Address details and xy coordinates of all branches of libraries.

More information on how to access the data:

https://www.cbs.nl/en-en/our-services/custom-and-microdata/microdata-self-research

Methodology

Using address data (postal code, street, house number, addition) or otherwise the aerial photo and / or map data, x and y coordinates of the library location have been added for exact location determination.

Population

Libraries' offices and service points.

Counter Strike Map Dataset

This dataset consists of Counter Strike map images along with their corresponding labels and x-y coordinates. The dataset is suitable for image classification tasks and includes the necessary information for each image.

  Dataset Details

Total Images: [1424] Classes: [5] Image Size: [1920x1080] Format: [png]

  Files

The dataset includes the following files:

maps/train/: This folder contains the Counter Strike map images. The images are… See the full description on the dataset page: https://huggingface.co/datasets/HOXSEC/csgo-maps.

The Taipei City pedestrian fixed facilities related to the location data of box facilities include name, administrative district, XY coordinates, geometric location data type, and geometric position relative coordinates. The coordinate system adopted for this data is TWD97.

New Parking Citations dataset here: https://res1datad-o-tlacityd-o-torg.vcapture.xyz/Transportation/Parking-Citations/4f5p-udkv/about_data ---Archived as of September 2023--- Parking citations with latitude / longitude (XY) in US Feet coordinates according to the California State Plane Coordinate System - Zone 5 (https://res1wwwd-o-tconservationd-o-tcad-o-tgov.vcapture.xyz/cgs/rgm/state-plane-coordinate-system). For more information on Geographic vs Projected coordinate systems, read here: https://res1wwwd-o-tesrid-o-tcom.vcapture.xyz/arcgis-blog/products/arcgis-pro/mapping/gcs_vs_pcs/ For information on how to change map projections, read here: https://res1learnd-o-tarcgisd-o-tcom.vcapture.xyz/en/projects/make-a-web-map-without-web-mercator/

PLSS Townships and Sections dataset current as of 2008. Public Land Survey square-mile section boundaries within Sedgwick County. Layer was developed interactively by GIS staff. Primary attribues include section, township, and range identifiers, and x-y coordinates, and Public Safety (ortho) map numbers..

Map of DAS, nodal, vibroseis and Reftek stations during March 2016 deployment. The plot on the left has nodal stations labeled; the plot on the right has vibroseis observations labeled. Stations are shown in map-view using Brady's rotated X-Y coordinates with side plots denoting elevation with respect to the WGS84 ellipsoid. Blue circles denote vibroseis data, x symbols denote DAS (cyan for horizontal and magenta for vertical), black asterisks denote Reftek data, and red plus signs denote nodal data. This map can be found on UW-Madison's askja server at /PoroTomo/DATA/MAPS/Deployment_Stations.pdf

This data set provides a means of identifying an x-y coordinate for the approximate center (centroid) of landnet units based on the corresponding standardized PLSS description (e.g., for PLSS Section this is DTRS -- Direction, Township, Range, and Section codes). This process is sometimes referred to as "protraction". The Landnet centroid shapefile includes coordinates in WTM83/91 and latitude/longitude expressed as decimal degrees or degrees, minutes and seconds.

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. The primary legal divisions of most states are termed counties. In Louisiana, these divisions are known as parishes. In Alaska, which has no counties, the equivalent entities are the organized boroughs, city and boroughs, municipalities, and for the unorganized area, census areas. The latter are delineated cooperatively for statistical purposes by the State of Alaska and the Census Bureau. In four states (Maryland, Missouri, Nevada, and Virginia), there are one or more incorporated places that are independent of any county organization and thus constitute primary divisions of their states. These incorporated places are known as independent cities and are treated as equivalent entities for purposes of data presentation. The District of Columbia and Guam have no primary divisions, and each area is considered an equivalent entity for purposes of data presentation. The Census Bureau treats the following entities as equivalents of counties for purposes of data presentation: Municipios in Puerto Rico, Districts and Islands in American Samoa, Municipalities in the Commonwealth of the Northern Mariana Islands, and Islands in the U.S. Virgin Islands. The entire area of the United States, Puerto Rico, and the Island Areas is covered by counties or equivalent entities. The boundaries for counties and equivalent entities are as of January 1, 2017, primarily as reported through the Census Bureau's Boundary and Annexation Survey (BAS).

Dataset Summary About this data: This map shows the bike paths of all Pace rides in 2018 in the form of XY coordinate points. The NSC (Neighborhood Service Center) Quadrant feature layer lays underneath the point layer as to give a visual division of activity in each of the four quadrants of Rochester. Note: depending on the basemap you choose, you may have to zoom out and locate to Rochester. Dictionary: Latitude: The latitude location of the Pace BikeShare trip start (in degrees). Longitude: The longitude location of the Pace BikeShare trip start (in degrees). TripID: The unique identifier of a specific Pace BikeShare trip. Action: The state that the bike trip is in. Can have one of the following values: AccessCode: StartTrip: The start of the bike ride Unlock: The bike is unlocked Foreground: Note if the bike started ride Background: Note if bike is in active ride EndTrip: The bike has ended the trip Lock – The bike is locked UserID: The unique identifier of a specific Pace BikeShare user. Date: The date the bike ride occurred. Time: The time of the bike ride. Source: This data comes from the City of Rochester.

Snapshot of all Yield and Yield Ahead Signs in West Virginia as extracted by Mutcdname from an overall Sign Dataset. Datasets include RouteID, SignID, County Code, Route Numbered, Sub Route Number, Sign System, supplemental code, Supplemental Description, Direction, Milepoint, Number of Signs, Location, Mutcdname and Mutcode, Mutcdcat, Text, County, Photo URL, and XY Coordinates. Data is current as of 2015 and is updated as needed. Coordinate System: NAD_1983_UTM_Zone_17N

Idaho, USA has a high percentage of federally owned land (over 60%), strong gradients in elevation and latitude, diverse landscape types and uses, the third fastest growing population in the United States, and is one of the most agriculturally productive states in the county. Knowledge of how different biophysical and socioeconomic functional classes in Idaho are distributed and overlapping is of particular interest in this region, and the intersection of these landscapes describe a foundational aspect of the socio-economic system (SES) in that area. Contemporary interest in SES has spawned efforts to map SES boundaries, but these studies are few in number, and do not converge on a consensus approach.

We adapted aspects of previous studies to develop an improved methodology for mapping SES boundaries in Idaho. We performed a spatially explicit, nested Principal Component Analysis (PCA) on suites of biophysical and socio-economic data aggregated by 5 km grids, followed by a comparison of two common, but mathematically distinct clustering techniques, k-means and Agglomerative Hierarchical Clustering (AHC), to classify homogeneous functional classes across the state. To address the issue of non-independence inherent to spatial datasets, we included XY coordinates in the PCA, but removed them for score calculation, thereby holding spatial locations constant without explicitly including them in score-based clustering analyses.

Both K-means and AHC generated outputs with a high percent agreement between analogous numbers of clusters, although cluster evaluators did not converge on a single most likely number of clusters for either dataset, biophysical or socioeconomic, and the median evaluator score was used to select a most likely number of clusters. Generally, AHC resulted in a greater number of likely clusters than did k-means, thus providing better resolution - particularly in urban areas. Composite SES maps were created by overlapping the shared 5km grid geometry of the classified biophysical and socioeconomic landscape maps, and distinct SES domains emerged. We detected notable differences in management interpretations between the k-means and AHC composite SES maps, given a small difference in the number of landscape classes selected by clustering analysis.

This research is funded by the NSF Idaho EPSCoR Program and by the National Science Foundation under award number IIA-1301792. The research reported in this paper contributes to the Programme on Ecosystem Change and Society (www.pecs-science.org), and the EPSCoR Managing Idaho Landscape for Ecosystem Services iSEED Award, Towards ONEIdaho: An investigation of social-ecological system boundaries and domains across MILES sites. Special thanks to Drs. Danelle Larson and Donna Lybecker. We also acknowledge Idaho State University, where this research took place.

The area of the Ville in western Germany is of particular importance for studying anthropogenic induced relief changes, as it belongs to the largest and oldest historic lignite mining areas worldwide. Comparison of topographic data from the first geodetic mapping in 1893 to 2015 allows the quantification of relief changes in a completed example of a post-mining landscape. The dataset "Digital Elevation Model "Ville" from 1893" is computed based on the digitized contour lines of the historic map Preußische Neuaufnahme, which is the first geodetic mapping in the area. The DEM has a spatial resolution of 30 m. XY Coordinate System ETRS_1989_UTM_Zone_32N Linear Unit Meter (1,000000) Angular Unit Degree (0,0174532925199433) False_Easting 500000 False northing 0 Central_Meridian 9 Scale_Factor 0,9996 Datum D_ETRS_1989 Top 5651450 Left 333730 Right 352660 Bottom 5626700

Rates of confirmed COVID-19 in Ottawa Wards, excluding LTC and RH cases, and number of cases in LTCH and RH in Ottawa Wards. Data are provided for all cases (i.e. cumulative), cases reported within 30 days of the data pull (i.e. last 30 days), and cases reported within 14 days of the data pull (i.e. last 14 days). Based on the most up to date information available at 2pm from the COVID-19 Ottawa Database (The COD) on the day prior to publication.Rates of confirmed COVID-19 in Ottawa Wards, excluding LTC and RH cases, and number of cases in LTCH and RH in Ottawa Wards. Data are provided for all cases (i.e. cumulative), cases reported within 30 days of the data pull (i.e. last 30 days), and cases reported within 14 days of the data pull (i.e. last 14 days). Based on the most up to date information available at 2pm from the COVID-19 Ottawa Database (The COD) on the day prior to publication. You can see the map on Ottawa Public Health's website.Accuracy: Points of consideration for interpretation of the data:Data extracted by Ottawa Public Health at 2pm from the COVID-19 Ottawa Database (The COD) on May 12th, 2020. The COD is a dynamic disease reporting system that allow for continuous updates of case information. These data are a snapshot in time, reflect the most accurate information that OPH has at the time of reporting, and the numbers may differ from other sources. Cases are assigned to Ward geography based on their postal code and Statistics’ Canada’s enhanced postal code conversion file (PCCF+) released in January 2020. Most postal codes have multiple geographic coordinates linked to them. Thus, when available, postal codes were attributed to a XY coordinates based on the Single Link Identifier provided by Statistics’ Canada’s PCCF+. Otherwise, postal codes that fall within the municipal boundaries but whose SLI doesn’t, were attributed to the first XY coordinates within Ottawa listed in the PCCF+. For this reason, results for rural areas should be interpreted with caution as attribution to XY coordinates is less likely to be based on an SLI and rural postal codes typically encompass a much greater surface area than urban postal codes (e.i. greater variability in geographic attribution, less precision in geographic attribution). Population estimates are based on the 2016 Census. Rates calculated from very low case numbers are unstable and should be interpreted with caution. Low case counts have very wide 95% confidence intervals, which are the lower and upper limit within which the true rate lies 95% of the time. A narrow confidence interval leads to a more precise estimate and a wider confidence interval leads to a less precise estimate. In other words, rates calculated from very low case numbers fluctuate so much that we cannot use them to compare different areas or make predictions over time.Update Frequency: Biweekly Attributes:Ward Number – numberWard Name – textCumulative rate (per 100 000 population), excluding cases linked to outbreaks in LTCH and RH – cumulative number of residents with confirmed COVID-19 in a Ward, excluding those linked to outbreaks in LTCH and RH, divided by the total population of that WardCumulative number of cases, excluding cases linked to outbreaks in LTCH and RH - cumulative number of residents with confirmed COVID-19 in a Ward, excluding cases linked to outbreaks in LTCH and RHCumulative number of cases linked to outbreaks in LTCH and RH - Number of residents with confirmed COVID-19 linked to an outbreak in a long-term care home or retirement home by WardRate (per 100 000 population) in the last 30 days, excluding cases linked to outbreaks in LTCH and RH –number of residents with confirmed COVID-19 in a Ward reported in the 30 days prior to the data pull, excluding those linked to outbreaks in LTCH and RH, divided by the total population of that WardNumber of cases in the last 30 days, excluding cases linked to outbreaks in LTCH and RH - cumulative number of residents with confirmed COVID-19 in a Ward reported in the 30 days prior to the data pull, excluding cases linked to outbreaks in LTCH and RHNumber of cases in the last 30 days linked to outbreaks in LTCH and RH - Number of residents with confirmed COVID-19, reported in the 30 days prior to the data pull, linked to an outbreak in a long-term care home or retirement home by WardRate (per 100 000 population) in the last 14 days, excluding cases linked to outbreaks in LTCH and RH –number of residents with confirmed COVID-19 in a Ward reported in the 30 days prior to the data pull, excluding those linked to outbreaks in LTCH and RH, divided by the total population of that WardNumber of cases in the last 14 days, excluding cases linked to outbreaks in LTCH and RH - cumulative number of residents with confirmed COVID-19 in a Ward reported in the 30 days prior to the data pull, excluding cases linked to outbreaks in LTCH and RHContact: OPH Epidemiology Team

Two-dimensional coordinates for lines traced onto images of beaks.

• This is a .zip archive xy coordinates (250 files, .txt); and a list of specimen names (1 file, .csv).
• All images traced in FIJI.
• For each specimen, there is a trace of the beak rostrum and a separate trace of the beak bite surface.
• Each trace file should be a list of xy coordinates that ends at the beak tip. This must be checked/verified/corrected for all files before running any analyses! I recommend visual inspection by plotting each beak dataset as a scatterplot in a color spectrum (rainbow, etc.).
• These were traced over pixel images, so each file has a different number of xy coordinates (depending on the pixel resolution/image size that was traced).
• All bird specimen images were downloaded from Phenome10k.org
• All cephalopod specimens were traced from images published in:
  • Xavier, J. C. & Cherel, Y. 2009 Cephalopod beak guide for the Southern Ocean. British Antarctic Survey.

Loudoun County Parcel X,Y coordinates table. Available in Latitude and Longitude decimal degrees and Virginia State Plane North.

Two-dimensional coordinates for lines traced onto images of beaks.

This is a .zip archive xy coordinates (250 files, .txt); and a list of specimen names (1 file, .csv).

All images traced in FIJI.

For each specimen, there is a trace of the beak rostrum and a separate trace of the beak bite surface.

Each trace file should be a list of xy coordinates that ends at the beak tip. This must be checked/verified/corrected for all files before running any analyses! I recommend visual inspection by plotting each beak dataset as a scatterplot in a color spectrum (rainbow, etc.).

These were traced over pixel images, so each file has a different number of xy coordinates (depending on the pixel resolution/image size that was traced).

All bird specimen images were downloaded from Phenome10k.org

All cephalopod specimens were traced from images published in:

Xavier, J. C. & Cherel, Y. 2009 Cephalopod beak guide for the Southern Ocean. British Antarctic Survey.

Orthophotography of the Hauts-de-Seine department carried out in 2010 * * * * This orthophotography of the Hauts-de-Seine territory is the result of a shot made in winter 2010. The technical characteristics of this orthophotography are as follows: * Projection: RGF93-CC49/IGN69 * Resolution: 10 cm * Shooting period: 6 March 2010 * Format: JPEG Specific comments This vertical aerial view has been orthorectified, that is to say, the deformations related to the relief and perspective have been eliminated in order to propose an image superimposed on a map. This orthophotography shall be made available in the form of: * 1 km x 1 km georeferenced tiles * of “zip” files containing the tile in JPEG format and its associated georeferencing file * the syntax used for the naming of tiles: “ORT_AAAA_XXXX_YYYY”, uses the XY coordinates in RGF93-CC49 according to the Xmin_Ymax standard of the relevant slab * the download of a slab is done by clicking on the slab in the table or in the map and downloading the associated zip file Aerial shooting is also offered as a standardised map service (WMS). The areas prohibited from aerial shooting in the right-of-way of speech therapy have been blurred in accordance with the Order of 27 October 2017 establishing the list of these zones throughout France. Related data The Hauts-de-Seine Department offers you all of its aerial shots taken at different periods (from 1978 to today). Orhophotographs (HR: high resolution) produced on these occasions are freely available on the platform. With a very close resolution and high precision, these orthophotoplans form a coherent set allowing comparisons over time. In addition, the Department offers a web cartographic application dedicated to the discovery of this heritage of ortophotographs: Go back in time in the Hauts-de-Seine Access the Webapps Carto dedicated to orthophotos

A detailed vegetation map of a 120m by 28m study site was published by Rudolph (1963). A paper copy of the original maps of this research was obtained from archives at the University of Ohio.The map was digitised into a GIS layer and converted to meters. In the field, the plot was found because some of the marking pegs were still present on site and aerial photographs were used to locate points. GPS was used to determine the real world coordinates of the plot location. The site was remapped using a one metre square grid and change analysis undertaken using a GIS. Rudolph's map classifies the cover of mosses, lichens and algae into four classes: Heavy (40-90%), Patch (10-40%), Scattered (less than 10%) and none (0%). The combination of these classes was used to describe the vegetation in 2004. Within each one metre square the percentage cover of mosses, lichens and algae were recorded. The x,y distance of the cell centre from the north west corner of the plot was also recorded together with a description of the surface rock, wetness and percentage under snow. Vegetation change was able to be compared between 1962 and 2004. The changes in relation to the physical characteristics of the surface of the plot, such as rock type, wetness and slope were analysed. The data was converted to a Dbase file and then imported to a GIS point layer using the xy location as the geographical coordinates. The vegetation was also described using relevee measurements to determine cover of vegetation. The grid was 20 x 10 cm (200 point relevee) and analysed to determine species association. The 2004 map was compared with the 1962 map with statistics generated that describe the change.

Orthophotography of the Hauts-de-Seine department carried out in 2018 * * * * This orthophotography of the Hauts-de-Seine territory is the result of a shot made in 2018. The technical characteristics of this orthophotography are as follows: * Projection: RGF93-CC49/IGN69 * Resolution: 8 cm * Shooting period: 4-6 May 2018 * Format: JPEG Specific comments This vertical aerial view has been orthorectified, that is to say, the deformations related to the relief and perspective have been eliminated in order to propose an image superimposed on a map. This orthophotography shall be made available in the form of: * 1 km x 1 km georeferenced tiles * of “zip” files containing the tile in JPEG format and its associated georeferencing file * the syntax used for the naming of tiles: “ORT_AAAA_XXXX_YYYY”, uses the XY coordinates in RGF93-CC49 according to the Xmin_Ymax standard of the relevant slab * the download of a slab is done by clicking on the slab in the table or in the map and downloading the associated zip file Aerial shooting is also offered as a standardised map service (WMS). The areas prohibited from aerial shooting in the right-of-way of speech therapy have been blurred in accordance with the Order of 27 October 2017 establishing the list of these zones throughout France. Related data The Hauts-de-Seine Department offers you all of its aerial shots taken at different periods (from 1978 to today). Orhophotographs (HR: high resolution) produced on these occasions are freely available on the platform. With a very close resolution and high precision, these orthophotoplans form a coherent set allowing comparisons over time. In addition, the Department offers a web cartographic application dedicated to the discovery of this heritage of ortophotographs: Go back in time in the Hauts-de-Seine Access the Webapps Carto dedicated to orthophotos

Orthophotography of the Hauts-de-Seine department carried out in 2013 * * * * This orthophotography of the Hauts-de-Seine territory is the result of a photograph taken in the summer of 2013. The technical characteristics of this orthophotography are as follows: * Projection: RGF93-CC49/IGN69 * Resolution: 6 cm * Shooting period: June and September 2013 * Format: JPEG Specific comments This vertical aerial view has been orthorectified, that is to say, the deformations related to the relief and perspective have been eliminated in order to propose an image superimposed on a map. This orthophotography shall be made available in the form of: * 1 km x 1 km georeferenced tiles * of “zip” files containing the tile in JPEG format and its associated georeferencing file * the syntax used for the naming of tiles: “ORT_AAAA_XXXX_YYYY”, uses the XY coordinates in RGF93-CC49 according to the Xmin_Ymax standard of the relevant slab * the download of a slab is done by clicking on the slab in the table or in the map and downloading the associated zip file Aerial shooting is also offered as a standardised map service (WMS). The areas prohibited from aerial shooting in the right-of-way of speech therapy have been blurred in accordance with the Order of 27 October 2017 establishing the list of these zones throughout France. Related data The Hauts-de-Seine Department offers you all of its aerial shots taken at different periods (from 1978 to today). Orhophotographs (HR: high resolution) produced on these occasions are freely available on the platform. With a very close resolution and high precision, these orthophotoplans form a coherent set allowing comparisons over time. In addition, the Department offers a web cartographic application dedicated to the discovery of this heritage of ortophotographs: Go back in time in the Hauts-de-Seine Access the Webapps Carto dedicated to orthophotos