This raster dataset represents the agricultural census data quality for cashew apple crop yields. Data quality categories include (0= missing, 0.25= county level census data, 0.5= interpolated with census data from within 2 degrees of latitude/longitude, 0.75= state level census data, 1= country level census data). Croplands cover ~15 million km2 of the planet and provide the bulk of the food and fiber essential to human well-being. Most global land cover datasets from satelites group croplands into just a few categories, thereby excluding information that is critical for answering key questions ranging from biodiversity conservation to food security to biogeochemical cycling. Information about agricultural land use practices like crop selection, yield, and fertilizer use is even more limited.Here we present land use data sets created by combining national, state, and county level census statistics with a recently updated global data set of croplands on a 5 minute by 5 minute (~10km x 10 km) latitude/longitude grid. Temporal resolution: Year 2000- based of average of census data between 1997-2003.

This dataset was produced as part of the Land Use Opportunities: Whitiwhiti Ora research programme funded by the Our Land and Water National Science Challenge. Further information about this layer and links to download the data, can be found at the Whitiwhiti Ora Data Supermarket.

N.B. The information provided here is not sufficiently accurate for detailed farm-scale use.

Suitability is based on consideration of multiple suitability criteria, and expressed as a score from 0 (totally unsuitable) to 1 (perfectly suited with no limitations with respect to any criteria). Potential yield was estimated as a theoretical maximum (based on the published literature) weighted by suitability scores for suitability criteria directly related to productivity, and is an estimate of production when climate and land limitations are not mitigated. Date: May 2023 Owner: MPI Contact: Kumar Vetharaniam, Plant and Food Research

This shapefile contains boundaries representing the Town of Apple Valley City Council Districts for the purpose of establishing election divisions within a district. This dataset should only be used for the purpose of establishing election divisions within a district. It will be removed once the redistricting process has concluded.To download:1. Click the Download button above.2. A side panel will appear showing download options. Under Shapefile, click the Download button.3. When the download completes, browse to the location of the downloaded .zip, copy it to the location where you manage your redistricting files, then right-click to extract the contents. You will then be able to use the file in GIS software.If, rather than downloading the data, you wish the reference online versions of these datasets directly to ensure you are always using the most up-to-date data, please contact the County of San Bernardino Innovation and Technology Departments at 909-884-4884 or by emailing OpenData@isd.sbcounty.gov for informations and instructions for doing so.

The Digital City Map (DCM) data represents street lines and other features shown on the City Map, which is the official street map of the City of New York. The City Map consists of 5 different sets of maps, one for each borough, totaling over 8000 individual paper maps. The DCM datasets were created in an ongoing effort to digitize official street records and bring them together with other street information to make them easily accessible to the public. The Digital City Map (DCM) is comprised of seven datasets; Digital City Map, Street Center Line, City Map Alterations, Arterial Highways and Major Streets, Street Name Changes (areas), Street Name Changes (lines), and Street Name Changes (points).

All of the Digital City Map (DCM) datasets are featured on the Streets App

All previously released versions of this data are available at BYTES of the BIG APPLE- Archive

The US Geological Survey, in cooperation with the National Park Service, mapped 35 7.5-minute quadrangles, within a 2-mile-wide+ corridor centered on the Parkway, from BLRI (Blue Ridge Parkway) Mile Post (MP) 0 near Afton, Virginia southward to MP 218 at Cumberland Knob, approximately 1.3 km south of the Virginia – North Carolina State Line. Detailed bedrock geologic mapping for this project was conducted at 1:24,000-scale by systematically traversing roads, trails, creeks, and ridges within and adjacent to the 2-mile-wide+ corridor along the 216.9-mile length of the BLRI in Virginia. Geologic data at more than 23,000 station points were collected during this project (September 2009 – February 2014), with approximately 19,500 included in the accompanying database. Station point geologic data collected included lithology, structural measurements (bedding, foliations, folds, lineations, etc), mineral resource information, and other important geologic observations. Station points at the start of this project (September 2009) were located in the field using topographic reckoning; after May 2012 stations were located using Topo Maps (latest version 1.12.1) for Apple IPad 2, model MC744LL/A. Since the start of the project, station point geologic data and locational metadata were recorded both in analog (field notebook and topographic field sheets) and digitally in ESRI ArcGIS (latest version ArcMAP 10.1). Station point geologic data were used to identify major map units, construct contact lines between map units, identify the nature of those contacts (igneous, stratigraphic or structural), determine contact convention control (exact – located in field to within 15 meters; approximate – located to within 60 meters; inferred – located greater than 60 meters), trace structural elements (faults, fold axes, etc) across the project area, and determine fault orientation and kinematics. Geologic line work was initially drafted in the field during the course of systematic detailed mapping; line editing occurred during office compilation in Adobe Illustrator (latest version CS 4). Final editing occurred during conversion and compilation of Illustrator line work into the ArcGIS database, where it was merged with station point geologic data. Station point geologic data, contacts and faults from previous work in the BLRI corridor were evaluated for compilation and synthesis in the BLRI mapping project. Station point geologic data compiled from previous work are referenced and marked with a “C” in the database. Compiled line work is also clearly tagged and referenced. The BLRI cuts at an oblique angle nearly the entire width of the Blue Ridge Geologic Province in Virginia. Thus, the geology varies significantly along it’s along its 216-mile traverse. North of Roanoke (BLRI MP 115), the Blue Ridge is defined as an orogen-scale, northwest-vergent, northeast-plunging reclined anticlinorium, and from its start at MP 0 near Afton, Virginia, southward to Roanoke, the BLRI traverses the western limb of this structure. Here, rocks range in age from Mesoproterozoic to Cambrian: Mesoproterozoic orthogneisses and metamorphosed granitoid rocks of the Shenandoah massif comprise “basement” to Neoproterozoic to Cambrian mildy- to non-metamorphosed to sedimentary “cover” rocks; the BLRI crisscrosses in many places the contact between cover and basement. Mesoproterozoic basement rocks in the Shenandoah massif represent the original crust of the Laurentian (ancestral North American) continent; sedimentary cover rocks were deposited directly on this crust during extension and breakup of the Rodinian supercontinent in the Neoproterozoic to earliest Cambrian. Very locally, diabase dikes of earliest Jurassic age intrude older basement and cover sequences. These dikes were emplaced in the Blue Ridge during continental extension (rifting) and the opening of the Atlantic Ocean in the Mesozoic Era. From MP 103.3 to MP 110.3 near Roanoke, the BLRI crosses into and out of a part of the Valley and Ridge Geologic Province. Unmetamorphosed sedimentary rocks of Cambrian to Ordovician age – mostly shale, siltstone and carbonate – occur here. These rocks were deposited in a terrestrial to shallow marine environment on the Laurentian continental margin, after extensional breakup of Rodinian supercontinent in the Neoproterozoic and earliest Cambrian, but before mid- to late-Paleozoic orogenesis. South of Roanoke, the Blue Ridge Geologic Province quickly transitions from an anticlinorium to a stack of imbricated thrust sheets. After crossing the southern end of the Shenandoah Mesoproterozoic basement massif (MP 124.1 to MP 144.4), the BLRI enters the eastern Blue Ridge province, a fault-bounded geologic terrane comprised of high-metamorphic-grade sedimentary and volcanic rocks deposited east of the Laurentian continental margin from the Neoproterozoic to early Paleozoic. These rocks were significantly metamorphosed, deformed, and transported westward onto the Laurentian margin along major orogenic faults during Paleozoic orogenesis. Sixty bedrock map units underlie the BLRI in Virginia. These units consist of one or more distinguishing lithologies (rock types), and are grouped into formal and informal hierarchal frameworks based on age, stratigraphy (formations-groups), and tectonogenesis. Many of these units exhibit characteristics and field relationships that are critical to our understanding of Appalachian orogenesis. Most of these units are named based on the dominant occurring lithology; other units follow formal nomenclature, some of which was developed and has been used for more than 100 years. Oldest rocks occurring along the BLRI corridor are Mesoproterozoic orthopyroxene-bearing basement rocks of the Shenandoah massif, in the core of the Blue Ridge anticlinorium. Preliminary SHRIMP U-Pb zircon geochronology (J. N. Aleinikoff, this study) shows that these rocks can be grouped based on crystallization ages: Group I (~1.2 to 1.14 Ga) are strongly foliated orthogneisses and Group II (~1.06 to 1.0 Ga) are less deformed metagranitoids. Group I orthogneisses, which occur discontinuously from near Irish Gap (MP 37) to Cahas Overlook (MP 139), comprise 10 map units: leucogranitic gneiss (Yllg); megacrystic quartz-monzonitic gneiss (Yqg); granitic gneiss (Yg); lineated granitoid gneiss (Ylgg); garnetiferous leucogneiss (Yglg); Sandy Creek gneiss (Ysg); porphyroblastic garnet-biotite leucogranitic gneiss (Ygtg); dioritic gneiss (Ydg); Pilot gneiss (Ypg); and megacrystic granodioritic gneiss (Ygg). Group II metagranitoids, which are first encountered along the BLRI at Reeds Gap (MP 14) and occur discontinuously to Roanoke River Overlook (MP 115), comprise 8 map units: megacrystic meta-quartz monzonitoid (Yqm); massive metagranitoid (Ymgm); megacrystic metagranitoid (Ypgm); mesocratic porphyritic metagranitoid (Ygpm); metagranodioritoid (Ygdm); Vesuvius megaporphyritic metagranitoid (Yvm); quartz-feldspar leucogranitoid (Yqfm); and Peaks of Otter metagranitoid (Ypom). An additional relatively undeformed metagranitoid with a preliminary SHRIMP U-Pb zircon age of ~1.12 Ga is assigned to the Bottom Creek Suite (Ybcm), and well layered migmatitic gneiss (Ymg) near Irish Gap (MP 37) has a a preliminary SHRIMP U-Pb zircon age of ~1.05 Ga. Other rocks of Mesoproterozoic age include orthogneisses in the Fries thrust sheet between MP 139 and MP 144.5 that range in age from ~1.19 to ~1.07 Ga: biotite-muscovite leucogneiss (Ymlg); biotite granitic augen gneiss (Ybgg); blue-quartz gneiss (Ybqg); and biotite leucogneiss (Yblg). Latest Mesoproterozoic rocks include paragneiss and pegmatite (Yprg) near Porters Mountain Overlook (MP 90), and a suite of igneous intrusive nelsonites and jotunites (Yjn). Two units, foliated metagreenstone (Zdm) and foliated metagranitoid (Zgm), locally intrude older Mesoproterozoic rocks in the core of the Blue Ridge anticlinorium. Metagreenstone is fine-grained and mafic in composition, and occur as narrow dikes and sills; metagranitoid is medium-grained and generally felsic in composition, and intrude basement rocks as small plutons, stocks, and a few narrow dikes. On the west limb of the Blue Ridge anticlinorium, metamorphosed sedimentary and volcanic rocks of Neoproterozoic to Cambrian age crop out discontinuously along the BLRI from near Afton (MP 0) to MP 103.3, in the vicinity Roanoke Mountain (MP 120 to MP 124), to near Adney Gap (MP 136). These rocks are assigned to a formal stratigraphic sequence: Swift Run Formation; Catoctin Formation; Chilhowee Group. Metasedimentary and meta-igneous rocks of lower Paleozoic (?) to Neoproterozoic age are assigned to the Alligator Back Formation, Lynchburg Group, and Ashe Formation. These units crop out southeast of the Red Valley fault from MP 144.5 southwestward to the North Carolina–Virginia State Line at Mile Post 216.9. Rocks assigned to the Alligator Back crop out in the Blue Ridge Parkway corridor from Mile Post 174.5 southward to the North Carolina–Virginia State Line: compositional-layered biotite-muscovite gneiss (abg); garnet-biotite-muscovite-quartz schist (abs); quartzite and quartz-rich metasandstone (abq); and marble (abm). The following lithologic map units along the BLRI corridor are correlated with Lynchburg Group formations: graphitic schist (lgs), muscovite-biotite metagraywacke (lmg), and graphite-muscovite-quartz metasandstone (lms). These rocks crop out between the Red Valley fault (Mile Post 144.5) and the Rock Castle Creek fault (Mile Post 174.5). Coarse-grained- to conglomeratic metagraywacke (acm), underlying Lynchburg Group rocks west of the Rock Castle Creek fault in the vicinity of Rakes Millpond (MP 162.3) and Rocky Knob Visitors Center (MP 169), are considered to be the lower metamorphic grade-equivalent of the higher metamorphic-grade Ashe Formation at its type section in northwestern North Carolina. Five meta-igneous lithologic map units

Germany Location-based Services Market size was valued at USD 4.6 Billion in 2024 and is projected to reach USD 12.3 Billion by 2032, growing at a CAGR of 13 % from 2026 to 2032.

Germany Location-based Services Market Drivers

Germany boasts a high smartphone penetration rate and widespread access to mobile internet. This provides a vast user base readily equipped to utilize LBS applications and services.

The increasing adoption of faster mobile networks (4G LTE and 5G) further enhances the user experience and enables more data-intensive LBS applications.

Personal Navigation: Consumers heavily rely on LBS for real-time navigation, traffic updates, and finding points of interest (POIs) through apps like Google Maps, Apple Maps, and local navigation solutions.

In-Car Navigation Systems: Integrated navigation systems in vehicles, often enhanced with real-time traffic and POI data powered by LBS, remain popular.

Location-Based Advertising: Retailers and advertisers are leveraging LBS to deliver targeted advertisements, promotions, and personalized offers to consumers based on their real-time location and proximity to stores or specific products.

Shapefile of zoning section map index, grid to determine which zoning section map relates to specific areas of NYC.

A sectional index grid to determine which Zoning Map refers to specific areas of New York City. Zoning maps show the boundaries of zoning districts throughout the city. The maps are regularly updated after the City Planning Commission and the City Council have approved proposed zoning changes. The set of 126 maps, which are part of the Zoning Resolution, are displayed in 35 sections. Each section is identified by a number from 1 to 35. Each map covers an area of approximately 8,000 feet (north/south) by 12,500 feet (east/west).

All previously released versions of this data are available at BYTES of the BIG APPLE- Archive

Splitgraph serves as an HTTP API that lets you run SQL queries directly on this data to power Web applications. For example:

See the Splitgraph documentation for more information.

GIS data: Community Districts (Water areas included)

Community Districts are mandated by the city charter to review and monitor quality of life issues for New York City (NYC) neighborhoods. NYC is currently comprised of 59 community districts. The first byte is a borough code and the second and third bytes are the community district number. There are also 12 Joint Interest Areas (JIAs). The JIAs are major parks and airports and are not contained within any community district. This dataset is being provided by the Department of City Planning (DCP) for informational purposes only. DCP does not warranty the completeness, accuracy, content, or fitness for any particular purpose or use of the dataset, nor are any such warranties to be implied or inferred with respect to the dataset as furnished on the website. DCP and the City are not liable for any deficiencies in the completeness, accuracy, content, or fitness for any particular purpose or use the dataset, or applications utilizing the dataset, provided by any third party.

All previously released versions of this data are available at BYTES of the BIG APPLE- Archive

Introduction

This dataset contains multiple test results conducted for the paper "Characterization of the iPhone LiDAR Sensor for Vibration Measurement and Modal Analysis".

Data Information

This dataset consists of displacement readings collected by a laser displacement transducer (L) and/or a light detection and ranging (LiDAR) sensor from an Apple iPhone 13 Pro. The LiDAR data was collected using two different apps: Stray Scanner (SS) returns full depth maps and PhyPhox collects depth at a specific coordinate. Two different structures were used as targets for the tests: a stiff plate, simulating rigid body movement, and a steel cantilever with four expected mode shapes within a low (> 60 Hz) frequency range. Tests consist of the targets being static, oscillating harmonically in a single frequency, or randomly as a response of a pre-defined spectrum. The oscillation tests were carried out with the aid of an air-bearing shaker.

Further details

Additional test details can be found on the README files along with the dataset. A MATLAB function to load specific test cases is also provided.

As global communities responded to COVID-19, we heard from public health officials that the same type of aggregated, anonymized insights we use in products such as Google Maps would be helpful as they made critical decisions to combat COVID-19. These Community Mobility Reports aimed to provide insights into what changed in response to policies aimed at combating COVID-19. The reports charted movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential.

Extensive land use and geographic data at the tax lot level in GIS format (ESRI Shapefile). Contains more than seventy fields derived from data maintained by city agencies, merged with tax lot features from the Department of Finance’s Digital Tax Map, clipped to the shoreline.

All previously released versions of this data are available at BYTES of the BIG APPLE- Archive