to this service but it may need to be taken down during routine IT maintenance or in case of an emergency. If you plan to ingest this service into your own application and would like to be informed about planned and unplanned service outages or changes to existing services, please register for our Data Services Newsletter (http://coast.noaa.gov/digitalcoast/publications/subscribe). For additional information, please contact the NOAA Office for Coastal Management (coastal.info@noaa.gov).

© Bureau of Ocean Energy Management (BOEM), MarineCadastre.gov

The Industrial Revenue Bond program (IRB) provides access to tax-exempt financing to help businesses and non-profit organizations renovate and build new construction, make tenant improvements, and purchase capital by securing interest rates up 4% lower than a traditional commercial loan. IRBs can be used to finance, refinance, and reimburse the costs of acquiring, constructing, restoring, rehabilitating, expanding, improving, equipping, or furnishing real property and related subordinate facilities. More than $9.5 billion has been issued through Washington, DC's IRB program since 1994.

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

This layer shows income data in Tucson by neighborhood, aggregated from block level data, between 2010-2019. For questions, contact GIS_IT@tucsonaz.gov. The data shown is from Esri's 2019 Updated Demographic estimates.Esri's U.S. Updated Demographic (2019/2024) Data - Population, age, income, sex, race, home value, and marital status are among the variables included in the database. Each year, Esri's Data Development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of U.S. geographies.Additional Esri Resources:Esri DemographicsU.S. 2019/2024 Esri Updated DemographicsEssential demographic vocabularyPermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

This web map shows the locations and details of Inland Revenue Department's offices in Hong Kong. It is a set of data made available by the Inland Revenue Department under the Government of Hong Kong Special Administrative Region (the "Government") at https://portal.csdi.gov.hk ("Hong Kong CSDI Portal"). The source data has been processed and converted into Esri File Geodatabase format and uploaded to Esri's ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of Hong Kong CSDI Portal at https://portal.csdi.gov.hk .

The District of Columbia Revenue Bond Program provides market interest rate loans to help lower cost of funds available for capital projects. These bonds are used to finance a wide variety of projects including industrial and commercial development.

This layer shows median household income by race and by age of householder. This is shown by tract, county, and state centroids. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Median income and income source is based on income in past 12 months of survey. This layer is symbolized to show median household income. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B19013B, B19013C, B19013D, B19013E, B19013F, B19013G, B19013H, B19013I, B19049, B19053Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

This map shows households that spend 30 percent or more of their income on housing, a threshold widely used by many affordable housing advocates and official government sources including Housing and Urban Development. Census asks about income and housing costs to understand whether housing is affordable in local communities. When housing is not sufficient or not affordable, income data helps communities: Enroll eligible households in programs designed to assist them.Qualify for grants from the Community Development Block Grant (CDBG), HOME Investment Partnership Program, Emergency Solutions Grants (ESG), Housing Opportunities for Persons with AIDS (HOPWA), and other programs.When rental housing is not affordable, the Department of Housing and Urban Development (HUD) uses rent data to determine the amount of tenant subsidies in housing assistance programs.Map opens in Atlanta. Use the bookmarks or search bar to view other cities. Data is symbolized to show the relationship between burdensome housing costs for owner households with a mortgage and renter households: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 web map shows the Working population income distribution in 2006 within the 18 districts of Hong Kong. It is a subset of the census data 2006 made available by the Census and Statistics Department under the Government of Hong Kong Special Administrative Region (the “Government”) at https://DATA.GOV.HK/ (“DATA.GOV.HK”). The source data is in XLS format and has been processed and converted into Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of DATA.GOV.HK at https://data.gov.hk.

This web map shows the Working population income distribution in 2001 within the 18 districts of Hong Kong. It is a subset of the census data 2001 made available by the Census and Statistics Department under the Government of Hong Kong Special Administrative Region (the “Government”) at https://DATA.GOV.HK/ (“DATA.GOV.HK”). The source data is in CSV format and has been processed and converted into Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of Data.gov.hk at https://data.gov.hk.

This layer shows the Hong Kong Population Distribution by Economically active domestic households by monthly domestic household income (HK$) by Large Tertiary Planning Unit Group in 2021. It is a subset of the 2021 Population Census made available by the Census and Statistics Department under the Government of Hong Kong Special Administrative Region (the "Government") at https://portal.csdi.gov.hk ("CSDI Portal"). The source data is in CSV format and has been processed and converted into Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort.For details about the data, source format and terms of conditions of usage, please refer to the website of CSDI Portal at https://portal.csdi.gov.hk.

Tracking local taxes and intergovernmental revenue and evaluating the credibility of revenue forecasts assists greatly with sound financial planning efforts; it allows policy makers the ability to make informed decisions, build a fiscally responsible budget, and support the City's priority to maintain financial stability and vitality.This page provides data for the Revenue Forecast performance measure.The performance measure dashboard is available at 5.10 Revenue Forecast Variance.Additional InformationSource: PeopleSoft 400 Report, ExcelContact: Benicia BensonContact E-Mail: Benicia_Benson@tempe.govData Source Type: TabularPreparation Method: Metrics are based on actual revenue collected for local taxes and intergovernmental revenue in the City's PeopleSoff 400 Report. Total Local Taxes include city sales tax, sales tax rebate, sales tax penalty and interest, sales tax to be rebated, temporary PLT tax, sales tax interest, refund and temporary PLT tax to be rebated. Total intergovernmental revenue includes State Sales Tax, State Income Tax, and State Auto Lieu Tax. Many of the estimates are provided by the League of Arizona Cities and Towns. Another principal sources includes our participation as a sponsor of the Forecasting Project developed by the University of Arizona Eller College of Economic and Business Research Center in Tucson, AZ.Publish Frequency: Annually based on a fiscal yearPublish Method: Manually retrieved and calculatedData Dictionary

This layer shows median earnings by occupational group. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. Only full-time year-round workers included. Median earnings is based on earnings in past 12 months of survey. Occupation Groups based on Bureau of Labor Statistics (BLS)' Standard Occupation Classification (SOC). This layer is symbolized to show median earnings of the full-time, year-round civilian employed population. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B24021Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

City of Topeka Revenue Budget

Important Note: This item is in mature support as of June 2023 and will be retired in December 2025. This map shows per capita income (income per person) in the U.S. in 2022 in a multiscale map by country, state, county, ZIP Code, tract, and block group. ArcGIS Online subscription required. Per capita income is calculated by taking the sum of all incomes and dividing by the total population.The pop-up is configured to include the following information for each geography level:2022 Per capita incomeTotal population2027 projected per capita incomePermitted use of this data is covered in the DATA section of the Esri Master Agreement (E204CW) and these supplemental terms.

Federal Way's revenue development area boundary.To participate in the LIFT program, local jurisdictions establish a revenue development area (RDA) and apply to the Community Economic Revitalization Board (CERB) for approval. There are currently nine LIFT projects around the state; the program is closed to further projects unless the Legislature increases the total amount of funding available for state contributions. The amount of state contribution each project receives per year is limited to the lowest amount of the following four caps: 1) One million dollars; 2) The amount of local revenue dedicated to the project; 3) The amount awarded to the project by CERB; or 4) The “state benefit” amount. The “state benefit” amount is based on a complicated statutory formula intended to approximate increases to state property and excise tax revenues within the RDA. Statute directs each local jurisdiction to submit an annual report to CERB and the Department of Revenue (DOR) that contains the information necessary to calculate the state contribution, as well as information about the progress of its LIFT project.