*If content does not automatically open in a new tab, click the Open button to the right.OnTheMap for Emergency Management is a public data tool from the U.S. Census Bureau that provides an intuitive web-based interface for accessing U.S. population and workforce statistics, in real time, for areas being affected by natural disasters. The tool allows users to retrieve reports containing detailed workforce, population, and housing characteristics for hurricanes, floods, wildfires, winter storms, and federal disaster declaration areas.To provide users this information for rapidly changing hazard event areas, OnTheMap for Emergency Management automatically incorporates real time data updates from the National Weather Service’s (NWS) National Hurricane Center, Department of Interior (DOI), Department of Agriculture (DOA), and the Federal Emergency Management Agency (FEMA).Highlights: Detailed social, economic, and housing data from the American Community Survey (ACS) Generate reports for specific communities for regional, local, and comparative analysesBar charts and an intuitive dashboard interfaceEvent search tool for easy access to current and historical emergency eventsLinkable maps and reports for easy sharing of maps and reports For more information and documentation, please see this page on the Census Bureau website.

Source: U.S. Census Bureau; Longitudinal Employer-Household Dynamics; "Job Counts by Counties Where Workers are Employed - Primary Jobs" 2022; OnTheMap; http://onthemap.ces.census.gov; generated by CCRPC staff; (6 February 2025).

Abstract

Published by the US Census Department, the LODES dataset aggregates data about where people live and work in the United States. This data is for New York State.

Documentation

The Longitudinal Employer-Household Dynamics (LEHD) program is part of the Center for Economic Studies at the U.S. Census Bureau. The LEHD program produces new, cost effective, public-use information combining federal, state and Census Bureau data on employers and employees under the Local Employment Dynamics (LED) Partnership. State and local authorities increasingly need detailed local information about their economies to make informed decisions. The LED Partnership works to fill critical data gaps and provide indicators needed by state and local authorities.

LEHD Origin-Destination Employment Statistics (LODES) used by OnTheMap are available for download below. Version 7 of LODES was enumerated by 2010 census blocks. Previous versions of LODES were enumerated with 2000 census blocks.

Data are state-based and organized into three types: Origin-Destination (OD), Residence Area Characteristics (RAC), and Workplace Area Characteristics (WAC), all at census block geographic detail. Data is available for most states for the years 2002–2018.

This raster analysis is based on 2015 LEHD data by location of the worker's home for all jobs. This raster layer is a point density analysis of the density of homes of workers 55 or older. The cell size is set at 200 feet; the radius is set at ¾ mile.

Learn more about the LEHD data at the Census' website.

U.S. Census Bureau. (2017). LEHD Origin-Destination Employment Statistics (2015) [computer file]. Washington, DC: U.S. Census Bureau, Longitudinal-Employer Household Dynamics Program [distributor], at https://onthemap.ces.census.gov. LODES 7.3 [version]

2015 LEHD county attributes for the Workforce Profile.Learn more about the LEHD data at the Census' website.

U.S. Census Bureau. (2017). LEHD Origin-Destination Employment Statistics (2015) [computer file]. Washington, DC: U.S. Census Bureau, Longitudinal-Employer Household Dynamics Program [distributor], at https://onthemap.ces.census.gov. LODES 7.3 [version]

description: The OnTheMap application provides detailed spatial distributions of workers' employment and residential locations and the relation between the two at the Census Block level. OnTheMap also provides characteristic detail on age, earnings, industry distributions, and local workforce indicators.; abstract: The OnTheMap application provides detailed spatial distributions of workers' employment and residential locations and the relation between the two at the Census Block level. OnTheMap also provides characteristic detail on age, earnings, industry distributions, and local workforce indicators.

This raster analysis is based on 2015 LEHD data by workplace for all jobs. This raster layer is a point density analysis of the workplace density of workers aged 30 to 54. The cell size is set at 200 feet; the radius is set at ¾ mile.

Learn more about the LEHD data at the Census' website.

U.S. Census Bureau. (2017). LEHD Origin-Destination Employment Statistics (2015) [computer file]. Washington, DC: U.S. Census Bureau, Longitudinal-Employer Household Dynamics Program [distributor], at https://onthemap.ces.census.gov. LODES 7.3 [version]

LEHD Origin-Destination Employment Statistics (LODES) used by OnTheMap are available for download below. Version 7 of LODES was enumerated by 2010 census blocks. Previous versions of LODES were enumerated with 2000 census blocks. Data files are state-based and organized into three types: Origin-Destination (OD), Residence Area Characteristics (RAC), and Workplace Area Characteristics (WAC), all at census block geographic detail. Data is available for most states for the years 2002–2013. To browse the LODES data files in their directory structure or to access them with a FTP program (must be able to access HTTP), go to http://lehd.ces.census.gov/data/lodes/.

Check out the data dictionary at http://celebratingcities.github.io/docs.html

This raster analysis is based on 2015 LEHD data by location of the worker's home for all jobs. This raster layer is a point density analysis of the density of homes of workers with yearly earnings of $15,000 or less. The cell size is set at 200 feet; the radius is set at 1 mile.

Learn more about the LEHD data at the Census' website.

U.S. Census Bureau. (2017). LEHD Origin-Destination Employment Statistics (2015) [computer file]. Washington, DC: U.S. Census Bureau, Longitudinal-Employer Household Dynamics Program [distributor], at https://onthemap.ces.census.gov. LODES 7.3 [version]

This archive contains supplementary materials for the published manuscript.

We report results from the first comprehensive total quality evaluation of five major indicators in the U.S. Census Bureau's Longitudinal Employer-Household Dynamics (LEHD) Program Quarterly Workforce Indicators (QWI): total flow-employment, beginning-of-quarter employment, full-quarter employment, average monthly earnings of full-quarter employees, and total quarterly payroll. Beginning-of-quarter employment is also the main tabulation variable in the LEHD Origin-Destination Employment Statistics (LODES) workplace reports as displayed in OnTheMap (OTM), including OnTheMap for Emergency Management. We account for errors due to coverage; record-level non-response; edit and imputation of item missing data; and statistical disclosure limitation. The analysis reveals that the five publication variables under study are estimated very accurately for tabulations involving at least 10 jobs. Tabulations involving three to nine jobs are a transition zone, where cells may be fit for use with caution. Tabulations involving one or two jobs, which are generally suppressed on fitness-for-use criteria in the QWI and synthesized in LODES, have substantial total variability but can still be used to estimate statistics for untabulated aggregates as long as the job count in the aggregate is more than 10.

LEHD Origin-Destination Employment Statistics (LODES) used by OnTheMap are available for download below. Version 7 of LODES was enumerated by 2010 census blocks. Previous versions of LODES were enumerated with 2000 census blocks. Data files are state-based and organized into three types: Origin-Destination (OD), Residence Area Characteristics (RAC), and Workplace Area Characteristics (WAC), all at census block geographic detail. Data is available for most states for the years 2002–2013. To browse the LODES data files in their directory structure or to access them with a FTP program (must be able to access HTTP), go to http://lehd.ces.census.gov/data/lodes/.

Check out the data dictionary at http://celebratingcities.github.io/docs.html

Baseline Data: 2014 U.S. Census Bureau's OnTheMap; jobs by census block assigned to TAZ geographies in GIS.2040 Forecast: Maine Center for Business and Economic Research using the REMI model.Disaggregating to Smaller GeographiesMunicipal Geography: The 2040 county employment total is apportioned to each municipality based on that municipality’s percent share of county jobs in 2014. For instance, if Freeport had 4% of all county jobs in 2014, it will have 4% of all county jobs in 2040 as well.TAZ Geography: The municipal-level estimates from above are apportioned to the TAZ level using a similar method. Each TAZ’s share of the municipal total in which it resides is calculated for the 2014 data. This ratio is then carried forward as the basis for 2040. NAICS categories are then grouped into Manufacturing, Residual, Retail, and Services using the same ratio as 2014.

This map compares the number of people living above the poverty line to the number of people living below. Why do this?There are people living below the poverty line everywhere. Nearly every area of the country has a balance of people living above the poverty line and people living below it. There is not an "ideal" balance, so this map makes good use of the national ratio of 6 persons living above the poverty line for every 1 person living below it. Please consider that there is constant movement of people above and below the poverty threshold, as they gain better employment or lose a job; as they encounter a new family situation, natural disaster, health issue, major accident or other crisis. There are areas that suffer chronic poverty year after year. This map does not indicate how long people in the area have been below the poverty line. "The poverty rate is one of several socioeconomic indicators used by policy makers to evaluate economic conditions. It measures the percentage of people whose income fell below the poverty threshold. Federal and state governments use such estimates to allocate funds to local communities. Local communities use these estimates to identify the number of individuals or families eligible for various programs." Source: U.S. Census BureauIn the U.S. overall, there are 6 people living above the poverty line for every 1 household living below. Green areas on the map have a higher than normal number of people living above compared to below poverty. Orange areas on the map have a higher than normal number of people living below the poverty line compared to those above in that same area.The map shows the ratio for counties and census tracts, using these layers, created directly from the U.S. Census Bureau's American Community Survey (ACS)For comparison, an older layer using 2013 ACS data is also provided.The layers are 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. Poverty status is based on income in past 12 months of survey. Current Vintage: 2014-2018ACS Table(s): B17020Data downloaded from: Census Bureau's API for American Community Survey National 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. 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. 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 clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. 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., -555555...) have been set to null. 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. NOTE: any calculated percentages or counts that contain estimates that have null margins of error yield null margins of error for the calculated fields.

This raster analysis is based on 2015 LEHD data by location of the worker's home for all jobs. This raster layer is a point density analysis of the density of homes of workers with only a high school diploma. The cell size is set at 200 feet; the radius is set at ¾ mile.

Learn more about the LEHD data at the Census' website.

U.S. Census Bureau. (2017). LEHD Origin-Destination Employment Statistics (2015) [computer file]. Washington, DC: U.S. Census Bureau, Longitudinal-Employer Household Dynamics Program [distributor], at https://onthemap.ces.census.gov. LODES 7.3 [version]

LEHD Origin-Destination Employment Statistics (LODES) used by OnTheMap are available for download below. Version 7 of LODES was enumerated by 2010 census blocks. Previous versions of LODES were enumerated with 2000 census blocks. Data files are state-based and organized into three types: Origin-Destination (OD), Residence Area Characteristics (RAC), and Workplace Area Characteristics (WAC), all at census block geographic detail. Data is available for most states for the years 2002–2013. To browse the LODES data files in their directory structure or to access them with a FTP program (must be able to access HTTP), go to http://lehd.ces.census.gov/data/lodes/.

Check out the data dictionary at http://celebratingcities.github.io/docs.html

This raster analysis is based on 2015 LEHD data by location of the worker's home for all jobs. This raster layer is a point density analysis of the density of homes of workers with yearly earnings of $15,001 to $40,000. The cell size is set at 200 feet; the radius is set at 1 mile.

Learn more about the LEHD data at the Census' website.

U.S. Census Bureau. (2017). LEHD Origin-Destination Employment Statistics (2015) [computer file]. Washington, DC: U.S. Census Bureau, Longitudinal-Employer Household Dynamics Program [distributor], at https://onthemap.ces.census.gov. LODES 7.3 [version]

Opportunity Zones are defined as "census tracts that are defined by the Internal Revenue Service (IRS) as “economically-distressed community where new investments, under certain conditions, may be eligible for preferential tax treatment. They were added to the tax code by the Tax Cuts and Jobs Act on December 22, 2017" (CA Opportunity Zones). Areas highlighted on the map represent census tracts that were designated as Qualified Opportunity Zones. Designations are based on the boundaries of the tract at the time of the designation in 2018.The data associated with the map came from the U.S. Department of the Treasury's Opportunity Zones Resources webpage.

This app highlights the predominant generations that make up the population of the United States, using country to block group geographies that vary according to zoom level. The map, which was featured in Esri's Living Atlas gallery, forms the basis of an analysis of travel agency locations to determine the best one for launching luxury travel services to baby boomers. Use the Bookmarks tool to see the predominant generations in the census tract areas in and around Los Angeles, Chicago, and Washington, D.C. Click individual census tracts on the map to see pop-up information, including the population of each generation in a given census tract.This app was created for instructional purposes only and should not be used as an authoritative resource.

Abstract

The survey of the Pemba was an attempt to reach all households in Kenya with links to Pemba in Tanzania. It was conducted in the two counties of Kilifi and Kwale on the coast, north and south of Mombasa, respectively. According to information from village elders familiar with the Pemba community in Kenya, most of the Pemba population resides in these two counties. While there are some Pemba residents in Lamu, the security situation prevented data collection there. Further, a few Pemba are believed to live in the city of Mombasa and elsewhere in the country. But due to lack of further information, no data were collected in Mombasa or elsewhere. The objectives of the full survey, conducted in August 2016, were: 1. To establish the number and characteristics of the Pemba living in Kenya, including their arrival period in Kenya, nationality and their problems; 2. To make recommendations for the issuance of the documentation that is required for those who apply for citizenshiop by registration

Geographic coverage

Kwale and Kilifi counties, Kenya.

Analysis unit

Households, individuals

Universe

The total number of households with links to Pemba in Tanzania, in Kilifi and Kwale counties.

Kind of data

Census/enumeration data [cen]

Sampling procedure

A household mapping exercise was conducted in Kilifi and Kwale to identify Pemba households and to make it easier to locate them on the ground. The mapping was done from 4 to 12 August 2016 by a team from UNHCR Kenya office and KNBS. The mapping in each village commenced with a visit to the chief's office, who put the team in touch with the village chair. The team explained the purpose of its visit to the village chair and began the mapping exercise. The importance of involving the chiefs and village chairpersons is that they are well connected, recognised and trusted by residents in their communities. The same procedure is followed by KNBS when they are mapping for sample surveys and censuses. The team established physical boundaries of the area to be mapped, located the boundaries on the map and then identified and listed the Pemba households within the enumeration boundary. A Pemba household, in this context, is one identified by the informants as having at least one person with origins or links to Pemba. The links may include a person's spouse, parents or grandparents, who migrated to Kenya from Pemba or where a person has migrated from Pemba to Kenya. The mapping team was followed by the village chair to the Pemba households, where the UNHCR and Haki Centre staff listed number of persons in each, while the KNBS staff marked the location of the household on the map. The entrances of identified Pemba households were marked in chalk with the letters HCR and a number starting at 001 to make it easier to find the houses during the enumeration. Since it seems to be generally well known where the Pemba live it was not considered stigmatising to mark their doors. During the feedback forums with the Pemba after the survey, there was no mention of stigmatization due to marking the door with chalk. The maps were from the 2009 national housing and population census, purchased from KNBS. The team made lists with information about the location, number and size of each household. The mapping team visited 17 villages in Kilifi and Kwale (see Table 1 in Section 2.7). All villages visited were identified before the mapping exercise by key informants as locations being home to the Pemba of Kenya. The key informants were Pemba elders in different sub-counties previously identified for providing background information on the Pemba arrival and history in Kenya. In each sub-country, the chief, the assistant chief or the village chair also accompanied the team. In Kwale, 358 households were identified with 2,220 persons, and in Kilifi, 86 households with 558 persons.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaire was developed before the pilot survey and revised during and after the pilot survey, based on the experience gained. The pilot survey was used to test the questions and to check for inconsistences and misinterpretations due to unclear concepts and definitions. The testing process also revealed some important themes that had been left out. The structure of the questionnaire was altered, including the order of the questions and the introductory pages, to facilitate administration of the questionnaire. Finally, the questionnaire was translated into Swahili. Both the English and Swahili versions were used in the survey, even though the English version was preferred by almost all interviewers. The two versions of the questionnaire are attached in Annex 4 and 5. Enumerators used the English questionnaire to frame the questions in the local and less academic version of Swahili.

Cleaning operations

The data were imported into a Statistics Analysis Software (SAS) file and validated. Several errors were identified during the validation process, both on how the data had been recorded by the interviewers in the field and how the data had been entered by the clerks. There were particularly many errors in the entry of the variable “Relation to the household head” (Q.2). There were also many errors in the entry of the age of the household head, which was mostly due to errors in recording the right codes. A substantial amount of time was spent cleaning the data after the data had been entered, which included consulting many paper questionnaires. The quality of the survey data was significantly improved after the data entry revision. The data were analysed using both SAS software and Excel spreadsheets.

Response rate

The rate of non-response was low. Of the 452 households visited, visits to only 23 households can be categorised as non-response. A lot of effort was made to revisit non-responding households, using interviewers living nearby. Out of the 23 non-responsive households, 12 were not at home or there was no adult at home. There were 2 interrupted interviews, 7 refusals and 2 with no links to Pemba. In one household the respondent was not mentally stable enough to be interviewed, according to the enumerator.

This layer was developed by the Research & Analytics Division of the Atlanta Regional Commission using data from the U.S. Census Bureau's On the Map to show characteristics of workers in the Atlanta region by census tract.Attributes:TRACTCE10 = 6-digit census tract codeGEOID10 = The full FIPS code for this geographyNAME10 = Census tract codePLNG_REGIO = Planning regionPercent BA or HigherMedian household incomeTotal Workers, 2011Workers Age 29 or Younger, 2011Workers Age 30 to 54, 2011Workers Age 55 or Older, 2011Population Change per Square Mile from 2000 to 2010Workers Earnings, $1250 per Month or Less, 2011Workers Earnings, $1251 to $3333 per Month, 2011Workers Earnings, Greater Than $3333 per Month, 2011Percent Workers Age 29 or Younger, 2011Percent Workers Age 30 to 54, 2011Percent Workers Age 55 or Older, 2011Percent Workers Earnings, $1250 per Month or Less, 2011Percent Workers Earnings, $1251 to $3333 per Month, 2011Percent Workers Earnings, Greater Than $3333 per Month, 2011Workers in NAICS sector 11, Agriculture, Forestry, Fishing, and Hunting, 2011Workers in NAICS sector 21, Mining, Quarrying, and Oil & Gas Extraction, 2011Workers in NAICS sector 22, Utilities, 2011Workers in NAICS sector 23, Construction, 2011Workers in NAICS sectors 31 & 33, Manufacturing, 2011Workers in NAICS sector 42, Wholesale Trade, 2011Workers in NAICS sectors 44 & 45, Retail Trade, 2011Workers in NAICS sectors 48 & 49, Transportation and Warehousing, 2011Workers in NAICS sector 51, Information, 2011Workers in NAICS sector 52, Finance and Insurance, 2011Workers in NAICS sector 53, Real Estate and Rental & Leasing, 2011Workers in NAICS sector 54, Professional, Scientific, and Technical Services, 2011Workers in NAICS sector 55, Management of Companies and Enterprises, 2011Workers in NAICS sector 56, Administrative and Support and Waste Management and Remediation Services, 2011Workers in NAICS sector 61, Educational Services, 2011Workers in NAICS sector 62, Health Care and Social Assistance, 2011Workers in NAICS sector 71, Arts, Entertainment, and Recreation, 2011Workers in NAICS sector 72, Accommodation and Food Services, 2011Workers in NAICS sector 81, Other Services, except Public Administration, 2011Workers in NAICS sector 92, Public Administration, 2011Shape.STArea() = Area in square feetSource: U.S. Census Bureau, Atlanta Regional CommissionDate: 2011For additional information, please visit the Atlanta Regional Commission at www.atlantaregional.com