Multibeam backscatter imagery extracted from gridded bathymetry for selected U.S. locations in the Pacific. The backscatter datasets include data collected using the RESON 8101ER multibeam sonar, Kongsberg 300 kHz EM3002D multibeam sonar, and a Kongsberg 30 kHz EM300 multibeam sonar. Data are available in GeoTIFF and NetCDF format as well as composite maps (jpg or PDF) which show all available data for a region. Please see the individual metadata records for additional information about a specific location.

GapMaps Live is an easy-to-use location intelligence platform available across 25 countries globally that allows you to visualise your own store data, combined with the latest demographic, economic and population movement intel right down to the micro level so you can make faster, smarter and surer decisions when planning your network growth strategy.

With one single login, you can access the latest estimates on resident and worker populations, census metrics (eg. age, income, ethnicity), consuming class, retail spend insights and point-of-interest data across a range of categories including fast food, cafe, fitness, supermarket/grocery and more.

Some of the world's biggest brands including McDonalds, Subway, Burger King, Anytime Fitness and Dominos use GapMaps Live as a vital strategic tool where business success relies on up-to-date, easy to understand, location intel that can power business case validation and drive rapid decision making.

Primary Use Cases for GapMaps Live includes:

1. Retail Site Selection - Identify optimal locations for future expansion and benchmark performance across existing locations.
2. Customer Profiling: get a detailed understanding of the demographic profile of your customers and where to find more of them.
3. Analyse your catchment areas at a granular grid levels using all the key metrics
4. Target Marketing: Develop effective marketing strategies to acquire more customers.
5. Marketing / Advertising (Billboards/OOH, Marketing Agencies, Indoor Screens)
6. Customer Profiling
7. Target Marketing
8. Market Share Analysis

Some of features our clients love about GapMaps Live include: - View business locations, competitor locations, demographic, economic and social data around your business or selected location - Understand consumer visitation patterns (“where from” and “where to”), frequency of visits, dwell time of visits, profiles of consumers and much more. - Save searched locations and drop pins - Turn on/off all location listings by category - View and filter data by metadata tags, for example hours of operation, contact details, services provided - Combine public data in GapMaps with views of private data Layers - View data in layers to understand impact of different data Sources - Share maps with teams - Generate demographic reports and comparative analyses on different locations based on drive time, walk time or radius. - Access multiple countries and brands with a single logon - Access multiple brands under a parent login - Capture field data such as photos, notes and documents using GapMaps Connect and integrate with GapMaps Live to get detailed insights on existing and proposed store locations.

Unacast Location Data enables privacy-friendly analysis of human movement in the U.S.

Location data enables users to answer complex questions related to human mobility on a large scale. Enter your polygonal geofence coordinates (geoJSON format) or pseudonymized registration IDs, and select a time range. Based on your query, the API will deliver merged, processed, and deduplicated location data that is fully annotated with Forensic Flags, allowing you to choose only signals that meet your accuracy criteria.

Companies use Location Data for: - Product development - Advertising and marketing - Audience creation - Fraud detection - Predictive analysis - Path analysis - Business intelligence - Market analysis

Location data can be used in many different ways to understand changes in human movement across different areas, predict future human mobility trends, and inform operational and marketing strategies.

Unlike other providers, Unacast does not share polygons or metadata for sensitive locations. This helps to ensure that visits to privacy-sensitive locations remain private and that organizations do not take unnecessary risks in their analysis.

Unacast's API data can be delivered right away by direct response or exported into an AWS S3.

Learn more at https://www.unacast.com/products/location-data.

This dataset contains the approximate location of 59 wetlands that were monitored as part of the U.S. Geological Survey (USGS) Amphibian Research and Monitoring Initiative (ARMI). Note, these were preliminary points used for locating the wetlands in the field and they may not fall directly within a wetlands boundary. The later surveying of pond boundaries provides more accurate locations. These point locations were collected with a Garmin GPSmap62 unit. The mention of firm, product, or trade names is done so for informative purposes only and does not constitute and recommendation or endorsement by the federal government.

Provides details on the sites selected for each study, including various attributes to allow for comparison across sites. ------------------------------------------ The City of Seattle Department of Transportation (SDOT) is providing data from the public life studies it has conducted since 2017. These studies consist of measuring the number of people using public space and the types of activities present on select sidewalks across the city, as well as several parks and plazas. The data set is continually updated as SDOT and other parties conduct public life studies using Gehl Institute’s Public Life Data Protocol. This dataset consists of four component spreadsheets and a GeoJSON file, which provide public life data as well as information about the study design and study locations: 1 Public Life Study: provides details on the different studies that have been conducted, including project information. https://data.seattle.gov/Transportation/Public-Life-Data-Study/7qru-sdcp 2 Public Life Location: provides details on the sites selected for each study, including various attributes to allow for comparison across sites. 3 Public Life People Moving: provides data on people moving through space, including total number observed, gender breakdown, group size, and age groups. https://data.seattle.gov/Transportation/Public-Life-Data-People-Moving/7rx6-5pgd 4 Public Life People Staying: provides data on people staying still in the space, including total number observed, demographic data, group size, postures, and activities. https://data.seattle.gov/Transportation/Public-Life-Data-People-Staying/5mzj-4rtf 5 Public Life Geography: A GeoJSON file with polygons of every location studied. https://data.seattle.gov/Transportation/Public-Life-Data-Geography/v4q3-5hvp Please download and refer to the Public Life metadata document - in the attachment section below - for comprehensive information about all of the Public Life datasets.

According to a survey conducted among warehouse occupiers in the Asia-Pacific region in 2021, proximity to markets and customers was the main factor in choosing the location of logistics facilities, with 67 percent of the respondents selecting it as one of their top three factors.

These data are depth contours (isobaths) derived at 50 meters for most islands and reefs in the Mariana Archipelago, American Samoa, and the Pacific Remote Island Areas. Contours at 10- or 20-meter depths have also been derived for a subset of the same locations. These contours are derived from bathymetry sources including multibeam data collected by Coral Reef Ecosystem Program (CREP) at the NOAA Pacific Islands Fisheries Science Center (PIFSC) since 2003, NOAA nautical charts, estimated depths derived from satellite images, and other sources of bathymetry collected by various agencies and entities.

In 2021, around 76 percent of suicides among females in the United States were committed in a home or apartment. This statistic depicts the distribution of U.S. suicides committed in select locations in 2021, by gender.

In a survey conducted in 2019 in the Asia Pacific region, regarding the important factors taken into consideration while selecting a university degree, 38 percent of the respondents from Beijing stated that the university location was one of the most important factors in choosing a university degree. Comparatively, 22 percent of respondents from Kuala Lumpur stated the university location was one of their most important factors when it came to choosing a university degree in 2019.

Scouring of streambed material surrounding bridge structures is a leading cause of bridge failure in the United States. Damages resulting from bridge failure oftentimes lead to financial burdens and loss of life. To date, there has been no comprehensive evaluation of the current (2016) effectiveness of the guidance or overall long-term performance of bridge-scour countermeasures provided in the Federal Highway Administration (FHWA), Hydraulic Engineering Circular No. 23, Bridge Scour and Stream Instability Countermeasures. To that end, the U.S. Geological Survey (USGS), in cooperation with the Federal Highway Administration, obtained bathymetric, topographical, and other data at 20 sites across the United States to begin an evaluation of the effectiveness of bridge-scour countermeasures. This data release contains the supplemental bathymetric and topographic data for Dudunake and others (2018).

These data are measurements of sediment depth in the downstream approach channel of Brandon Rd Lock and Dam at Joliet, Illinois, on February 13-14, 2017. Data collection software recorded and stored the horizontal position of the vessel and the measured sediment depth. Data processing required computer software to extract position data from the target data files and to summarize and map the information.

This statistic shows the share of consumers that purchased liquor from select retailers or outlets as of 2018. As of 2018, 20 percent of liquor consumers made purchases at Walmart stores. Comparatively, 16 percent of consumers made liquor purchases at Costco.

A database of environmental input parameters for River Invertebrate Prediction and Classification System (RIVPACS Model 44) implemented in a new version of the River Invertebrate Classification Tool (RICT).

The model predicts the invertebrate biological communities (species composition, abundance and value of biotic indices) at any site if its environmental quality was minimally impacted by people.

The database contains abiotic environmental parameters from geographical information systems for the river network of Great Britain on a 50 m grid based on the UK Centre for Ecology and Hydrology (CEH) Intelligent River Network. It includes the start and end location of the river segment on the Intelligent River Network on a 50m grid so that users can identify the river segment for which they want data.

The data is delivered to users from an online GIS system that allows them to select a location by Ordnance Survey grid reference, select an area and extract data for up to 9 river segments within that area.

For user documentation and guidance please see the link to RICT user documentation in the data resources available below.

Welcome to the City of St. Augustine's interactive Utility Service Area web map application. You can search for the property you are interested in by typing in the address in the location query or manually by zooming into your area of interest. Parcels are viewable when searching for an address or by zooming into the street level. You can change the underlying basemap using the basemap tab below the location query. There is a measurement tab located below the location query. This web map application has print capability as well. By selecting the print icon below the location query, you can select the desired format as well, i.e. jpeg, pdf, ect. You can give the document a name by selecting the "advanced options" button. Select "print" and the app will produce the map in the given layout and format.

When choosing the location for building a house, the most important aspects were the neighborhood and price of the land in Poland in 2020.

Abstract

This dataset is derived from GA TOPO 250K Series 3 features clipped to the BA_SYD and environs extent for the purpose of providing geographic context in BA_SYD report map images. The source datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

Selected features currently include:

Lakes

PlaceNames\*

PopulatedPlaces

Railways

Roads

WatercourseLines

additional features may be included as required (relevant feature classes asterisked).

Currently the only addition has been to PlaceNames with the addition of Census Spring (see Lineage).

Purpose

providing geographic context in BA_SYD report map images.

Dataset History

A rectangular mask polygon feature was manually drawn around the BA_SYD (ie NSB+SSB) boundary extending approximately 100km beyond the BA_SYD extent. This mask is included in the dataset (SYD_clip).

Selected features from the national GEODATA TOPO 250K series 3 were overlaid with the mask and intersecting features extracted.

Extracted feature classes have the same names as the source features.

The additional feature of "Census Spring" was added to place names. It's approximate location was sourced from

Fig 4, p172 of the document :

Duralie Coal (2013) Duralie Coal Mine - Water Management Plan (Document No. WAMP-R02-D) Appendix 3 - Groundwater Management Plan . September 2013 Document No. GWMP-R02-C (00519574) . Fig4 pp13

http://www.gloucestercoal.com.au/documents/community_environment/duralie/Duralie_Coal_Mine_Water_Management_Plan.pdf

Dataset Citation

Bioregional Assessment Programme (2014) BA SYD selected GA TOPO 250K data plus added map features. Bioregional Assessment Derived Dataset. Viewed 13 March 2019, http://data.bioregionalassessments.gov.au/dataset/ba5feac2-b35a-4611-82da-5b6213777069.

Dataset Ancestors

• Derived From GEODATA TOPO 250K Series 3

This is a complete list of all Sleep Number by Select Comfort locations along with their geographic coordinate. Select Comfort (NASDAQ: SCSS) is a U.S.-based manufacturer that makes the Sleep Number beds as well as foundations and bedding accessories. The company is based in Plymouth, Minnesota. In addition to its Minnesota headquarters, Select Comfort has manufacturing and distribution facilities in South Carolina and Utah. The data includes phone numbers and store hours for each location.

Report of the number of clients connected to public wifi locations in San Mateo County. Data includes the amount of data sent and received by each user connected to the network. This data contains reports for 3 public wifi locations: Coastside Hope, Lan Honda Puente Center, and Lincoln Community Center. Public wifi usage data for other sites in San Mateo County can be found here: https://data.smcgov.org/Government/Public-Wifi-Use-Over-Time/dsfi-fpdz

Pick 'n Save is a Wisconsin-based grocery chain owned by Kroger that aims to provide a balance of value and variety. Pick 'n Save’s business model centers around offering competitive pricing on a wide selection of groceries, including fresh produce, meat, and local products, while also providing a full-service shopping experience with features like delis and sometimes pharmacies. You can download the complete list of key information about Pick 'n Save locations, contact details, services offered, and geographical coordinates, beneficial for various applications like store locators, business analysis, and targeted marketing. The Pick 'n Save data you can download includes:

Identification & Location:


  Store_name, store_type, store_name, address, city, state, zip_code, latitude, longitude, geo_accuracy, country_code, county,  


Contact Information:


  Phone_number, pharmacy_phone_number, website_address,


Operational Details & Services:


  Store_hours, pharmacy_hours,

Carbon-14 data in this file were compiled by W.F. Ruddiman and

 staff at the Lamont-Doherty Earth Observatory of Columbia University. Data include

 974 carbon-14 dates from 309 ocean sediment cores, covering the period from 40,000

 years bp to the present worldwide. Estimated error range is given. Also included are

 core identifier, latitude/longitude, water depth, depth in core, institutional

 source, laboratory number, and sediment fraction analyzed (total, bulk, or fine

 fraction). The LDEO C14 data were originally submitted to NOAA's National Geophysical

 Data Center (NGDC) for archive, but were subsequently transferred to NOAA's National

 Climatic Data Center (NCDC) Paleoclimatology Group for stewardship. The data are available for direct download from NCDC's Web

 server.