Browse UnitedHealth Group Incorporated (UNH) market data. Get instant pricing estimates and make batch downloads of binary, CSV, and JSON flat files.

Consolidated last sale, exchange BBO and national BBO across all US equity options exchanges. Includes single name stock options (e.g. TSLA), options on ETFs (e.g. SPY, QQQ), index options (e.g. VIX), and some indices (e.g. SPIKE and VSPKE). This dataset is based on the newer, binary OPRA feed after the migration to SIAC's OPRA Pillar SIP in 2021. OPRA is notable for the size of its data and we recommend users to anticipate several TBs of data per day for the full dataset in its highest granularity (MBP-1).

Origin: Options Price Reporting Authority

Supported data encodings: DBN, JSON, CSV Learn more

Supported market data schemas: MBP-1, OHLCV-1s, OHLCV-1m, OHLCV-1h, OHLCV-1d, TBBO, Trades, Statistics, Definition Learn more

Resolution: Immediate publication, nanosecond-resolution timestamps

This data depicts the social vulnerability of New Hampshire census block groups to environmental hazards. Data were culled primarily from the 2000 Decennial Census.

The present data set demonstrates the potential of combining observed river discharge information with a climate-driven Water Balance Model in order to develop composite runoff fields which are consistent with observed discharges. Such combined runoff fields preserve the accuracy of the discharge measurements as well as the spatial and temporal distribution of simulated runoff, thereby providing the "best estimate" of terrestrial runoff over large domains.

 The method applied in the preparation of this data set utilizes a
 gridded river network at 30-minute spatial resolution to represent the
 riverine flow pathways and to link the continental land mass to oceans
 through river channels. Selected gauging stations from the Global
 Runoff Data Centre data archive were co-registered to a simulated
 topological network (STN-30p) developed at the University of New
 Hampshire. Inter-station regions between gauging stations along the
 STN-30p network were identified. Inter-station discharge and runoff
 were calculated to compare observed runoff with outputs from the water
 balance model (WBM) simulation. Correction coefficients based on the
 ratio of observed and simulated runoff for inter-station areas were
 calculated and applied against simulated runoff to create composite
 runoff fields.

 The present CD contains not only "UNH-GRDC Composite Runoff Fields
 V1.0" but also intermediate data sets, such as station attributes and
 long-term monthly regimes of the selected gauging stations. Also
 included on the CD are the simulated topological network (STN-30p),
 STN-30p derived attributes for the selected stations and gridded
 fields of the inter-station regions along STN-30p.

 An HTML based data explorer was developed to help users of the
 CD-ROM view the data. With a standard web browser and the CD it is
 possible to navigate from a global view of the data, down to a
 subbasin or station level.

 The printed version of the report can be ordered free of charge
 from GRDC (grdc@bafg.de) or WMO (dhwr@gateway.wmo.ch).

 Note: Due to inaccuracies in the topographical dataset used for the
 compilation of the simulated river network, errors may occur in the
 graphical display of certain lower-order rivers. Users are invited to
 send their comments and notification of errors to the e-mail addresses
 shown above.

 The full report on the UNH/GRDC is available here -
 "http://www.grdc.sr.unh.edu/html/paper/index.html"

This data set contains vector polygons representing the boundaries of all the hardcopy cartographic products produced as part of the Environmental Sensitivity Index (ESI) for New Hampshire, as well as digital data extents. This data set comprises a portion of the ESI data for New Hampshire. ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil. The ESI data include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources.

The Ocean Uses Atlas Project is an innovative partnership between the Coastal Response Research Center (CRRC) and NOAA's Office of Ocean and Coastal Resource Management (OCRM). The Project was designed to enhance ocean management through geospatial data on the full range of significant human uses of the ocean environment from the shorelines of New Hampshire and Southern Maine to the EEZ boundary. The data were gathered from regional ocean experts and users through participatory GIS methods. For more information on the project scope, background and related data products, please visit http://www.crrc.unh.edu/workshops/ocean_uses/index.html or http://marineprotectedareas.noaa.gov/dataanalysis/atlas_nhsm/.

The 2015 1-foot orthophotography mosiac for New Hampshire (CIR) is composed of GeoTIFF images described in the following metadata:This data set consists of 0.30-meter, 4-band natural color orthoimages covering approximately 9,329 square miles (including water) over the New Hampshire State Wide area and its offshore islands. An orthoimage is remotely sensed image data in which displacement of features in the image caused by terrain relief and variations in aircraft altitude and orientation have been mathematically removed. Orthoimagery combines the image characteristics of a photograph with the geometric qualities of a map. For 0.30 meter GSD Ortho image, horizontal positional accuracy was designed not to exceed 1.52 meters NSSDA 95% confidence. This dataset consists of uncompressed, ortho photo tiles, produced at a scale of 1:2400 (1"=200'), and formatted as 8-bit, 4-band (RGB-IR), uncompressed, GeoTIFF images with TIF world files. A total of 10,805 tiles were produced in New Hampshire State Plane, Zone 2800, US Survey Feet. Tile size is 5,000 feet x 5,000 ft and uses the 2010 tile index which derives the tile file name from the southwest corner of each tile. There is no image overlap between adjacent files. Aerial photography of New Hampshire was captured during the Spring of 2015 on the following flight dates: May 6, 2015; May 7, 2015; and May 14, 2015. The Nominal Acquisition Altitude of 15,142 ft (AGL) was used to capture the 0.30-meter imagery. The Microsoft UltraCam and Eagle (UCE) large format digital camera was used to capture four band (RGB-IR) imagery at 8 bits. Maximum and mean differential baseline lengths were not generated for the NH Statewide project due to the use of Applanix SmartBase software to process and compute atmospheric errors within a specified GNSS multi-base network. SmartBase processing offers a number of significant benefits including: the distance to the nearest reference station can be extended well beyond 30 km; the time to fix integer ambiguities is significantly reduced; and the overall reliability of fixing integer ambiguities is increased. No special processing is required in the RTK engine, as it is the case for a centralized multi-base approach. Due to the complexity of the typical reference station network used in SmartBase processing, determining maximum and mean differential baseline lengths is not feasible for this project.

The Ocean Uses Atlas Project is an innovative partnership between the Coastal Response Research Center (CRRC) and NOAA's Office of Ocean and Coastal Resource Management (OCRM). The Project was designed to enhance ocean management through geospatial data on the full range of significant human uses of the ocean environment from the shorelines of New Hampshire and Southern Maine to the EEZ boundary. The data were gathered from regional ocean experts and users through participatory GIS methods. For more information on the project scope, background and related data products, please visit http://www.crrc.unh.edu/workshops/ocean_uses/index.html or https://coast.noaa.gov/arcgis/rest/services/MarineCadastre/OceanUsesNewHampshireMaine/MapServer.

This data set contains vector lines and polygons representing the shoreline and coastal habitats of New Hampshire classified according to the Environmental Sensitivity Index (ESI) classification system. This data set comprises a portion of the ESI for New Hampshire. ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil. The ESI data include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources.

This data set contains vector lines representing coastal habitats of Maine and New Hampshire, classified by their susceptibility to oiling. The Environmental Sensitivity Index (ESI) classification system, developed by NOAA, considers several natural and biological factors when ranking an intertidal range's sensitivity and persistence of oil impacts. This data set is a portion of the ESI data for Maine and New Hampshire. As a whole, the ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil, and include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources. See also the HYDROL (Hydrography Lines), HYDROP (Hydrography Polygons), ESIP (ESI Shoreline Types - Polygons) data layer for additional shoreline/hydrography information.

This data set contains vector polygons representing the coastal shoreline and hydrography used in the creation of the Environmental Sensitivity Index (ESI) for Maine and New Hampshire. As a whole, the ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil, and include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources. See also the HYDROL (Hydrography Lines), ESIL (ESI Shoreline Types - Lines), ESIP (ESI Shoreline Types - Polygons) data layer for additional shoreline/hydrography information.

This data set represents smoothed, 2-foot bare earth contours (isolines) for the Ossipee Lake (0106000208) HUC 10 unit. It was derived from a data set which was compiled from LIDAR collections in NH available as of spring, 2019. The raster was filtered using the ArcGIS FOCAL STATISTICS tool with a 3x3 circular neighborhood. The contours were generated using the ArcGIS CONTOUR tool while applying a Z factor of 3.2808 to convert the elevation values from meters to feet. The filtered contours were then smoothed using the ArcGIS SMOOTH LINE tool. The data include an INDEX field with values of 10 and 100 to flag 10 and 100-foot contours. Note on HUC 01060000310: Due to limitations in the source LIDAR data, some anomalies exist in the generated contours in coastal areas of the state. These were left in the data so that users can determine what further processing best meets their application needs.

UNH Coastal Marine Laboratory. Ocean observation data from the Northeastern Regional Associationof Coastal & Ocean Observing Systems (Northeastern Regional Association Ocean Observing Systems (NERACOOS)).The NERACOOS region includes the northeast United States andCanadian Maritime provinces, as part of the United StatesIntegrated Ocean Observing System (IOOS). These data are servedby Unidatas Thematic Realtime Environmental Distributed Data Services (THREDDS) Data Server (TDS) in a variety of interoperabledata services and output formats area=Gulf of Maine author=Joe Salisbury cdm_data_type=TimeSeries cdm_timeseries_variables=platform, longitude, latitude, depth citation=Data from CML made available by Joe Salisbury of UNH/OPAL comment=Processed with Matlab contact=Joe Salisbury contributor_name=Chris Hunt contributor_role=Data Manager Conventions=CF-1.6, COARDS, ACDD-1.3 data_type=CML time-series data defaultGraphQuery=time,temperature&temperature_QARTOD_gross_range_test=1&time%3E=now-7days&.draw=lines&.color=0x000000 deployment_code=2023 deployment_number=2023 Easternmost_Easting=70.0798 featureType=TimeSeries geospatial_lat_max=43.0718 geospatial_lat_min=43.0718 geospatial_lat_resolution=0.01 degrees geospatial_lat_units=degrees_north geospatial_lon_max=70.0798 geospatial_lon_min=70.0798 geospatial_lon_resolution=0.01 degrees geospatial_lon_units=degrees_east geospatial_vertical_max=3.0 geospatial_vertical_min=3.0 geospatial_vertical_positive=down geospatial_vertical_resolution=0.1 geospatial_vertical_units=m history=processed with Matlab by Chris Hunt, 2023-04-29 converted to NetCDF id=CML_2023 infoUrl=http://www.neracoos.org/ institution=Univ. of New Hampshire - Ocean Process Analysis Laboratory- University of New Hampshire julian_date_convention=Julian_date_convention_starts_at_00:00:00_UTC_on_17_November_1858_AD keywords_vocabulary=GCMD Science Keywords Metadata_Conventions=Unidata Dataset Discovery v1.6 metadata_link=http://www.opal.sr.unh.edu missing_flag=-999 mooring_site_ID=CML naming_authority=edu.unh neracoos_data_provider=UNH netcdf_version=netcdf4_classic Northernmost_Northing=43.0718 observation_depth=surface platform_code=CML principal_investigator=Joe Salisbury processing_level=not QCd, see qc_manual project=NERACOOS provider_email=joe.salisbury@unh.edu provider_institution=Ocean Process Analysis Laboratory- University of New Hampshire provider_name=Joe_Salisbury provider_url=http://www.opal.sr.unh.edu qc_manual=void quality_control_procedure=see qc_manual quality_index=manually reviewed, not QCd references=http://www.opal.sr.unh.edu/research.shtml sea_name=Atlantic Ocean site_code=CML source=coastal laboratory sourceUrl=(local files) Southernmost_Northing=43.0718 standard_name_vocabulary=CF Standard Name Table v29 subsetVariables=platform, depth, latitude, longitude time_coverage_duration=P48D time_coverage_end=2023-04-29T10:58:04Z time_coverage_resolution=P1M time_coverage_start=2008-01-01T00:00:00Z time_zone=UTC update_interval=void watch_circle=void water_depth=8m Westernmost_Easting=70.0798

This data set represents smoothed, 2-foot bare earth contours (isolines) for the Lamprey River (0106000307) HUC 10 unit. It was derived from a data set which was compiled from LIDAR collections in NH available as of spring, 2019. The raster was filtered using the ArcGIS FOCAL STATISTICS tool with a 3x3 circular neighborhood. The contours were generated using the ArcGIS CONTOUR tool while applying a Z factor of 3.2808 to convert the elevation values from meters to feet. The filtered contours were then smoothed using the ArcGIS SMOOTH LINE tool. The data include an INDEX field with values of 10 and 100 to flag 10 and 100-foot contours. Note on HUC 01060000310: Due to limitations in the source LIDAR data, some anomalies exist in the generated contours in coastal areas of the state. These were left in the data so that users can determine what further processing best meets their application needs.

This data set contains vector polygons representing the coastal shoreline and hydrography used in the creation of the Environmental Sensitivity Index (ESI) for Maine and New Hampshire. As a whole, the ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil, and include information for three main components: shoreline habitats, sensitive biologi...

This data set provides a time series of vegetation phenological observations for 393 sites across diverse ecosystems of the world (mostly North America) from 2000-2018. The phenology data were derived from conventional visible-wavelength automated digital camera imagery collected through the PhenoCam Network at each site. From each acquired image, RGB (red, green, blue) color channel information was extracted and means and other statistics calculated for a region-of-interest (ROI) that delineates an area of specific vegetation type. From the high-frequency (typically, 30 minute) imagery collected over several years, time series characterizing vegetation color, including canopy greenness, plus greenness rising and greenness falling transition dates, were summarized over 1- and 3-day intervals.The PhenoCam data are released under a CC-BY license.

This data set contains vector lines and polygons representing coastal hydrography used in the creation of the Environmental Sensitivity Index (ESI) for New Hampshire. The Hydro data layer contains all annotation used in producing the atlas. The annotation features are categorized into three subclasses in order to simplify the mapping and quality control procedures: GEOG or geographic features, SOC or socioeconomic features, and HYDRO or water features. This data set comprises a portion of the ESI for New Hampshire. ESI data characterize the marine and coastal environments and wildlife by their sensitivity to spilled oil. The ESI data include information for three main components: shoreline habitats, sensitive biological resources, and human-use resources.

UNH Jackson Laboratory. Ocean observation data from the Northeastern Regional Association of Coastal & Ocean Observing Systems (Northeastern Regional Association Ocean Observing Systems (NERACOOS)).The NERACOOS region includes the northeast United States and Canadian Maritime provinces, as part of the United States Integrated Ocean Observing System (IOOS). These data are servedby Unidata's Thematic Realtime Environmental Distributed Data Services (THREDDS) Data Server (TDS) in a variety of interoperable data services and output formats _NCProperties=version=2,netcdf=4.9.2,hdf5=1.14.4 area=Gulf of Maine author=Chris Hunt cdm_data_type=TimeSeries cdm_timeseries_variables=platform, longitude, latitude, depth citation=Data from JEL made available by Chris Hunt of UNH/OPAL comment=Processed with Matlab contact=Chris Hunt contributor_name=Chris Hunt contributor_role=Data Manager Conventions=CF-1.8, COARDS, ACDD-1.3, IOOS 1.2 data_type=WBD time-series data defaultGraphQuery=time,temperature&temperature_QARTOD_gross_range_test=1&time%3E=now-7days&.draw=lines&.color=0x000000 deployment_code=2017 deployment_number=2017 DODS_dimName=platform_name_length DODS_EXTRA_Unlimited_Dimension=time DODS_strlen=5 Easternmost_Easting=70.8649 featureType=TimeSeries geospatial_lat_max=43.0923 geospatial_lat_min=43.0923 geospatial_lat_resolution=0.01 degrees geospatial_lat_units=degrees_north geospatial_lon_max=70.8649 geospatial_lon_min=70.8649 geospatial_lon_resolution=0.01 degrees geospatial_lon_units=degrees_east geospatial_vertical_max=3.0 geospatial_vertical_min=3.0 geospatial_vertical_positive=down geospatial_vertical_resolution=0.1 geospatial_vertical_units=m gts_ingest=true history=processed with Matlab by Chris Hunt, 2024-04-23 converted to NetCDF id=JEL_2025 infoUrl=http://www.opal.sr.unh.edu institution=Ocean Process Analysis Laboratory - University of New Hampshire julian_date_convention=Julian_date_convention_starts_at_00:00:00_UTC_on_17_November_1858_AD keywords_vocabulary=GCMD Science Keywords Metadata_Conventions=Unidata Dataset Discovery v1.6 metadata_link=http://www.opal.sr.unh.edu missing_flag=-999.0 mooring_site_ID=JEL naming_authority=edu.unh neracoos_data_provider=UNH netcdf_version=netcdf4_classic Northernmost_Northing=43.0923 observation_depth=surface platform=station platform_code=JEL platform_name=Coastal Marine Laboratory principal_investigator=Chris Hunt processing_level=not QCd, see qc_manual project=NERACOOS provider_email=chunt@unh.edu provider_institution=Ocean Process Analysis Laboratory- University of New Hampshire provider_name=Chris_Hunt provider_url=http://www.opal.sr.unh.edu qc_manual=void quality_control_procedure=see qc_manual quality_index=manually reviewed, not QCd references=http://www.opal.sr.unh.edu/research.shtml sea_name=Atlantic Ocean site_code=JEL source=Jackson laboratory sourceUrl=https://tds-opal.sr.unh.edu/thredds/catalog/opal_ts/JEL/catalog.html Southernmost_Northing=43.0923 standard_name_vocabulary=CF Standard Name Table v79 subsetVariables=platform, depth, latitude, longitude testOutOfDate=now-1day time_coverage_duration=P48D time_coverage_end=2025-07-03T00:00:00Z time_coverage_resolution=P1M time_coverage_start=2024-01-01T00:00:00Z time_zone=UTC update_interval=void watch_circle=void water_depth=8m Westernmost_Easting=70.8649 wmo_platform_code=JELN3

description: The Ocean Uses Atlas Project is an innovative partnership between the Coastal Response Research Center (CRRC) and NOAA's Office of Ocean and Coastal Resource Management (OCRM). The Project was designed to enhance ocean management through geospatial data on the full range of significant human uses of the ocean environment from the shorelines of New Hampshire and Southern Maine to the EEZ boundary. The data were gathered from regional ocean experts and users through participatory GIS methods. For more information on the project scope, background and related data products, please visit http://www.crrc.unh.edu/workshops/ocean_uses/index.html or https://coast.noaa.gov/arcgis/rest/services/MarineCadastre/OceanUsesNewHampshireMaine/MapServer.; abstract: The Ocean Uses Atlas Project is an innovative partnership between the Coastal Response Research Center (CRRC) and NOAA's Office of Ocean and Coastal Resource Management (OCRM). The Project was designed to enhance ocean management through geospatial data on the full range of significant human uses of the ocean environment from the shorelines of New Hampshire and Southern Maine to the EEZ boundary. The data were gathered from regional ocean experts and users through participatory GIS methods. For more information on the project scope, background and related data products, please visit http://www.crrc.unh.edu/workshops/ocean_uses/index.html or https://coast.noaa.gov/arcgis/rest/services/MarineCadastre/OceanUsesNewHampshireMaine/MapServer.

About this dataset

Context

The dataset illustrates the median household income in Hampton Falls town, spanning the years from 2010 to 2023, with all figures adjusted to 2023 inflation-adjusted dollars. Based on the latest 2019-2023 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

Key observations:

From 2010 to 2023, the median household income for Hampton Falls town decreased by $2,152 (1.36%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $5,602 (7.68%) between 2010 and 2023.

Analyzing the trend in median household income between the years 2010 and 2023, spanning 13 annual cycles, we observed that median household income, when adjusted for 2023 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 6 years and declined for 7 years.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2019-2023 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Years for which data is available:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 0223

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2023
• Median Household Income: Median household income, in 2023 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2023 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Hampton Falls town median household income. You can refer the same here

About this dataset

Context

The dataset illustrates the median household income in New Hampshire, spanning the years from 2010 to 2021, with all figures adjusted to 2022 inflation-adjusted dollars. Based on the latest 2017-2021 5-Year Estimates from the American Community Survey, it displays how income varied over the last decade. The dataset can be utilized to gain insights into median household income trends and explore income variations.

Key observations:

From 2010 to 2021, the median household income for New Hampshire increased by $4,823 (5.65%), as per the American Community Survey estimates. In comparison, median household income for the United States increased by $4,559 (6.51%) between 2010 and 2021.

Analyzing the trend in median household income between the years 2010 and 2021, spanning 11 annual cycles, we observed that median household income, when adjusted for 2022 inflation using the Consumer Price Index retroactive series (R-CPI-U-RS), experienced growth year by year for 7 years and declined for 4 years.

https://i.neilsberg.com/ch/new-hampshire-median-household-income-trend.jpeg" alt="New Hampshire median household income trend (2010-2021, in 2022 inflation-adjusted dollars)">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates. All incomes have been adjusting for inflation and are presented in 2022-inflation-adjusted dollars.

Years for which data is available:

• 2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021

Variables / Data Columns

• Year: This column presents the data year from 2010 to 2021
• Median Household Income: Median household income, in 2022 inflation-adjusted dollars for the specific year
• YOY Change($): Change in median household income between the current and the previous year, in 2022 inflation-adjusted dollars
• YOY Change(%): Percent change in median household income between current and the previous year

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Hampshire median household income. You can refer the same here