Combined Statistical AreasThis feature layer, utilizing National Geospatial Data Asset (NGDA) data from the U.S. Census Bureau (USCB), displays Combined Statistical Areas (CSA) in the United States. Per the USCB, "CSAs are defined by the Office of Management and Budget (OMB) and consist of two or more adjacent Core Based Statistical Areas (CBSAs) that have significant employment interchanges. The CBSAs that combine to create a CSA retain separate identities within the larger CSA. Because CSAs represent groupings of CBSAs, they should not be ranked or compared with individual CBSAs."Green Bay-Shawano, WIData currency: This cached Esri federal service is checked weekly for updates from its enterprise federal source (Combined Statistical Areas) and will support mapping, analysis, data exports and OGC API – Feature access.NGDAID: 74 (Series Information for Combined Statistical Area (CSA) National TIGER/Line Shapefiles, Current)OGC API Features Link: (Combined Statistical Areas - OGC Features) copy this link to embed it in OGC Compliant viewersFor more information, please visit: Combined Statistical Areas Map (March 2020)For feedback please contact: Esri_US_Federal_Data@esri.comNGDA Data SetThis data set is part of the NGDA Governmental Units, and Administrative and Statistical Boundaries Theme Community. Per the Federal Geospatial Data Committee (FGDC), this theme is defined as the "boundaries that delineate geographic areas for uses such as governance and the general provision of services (e.g., states, American Indian reservations, counties, cities, towns, etc.), administration and/or for a specific purpose (e.g., congressional districts, school districts, fire districts, Alaska Native Regional Corporations, etc.), and/or provision of statistical data (census tracts, census blocks, metropolitan and micropolitan statistical areas, etc.). Boundaries for these various types of geographic areas are either defined through a documented legal description or through criteria and guidelines. Other boundaries may include international limits, those of federal land ownership, the extent of administrative regions for various federal agencies, as well as the jurisdictional offshore limits of U.S. sovereignty. Boundaries associated solely with natural resources and/or cultural entities are excluded from this theme and are included in the appropriate subject themes."For other NGDA Content: Esri Federal Datasets

The CSA mine area 1:10,000 regolith-landform map illustrates the distribution of regolith materials and the landforms on which they occur, described using the RTMAP scheme developed by Geoscience Australia

PDF Map of UNEP Climate Security Assessment in North-Eastern Côte d'Ivoire project location.

Group average map of pial cortical surface area images in fsaverage space across 1,832 MRiShare subjects.

Collection description

This collection contains group average maps presented in the associated publication "The MRi-Share database: brain imaging in a cross-sectional cohort of 1,870 university students".

Subject species

homo sapiens

Modality

Structural MRI

Analysis level

group

Cognitive paradigm (task)

None / Other

Map type

A

Supermarkets are one of the most popular and convenient ways in which Americans gain access to healthy food, such as fresh meat and fish, or fresh fruits and vegetables. There are various ways in which people gain access to supermarkets. People in the suburbs drive to supermarkets and load up the car with many bags of food. People in cities depend much more on walking to the local store, or taking a bus or train.This map came about after asking a simple question: how many Americans live within a reasonable walk or drive to a supermarket?In this case, "reasonable" was defined as a 10 minute drive, or a 1 mile walk. The ArcGIS Network Analyst extension performed the calculations on streets data from StreetMap Premium, and the ArcGIS Spatial Analyst extension created a heat map of the walkable access and drivable access to supermarkets.The green dots represent populations in poverty who live within one mile of a supermarket. The red dots represent populations in poverty who live beyond a one mile walk to a supermarket, but may live within a 10 minute drive...which presumes they have access to a car or public transit. The grey dots represent the total population in a given area.This is an excellent map to use as backdrop to show how people are improving access to healthy food in their community. Open this map in ArcGIS Pro or ArcGIS Online to use it as a backdrop to your local analysis work. Or open it in ArcGIS Explorer to add your favorite farmers' market, CSA, or transit line -- then share that map via Facebook, Twitter or email.This map shows data for the entire U.S. The supermarkets included in the analysis have annual sales of $1 million or more.Data source: see this map package.

United States Mosaic - This RADARSAT-1 mosaic of the United States comprises 190 images acquired between March 1998 and October 1999. Include one full map and maps by regions (East Central, North East, North West, South Central, South East and South West). The mosaic was produced by MacDonald Dettwiler and Associates Ltd. in collaboration with the Canadian Space Agency (CSA) and the Canada Centre for Remote Sensing. RADARSAT data © CSA. Note that some more massive images can be complicated to download. It is then advisable to use a viewing tool created specifically for satellite images. Several tools are available in open format.

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The GO Canada initiative is a project that brings together a variety of space weather research tools and infrastructure. This network of ground-based instruments (more than 120 as of June 2019) that monitor space weather over Canada's North collects geospatial data, conducts scientific research and turns scientific knowledge into applications that benefit Canadians. This set of instruments, tools and measuring stations is essential for monitoring the Earth's magnetic field and protecting the population from solar flares. The proposed resources produce an interactive map (Google Earth) showing where GO Canada tools, instruments and research stations are located across the country. This data also identifies the devices and provides a link to the data generated by each station.

This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, contains seasonal (winter) ice sheet-wide velocity maps for Greenland. The maps are derived from Interferometric Synthetic Aperture Radar (InSAR) data obtained by the Canadian Space Agency's (CSA) RADARSAT-1, the Japan Aerospace Exploration Agency's (JAXA) Advanced Land Observation Satellite (ALOS), and the German Aerospace Center's (DLR) TerraSAR-X/TanDEM-X (TSX/TDX) satellites, as well as from the European Space Agency's (ESA) C-band Synthetic Aperture Radar data from Copernicus Sentinel-1A and -1B. See Greenland Ice Mapping Project (GIMP) for related data.

Supermarkets are one of the most popular and convenient ways in which Americans gain access to healthy food, such as fresh meat and fish, or fresh fruits and vegetables. There are various ways in which people gain access to supermarkets. People in the suburbs drive to supermarkets and load up the car with many bags of food. People in cities depend much more on walking to the local store, or taking a bus or train.This map came about after asking a simple question: how many Americans live within a reasonable walk or drive to a supermarket?In this case, "reasonable" was defined as a 10 minute drive, or a 1 mile walk. The ArcGIS Network Analyst extension performed the calculations on streets data from StreetMap Premium, and the ArcGIS Spatial Analyst extension created a heat map of the walkable access and drivable access to supermarkets.The green dots represent populations in poverty who live within one mile of a supermarket. The red dots represent populations in poverty who live beyond a one mile walk to a supermarket, but may live within a 10 minute drive...which presumes they have access to a car or public transit. The grey dots represent the total population in a given area.This is an excellent map to use as backdrop to show how people are improving access to healthy food in their community. Open this map in ArcGIS Pro or ArcGIS Online to use it as a backdrop to your local analysis work. Or open it in ArcGIS Explorer to add your favorite farmers' market, CSA, or transit line -- then share that map via Facebook, Twitter or email. See this web map for a map with a popup layer.This map shows data for the entire U.S. The supermarkets included in the analysis have annual sales of $1 million or more.Data source: see this map package.

The H1B Sponsorship Trends linear chart shows the number of H1B cases filed by Csa America Standards from 2020 to 2023, providing a clear view of filing trends over time. Alongside, the horizontal bar chart titled Distribution of Job Fields Receiving H1B Sponsorship breaks down which roles and industries are most commonly sponsored.

This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, provides the first comprehensive, high-resolution, digital mosaics of ice motion in Antarctica assembled from multiple satellite interferometric synthetic-aperture radar data. Data were acquired during the International Polar Year 2007 to 2009.

These maps were built from spring 2009 data from the Canadian Space Agency (CSA)'s and MacDonald, Dettwiler and Associates Ltd. (MDA)'s RADARSAT-2, spring 2007-2008-2009 data from European Space Agency (ESA)'s Envisat Advanced Synthetic Aperture Radar (ASAR), and fall 2007-2008 data from the Japan Aerospace Exploration Agency (JAXA)'s Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR), complemented by patches of CSA's RADARSAT-1 data from fall 2000 and ESA's Earth Remote Sensing Satellites ERS-1 and -2 data from spring 1996. Each radar instrument contributes its unique coverage and performance level. The final mosaics assemble 900 satellite tracks and more than 3,000 orbits of radar data. Data acquisitions between 2006 and 2011 are courtesy of the IPY Space Task Group.

Data are available via FTP at 450 m and 900 m spacings, in both binary format (.dat) with an ENVI text header (.txt) and NetCDF.

Note. These data are considered provisional pending a review by the MEaSUREs program. Once the data have been reviewed, this statement will be removed from this documentation.

This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, provides annual maps of Antarctic ice velocity. The maps are assembled using SAR data from the Japanese Space Agency's (JAXA) ALOS PALSAR, the European Space Agency's (ESA) ENVISAT ASAR and Copernicus Sentinel-1, the Canadian Space Agency's (CSA) RADARSAT-1, RADARSAT-2, the German Aerospace Agency's (DLR) TerraSAR-X (TSX) and TanDEM –X (TDX), and the U.S. Geological Survey's (USGS) Landsat-8 optical imagery.. See Antarctic Ice Sheet Velocity and Mapping Data for related data.

A new global map of climate classifications using the Koppen-Geiger system has been produced based on a large global data set of long-term monthly precipitation and temperature station time series.

To construct the new map, long-term station records of monthly precipitation and monthly temperature were obtained from the Global Historical Climatology Network (GHCN) version 2.0 data set (Peterson and Vose, 1997). Stations from this data set with at least 30 observations for each month were used in the analysis (12,396 precipitation and 4,844 temperature stations). The data are most representative from 1909 to 1991 for precipitation and 1923 to 1993 for temperature. Climatic variables were interpolated between stations in ESRI ArcMap version 9.1 using a two-dimensional (latitude and longitude) thin-plate spline with tension onto a 0.1 x 0.1 degree grid for each continent. The Koppen-Geiger criteria were then applied to the splined variables.

The Koppen-Geiger system includes 30 possible climate types. They are divided into 3 tropical (Af, Am and Aw), 4 arid (BWh, BWk, BSh and BSk), 9 temperate (Csa, Csb, Csc, Cfa, Cfb, Cfc, Cwa, Cwb and Cwc), 12 cold (Dsa, Dsb, Dsc, Dsd, Dfa, Dfb, Dfc, Dfd, Dwa, Dwb, Dwc and Dwd) and 2 polar (ET and EF) (The source document and metadata record define the subdivisions). All precipitation variables are in units of millimetres (mm) and all temperature variables are in units of degrees Celsius (C).

Koppen-Geiger climate type maps were constructed for each continent and the percentage of land area covered by the major climate types was calculated. Since the area of a 0.1 x 0.1 degree pixel changes with latitude, a map of 0.1 x 0.1 degree pixel area was constructed and then projected onto a Cylindrical Equal Area projection of the world to determine the area (in km2) of each 0.1 x 0.1 degree pixel. These pixel areas were then summed for each climate type to provide an estimate of the land area covered by each climate type. The continental maps are presented and discussed in Peel et al. (2007). The global map is available for download in ESRI Arc Grid.

Oak Ridge National Laboratory (ORNL) also provides the updated World Map of the Koppen-Geiger Climate Classification, but in GeoTiff format. ORNL Convert data from ESRI Grid format to GeoTIFF format. The processed GeoTIFF data were fed into ORNL DAAC Web Map Service v1.1.1 (WMS), Web Coverage Service v1.0.0 (WCS), and Spatial Data Access Tool (SDAT) to provide data visualization and distribution capabilities. References:

Koppen, W. 1936. Das geographisca System der Klimate, in: Handbuch der Klimatologie, edited by: K¨oppen, W. and Geiger, G., 1. C. Gebr, Borntraeger, 1â�“44.

Peel, M. C., B. L. Finlayson, and T. A. McMahon. 2007. Updated World Map of the Koppen-Geiger Climate Classification. Hydrol. Earth Syst. Sci., 11, 1633-1644. doi:10.5194/hess-11-1633-2007.

Peterson, T.C., and R.S. Vose. 1997. An overview of the Global Historical Climatology Network temperature database, Bull. Am. Meteorol. Soc., 78(12), 2837�2849.

This data set, part of the National Aeronautics and Space Administration (NASA) Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, contains seasonal (winter) ice sheet-wide velocity maps for Greenland. The maps are derived from Interferometric Synthetic Aperture Radar (InSAR) data obtained by the Canadian Space Agency's (CSA) RADARSAT-1, the Japan Aerospace Exploration Agency's (JAXA) Advanced Land Observation Satellite (ALOS), and the German Aerospace Center's (DLR) TerraSAR-X/TanDEM-X (TSX/TDX) satellites, as well as from the European Space Agency's (ESA) C-band Synthetic Aperture Radar data from Copernicus Sentinel-1A and -1B. This data set contains eleven winter Greenland ice sheet-wide mosaicked velocity maps derived from Synthetic Aperture Radar (SAR) data. Depending on the year, different platforms and sensors were used to produce these data (see Table 3). For each winter, a shapefile is included to indicate the source satellite image pairs that were processed to produce the mosaic. Since speckle tracking may fail to produce results at some points within a SAR image pair, the swaths listed in the shapefile only indicate which data could have contributed to a particular point (i.e., some data from that swath were used in the mosaic, but at any particular point, there may not have been a valid result from that swath). Joughin, I., B. Smith, I. Howat, and T. Scambos. 2015, updated 2018. MEaSUREs Greenland Ice Sheet Velocity Map from InSAR Data, Version 2. Boulder, Colorado USA. NASA National Snow and Ice Data Center Distributed Active Archive Center. doi: https://doi.org/10.5067/OC7B04ZM9G6Q. 13 Nov 2020.

Complete map of ice motion in Antarctica combining phase data in the interior and speckle tracking in the fast-moving sectors.

We present a new map of Antarctic ice velocity that is ten times more precise than prior maps and reveals ice motion at a high precision over 80% of the continent versus 20% in the past. The ice motion vector map provides novel constrains on interior ice motion and its connection with the glaciers and ice stream that control the stability and mass balance of the Antarctic Ice Sheet.

The H1B Sponsorship Trends linear chart shows the number of H1B cases filed by Csa America from 2020 to 2023, providing a clear view of filing trends over time. Alongside, the horizontal bar chart titled Distribution of Job Fields Receiving H1B Sponsorship breaks down which roles and industries are most commonly sponsored.

Tabular data of population by age groups, race and gender, and the poverty by race is attached to the split tract geography to create this split tract with population and poverty data. Split tract data is the product of 2010 census tracts split by 2019 incorporated city boundaries and unincorporated community/countywide statistical areas (CSA) boundaries. The census tract boundaries have been altered and aligned where necessary with legal city boundaries and unincorporated areas, including shoreline/coastal areas. Census Tract:Every 10 years the Census Bureau counts the population of the United States as mandated by Constitution. The Census Bureau (https://www.census.gov/) released 2010 geographic boundaries data including census tracts for the analysis and mapping of demographic information across the United States. City Boundary:City Boundary data is the base map information for the County of Los Angeles. These City Boundaries are based on the Los Angeles County Seamless Cadastral Landbase. The Landbase is jointly maintained by the Los Angeles County Assessor and the Los Angeles County Department of Public Works (DPW). This layer represents current city boundaries within Los Angeles County. The DPW provides the most current shapefiles representing city boundaries and city annexations. True, legal boundaries are only determined on the ground by surveyors licensed in the State of California.Countywide Statistical Areas (CSA): The countywide Statistical Area (CSA) was defined to provide a common geographic boundary for reporting departmental statistics for unincorporated areas and incorporated Los Angeles city to the Board of Supervisors. The CSA boundary and CSA names are established by the CIO and the LA County Enterprise GIS group worked with the Los Angeles County Board of Supervisors Unincorporated Area and Field Deputies that reflect as best as possible the general name preferences of residents and historical names of areas. This data is primarily focused on broad statistics and reporting, not mapping of communities. This data is not designed to perfectly represent communities, nor jurisdictional boundaries such as Angeles National Forest. CSA represent board approved geographies comprised of Census block groups split by cities.Data Field:CT10: 2010 Census tractFIP19: 2019 City FIP CodeCITY: City name for incorporated cities and “Unincorporated” for unincorporated areas (as of July 1, 2019) CSA: Countywide Statistical Area (CSA) - Unincorporated area community names and LA City neighborhood names.CT10FIP19CSA: 2010 census tract with 2019 city FIPs for incorporated cities, unincorporated areas and LA neighborhoods. SPA12: 2012 Service Planning Area (SPA) number.SPA_NAME: Service Planning Area name.HD12: 2012 Health District (HD) number: HD_NAME: Health District name.POP19_AGE_0_4: 2019 population 0 to 4 years oldPOP19_AGE_5_9: 2019 population 5 to 9 years old POP19_AGE_10_14: 2019 population 10 to 14 years old POP19_AGE_15_17: 2019 population 15 to 17 years old POP19_AGE_18_19: 2019 population 18 to 19 years old POP19_AGE_20_44: 2019 population 20 to 24 years old POP19_AGE_25_29: 2019 population 25 to 29 years old POP19_AGE_30_34: 2019 population 30 to 34 years old POP19_AGE_35_44: 2019 population 35 to 44 years old POP19_AGE_45_54: 2019 population 45 to 54 years old POP19_AGE_55_64: 2019 population 55 to 64 years old POP19_AGE_65_74: 2019 population 65 to 74 years old POP19_AGE_75_84: 2019 population 75 to 84 years old POP19_AGE_85_100: 2019 population 85 years and older POP19_WHITE: 2019 Non-Hispanic White POP19_BLACK: 2019 Non-Hispanic African AmericanPOP19_AIAN: 2019 Non-Hispanic American Indian or Alaska NativePOP19_ASIAN: 2019 Non-Hispanic Asian POP19_HNPI: 2019 Non-Hispanic Hawaiian Native or Pacific IslanderPOP19_HISPANIC: 2019 HispanicPOP19_MALE: 2019 Male POP19_FEMALE: 2019 Female POV19_WHITE: 2019 Non-Hispanic White below 100% Federal Poverty Level POV19_BLACK: 2019 Non-Hispanic African American below 100% Federal Poverty Level POV19_AIAN: 2019 Non-Hispanic American Indian or Alaska Native below 100% Federal Poverty Level POV19_ASIAN: 2019 Non-Hispanic Asian below 100% Federal Poverty Level POV19_HNPI: 2019 Non-Hispanic Hawaiian Native or Pacific Islander below 100% Federal Poverty Level POV19_HISPANIC: 2019 Hispanic below 100% Federal Poverty Level POV19_TOTAL: 2019 Total population below 100% Federal Poverty Level POP19_TOTAL: 2019 Total PopulationAREA_SQMIL: Area in square milePOP19_DENSITY: Population per square mile.POV19_PERCENT: Poverty percentage.How this data created?The tabular data of population by age groups, by ethnic groups and by gender, and the poverty by ethnic groups is attributed to the split tract geography to create this data. Split tract polygon data is created by intersecting 2010 census tract polygons, LA Country City Boundary polygons and Countywide Statistical Areas (CSA) polygon data. The resulting polygon boundary aligned and matched with the legal city boundary whenever possible. Note:1. Population and poverty data estimated as of July 1, 2019. 2. 2010 Census tract and 2020 census tracts are not the same. Similarly, city and community boundary are not the same because boundary is reviewed and updated annually.

The PERM Sponsorship Trends linear chart visualizes the number of PERM cases filed by Csa America Standards from 2020 to 2023, highlighting the company’s long-term sponsorship patterns. The horizontal bar chart titled Distribution of Job Fields Receiving PERM Sponsorship further categorizes sponsored roles by job type.

The PERM Sponsorship Trends linear chart visualizes the number of PERM cases filed by Csa America from 2020 to 2023, highlighting the company’s long-term sponsorship patterns. The horizontal bar chart titled Distribution of Job Fields Receiving PERM Sponsorship further categorizes sponsored roles by job type.