MAPS – standing for MIDI Aligned Piano Sounds – is a database of MIDI-annotated piano recordings. MAPS has been designed in order to be released in the music information retrieval research community, especially for the development and the evaluation of algorithms for single-pitch or multipitch estimation and automatic transcription of music. It is composed by isolated notes, random-pitch chords, usual musical chords and pieces of music. The database provides a large amount of sounds obtained in various recording conditions.

The MAPS dataset is one of the most used benchmark dataset for automatic music transcription. We propose here an updated version of the ground truth MIDI files, containing, on top of the original pitch, onset and offsets, additional annotations.

The annotations include:

• Tempo curve

• Time signature

• Durations of notes in fraction of a quarter note (some of them are approximate)

• Key signature (always written as the major relative)

• Sustain pedal activation

• Separate left and right hand staff

• Text annotations from the score (tempo indications, coda...).

If you use these annotations in a published research project, please cite:
Adrien Ycart and Emmanouil Benetos. “A-MAPS: Augmented MAPS Dataset with Rhythm and Key Annotations” 19th International Society for Music Information Retrieval Conference Late Breaking and Demo Papers, September 2018, Paris, France.

More information is available at: http://c4dm.eecs.qmul.ac.uk/ycart/a-maps.html

This layer features special areas of interest (AOIs) that have been contributed to Esri Community Maps using the new Community Maps Editor app. The data that is accepted by Esri will be included in selected Esri basemaps, including our suite of Esri Vector Basemaps, and made available through this layer to export and use offline. Export DataThe contributed data is also available for contributors and other users to export (or extract) and re-use for their own purposes. Users can export the full layer from the ArcGIS Online item details page by clicking the Export Data button and selecting one of the supported formats (e.g. shapefile, or file geodatabase (FGDB)). User can extract selected layers for an area of interest by opening in Map Viewer, clicking the Analysis button, viewing the Manage Data tools, and using the Extract Data tool. To display this data with proper symbology and metadata in ArcGIS Pro, you can download and use this layer file.Data UsageThe data contributed through the Community Maps Editor app is primarily intended for use in the Esri Basemaps. Esri staff will periodically (e.g. weekly) review the contents of the contributed data and either accept or reject the data for use in the basemaps. Accepted features will be added to the Esri basemaps in a subsequent update and will remain in the app for the contributor or others to edit over time. Rejected features will be removed from the app.Esri Community Maps Contributors and other ArcGIS Online users can download accepted features from this layer for their internal use or map publishing, subject to the terms of use below.

This digital data release presents contour data from multiple subsurface geologic horizons as presented in previously published summaries of the regional subsurface configuration of the Michigan and Illinois Basins. The original maps that served as the source of the digital data within this geodatabase are from the Geological Society of America’s Decade of North American Geology project series, “The Geology of North America” volume D-2, chapter 13 “The Michigan Basin” and chapter 14 “Illinois Basin Region”. Contour maps in the original published chapters were generated from geophysical well logs (generally gamma-ray) and adapted from previously published contour maps. The published contour maps illustrated the distribution sedimentary strata within the Illinois and Michigan Basin in the context of the broad 1st order supercycles of L.L. Sloss including the Sauk, Tippecanoe, Kaskaskia, Absaroka, Zuni, and Tejas supersequences. Because these maps represent time-transgressive surfaces, contours frequently delineate the composite of multiple named sedimentary formations at once. Structure contour maps on the top of the Precambrian basement surface in both the Michigan and Illinois basins illustrate the general structural geometry which undergirds the sedimentary cover. Isopach maps of the Sauk 2 and 3, Tippecanoe 1 and 2, Kaskaskia 1 and 2, Absaroka, and Zuni sequences illustrate the broad distribution of sedimentary units in the Michigan Basin, as do isopach maps of the Sauk, Upper Sauk, Tippecanoe 1 and 2, Lower Kaskaskia 1, Upper Kaskaskia 1-Lower Kaskaskia 2, Kaskaskia 2, and Absaroka supersequences in the Illinois Basins. Isopach contours and structure contours were formatted and attributed as GIS data sets for use in digital form as part of U.S. Geological Survey’s ongoing effort to inventory, catalog, and release subsurface geologic data in geospatial form. This effort is part of a broad directive to develop 2D and 3D geologic information at detailed, national, and continental scales. This data approximates, but does not strictly follow the USGS National Cooperative Geologic Mapping Program's GeMS data structure schema for geologic maps. Structure contour lines and isopach contours for each supersequence are stored within separate “IsoValueLine” feature classes. These are distributed within a geographic information system geodatabase and are also saved as shapefiles. Contour data is provided in both feet and meters to maintain consistency with the original publication and for ease of use. Nonspatial tables define the data sources used, define terms used in the dataset, and describe the geologic units referenced herein. A tabular data dictionary describes the entity and attribute information for all attributes of the geospatial data and accompanying nonspatial tables.

Produced collectively by tsunami modelers, geologic hazard mapping specialists, and emergency planning scientists from the University of Southern California (USC) Tsunami Research Center, CGS, and Cal OES. The Tsunami Inundation Maps for Emergency Planning cover all low-lying, populated areas along the State’s coastline. Coordinated by Cal OES, these inudation maps are developed for at risk areas to tsunamis in California and represent a combination of the maximum considered tsunamis for each area.

This web map references the live tiled map service from the OpenStreetMap (OSM) project. OpenStreetMap (OSM) is an open collaborative project to create a free editable map of the world. Volunteers gather location data using GPS, local knowledge, and other free sources of information and upload it. The resulting free map can be viewed and downloaded from the OpenStreetMap server: https://www.OpenStreetMap.org. See that website for additional information about OpenStreetMap. It is made available as a basemap for GIS work in ESRI products under a Creative Commons Attribution-ShareAlike license. Tip: This service is one of the basemaps used in the ArcGIS.com map viewer. Simply click one of those links to launch the interactive application of your choice, and then choose Open Street Map from the Basemap control to start using this service. You'll also find this service in the Basemap gallery in ArcGIS Explorer Desktop and ArcGIS Desktop 10. Tip: Here are some well known locations as they appear in this web map, accessed by launching the web map with a URL that contains location parameters: Athens, Cairo, Jakarta, Moscow, Mumbai, Nairobi, Paris, Rio De Janeiro, Shanghai

This tool includes a variety of layers as well as historical basemaps such as the Cassini 6 Inch. Use the Swipe Tool (brown button) to compare historic and modern maps with each other.Visit https://maps.scoilnet.ie/ to access video tutorials on how to use this map viewer as well as links to other useful applications such as The True Size and Passengers of the Titanic.

Pollution Impact Potential (PIP) maps were generated separately for nitrate and phosphate to rank critical source areas (CSAs) relative to one another from diffuse agriculture for both the groundwater and surface water receptor. The PIP maps are generated by the EPA Catchment Characterisation Tool (CCT). The CCT delineates the CSAs displayed in the PIP maps by overlaying the hydro(geo)logically susceptible areas (the likelihood of nutrient transfer due to soil and geological properties along the near surface and/or subsurface pathway) with nitrate or phosphate loadings. The nitrate and phosphate PIP maps for the surface water receptor combine the contribution from both the subsurface pathway and the near surface pathway while the groundwater receptor maps only consider the contribution from the groundwater pathway. Surface Water Receptor Phosphate PIP maps show the relative the pollution impact potential to surface water along the subsurface and near surface pathways due to phosphate loading. This map should be used to evaluate nutrient impact at the waterbody, subcatchment and catchment scale (at a resolution of less than 1:20,000). Pollution impact potential (PIP) maps rank the CSAs in descending order of risk (where Rank 1 is the highest risk) and are available for the surface water receptor for nitrate and phosphate, and the groundwater receptor for nitrate. Local pressure data has been used to generate the maps in agricultural areas where available. For urban, forestry and the remaining agricultural areas, regional sources of pressure data have been used; these areas are marked 'using regional loadings' on the PIP maps.

This is number 1 of 3 data sets that accompany Open Data Maps Data Story on VA's Open Data Site.

Specifically this is a crosswalk data set that identifies VA facilities and their locations via postal address with zip codes and Latitude and Longitude information for facility geo plotting postal addresses. Facility location information as of 2018.

This dataset contains the scanned maps for the currently published bedrock geology maps for Maine at 1:100,000 scale.

Near Real-time and archival data of High-resolution (10 m) flood inundation dataset over the Contiguous United States, developed based on the Sentinel-1 SAR imagery (2016-current) archive, using an automated Radar Produced Inundation Diary (RAPID) algorithm.

Important Note: The USA Topo Maps raster tile layer is in mature support as of June 2021 and no longer updated. The USA Topo Maps (US Edition) map presents land cover and detailed topographic maps for the United States. The map includes the National Park Service (NPS) Natural Earth physical map at 1.24km per pixel for the world at small scales, i-cubed eTOPO 1:250,000-scale maps for the contiguous United States at medium scales, and National Geographic TOPO! 1:100,000 and 1:24,000-scale maps (1:250,000 and 1:63,000 in Alaska) for the United States at large scales. The TOPO! maps are seamless, scanned images of United States Geological Survey (USGS) paper topographic maps.This basemap is available in the United States Vector Basemaps gallery and uses the Hybrid Reference Layer (US Edition) vector tile layer and USA Topo Maps.The vector tile layer in this web map is built using the same data sources used for other Esri Vector Basemaps. Use this MapThis map is designed to be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. If you like, you can add this web map to a custom basemap gallery for others in your organization to use in creating web maps. If you would like to add this map as a layer in other maps you are creating, you may use the tile layer item referenced in this map.

The dataset contains a range of different Pacific regional maps developed by the SPREP GIS team and is available for use by members and partners.

The USGS Topo base map service from The National Map is a combination of contours, shaded relief, woodland and urban tint, along with vector layers, such as geographic names, governmental unit boundaries, hydrography, structures, and transportation, to provide a composite topographic base map. Data sources are the National Atlas for small scales, and The National Map for medium to large scales.

χ' maps in shapefile format

ICDAR 2021 Competition on Historical Map Segmentation — Dataset

This is the dataset of the ICDAR 2021 Competition on Historical Map Segmentation (“MapSeg”). This competition ran from November 2020 to April 2021. Evaluation tools are freely available but distributed separately.

Official competition website: https://icdar21-mapseg.github.io/

The competition report can be cited as:

Joseph Chazalon, Edwin Carlinet, Yizi Chen, Julien Perret, Bertrand Duménieu, Clément Mallet, Thierry Géraud, Vincent Nguyen, Nam Nguyen, Josef Baloun, Ladislav Lenc, and Pavel Král, "ICDAR 2021 Competition on Historical Map Segmentation", in Proceedings of the 16th International Conference on Document Analysis and Recognition (ICDAR'21), September 5-10, 2021, Lausanne, Switzerland.

BibTeX entry:

@InProceedings{chazalon.21.icdar.mapseg, author = {Joseph Chazalon and Edwin Carlinet and Yizi Chen and Julien Perret and Bertrand Duménieu and Clément Mallet and Thierry Géraud and Vincent Nguyen and Nam Nguyen and Josef Baloun and Ladislav Lenc and and Pavel Král}, title = {ICDAR 2021 Competition on Historical Map Segmentation}, booktitle = {Proceedings of the 16th International Conference on Document Analysis and Recognition (ICDAR'21)}, year = {2021}, address = {Lausanne, Switzerland}, }

We thank the City of Paris for granting us with the permission to use and reproduce the atlases used in this work.

The images of this dataset are extracted from a series of 9 atlases of the City of Paris produced between 1894 and 1937 by the Map Service (“Service du plan”) of the City of Paris, France, for the purpose of urban management and planning. For each year, a set of approximately 20 sheets forms a tiled view of the city, drawn at 1/5000 scale using trigonometric triangulation.

Sample citation of original documents:

Atlas municipal des vingt arrondissements de Paris. 1894, 1895, 1898, 1905, 1909, 1912, 1925, 1929, and 1937. Bibliothèque de l’Hôtel de Ville. City of Paris. France.

Motivation

This competition aims as encouraging research in the digitization of historical maps. In order to be usable in historical studies, information contained in such images need to be extracted. The general pipeline involves multiples stages; we list some essential ones here:

segment map content: locate the area of the image which contains map content;

extract map object from different layers: detect objects like roads, buildings, building blocks, rivers, etc. to create geometric data;

georeference the map: by detecting objects at known geographic coordinate, compute the transformation to turn geometric objects into geographic ones (which can be overlaid on current maps).

Task overview

Task 1: Detection of building blocks

Task 2: Segmentation of map content within map sheets

Task 3: Localization of graticule lines intersections

Please refer to the enclosed README.md file or to the official website for the description of tasks and file formats.

Evaluation metrics and tools

Evaluation metrics are described in the competition report and tools are available at https://github.com/icdar21-mapseg/icdar21-mapseg-eval and should also be archived using Zenodo.

The ArcGIS Online US Geological Survey (USGS) topographic map collection now contains over 177,000 historical quadrangle maps dating from 1882 to 2006. The USGS Historical Topographic Map Explorer app brings these maps to life through an interface that guides users through the steps for exploring the map collection:

Finding the maps of interest is simple. Users can see a footprint of the map in the map view before they decide to add it to the display, and thumbnails of the maps are shown in pop-ups on the timeline. The timeline also helps users find maps because they can zoom and pan, and maps at select scales can be turned on or off by using the legend boxes to the left of the timeline. Once maps have been added to the display, users can reorder them by dragging them. Users can also download maps as zipped GeoTIFF images. Users can also share the current state of the app through a hyperlink or social media. This ArcWatch article guides you through each of these steps: https://www.esri.com/esri-news/arcwatch/1014/envisioning-the-past.

This statistic illustrates the share of internet users who used online maps / navigation services on a smartphone in the past 4 weeks in the United States in 2022, by age. The results were sorted by age. In 2022, some 39 percent of respondents aged 18 to 29 years stated they used online maps / navigation services on a smartphone in the past 4 weeks.

The Statista Global Consumer Survey offers a global perspective on consumption and media usage, covering the offline und online world of the consumer.

webninjasi/tfm-maps dataset hosted on Hugging Face and contributed by the HF Datasets community

The Charted Territory Map (World Edition) web map provides a customized world basemap uniquely symbolized. It takes its inspiration from a printed atlas plate and pull-down scholastic classroom maps. The map emphasizes the geographic and political features in the design. The use of country level polygons are preassigned with eight different colors. It also includes the global graticule features as well as landform labels of physical features and hillshade. This basemap, included in the ArcGIS Living Atlas of the World, uses the Charted Territory vector tile layer and World Hillshade. The vector tile layer in this web map is built using the same data sources used for other Esri Vector Basemaps. For details on data sources contributed by the GIS community, view the map of Community Maps Basemap Contributors. Esri Vector Basemaps are updated monthly.Use this MapThis map is designed to be used as a basemap for overlaying other layers of information or as a stand-alone reference map. You can add layers to this web map and save as your own map. If you like, you can add this web map to a custom basemap gallery for others in your organization to use in creating web maps. If you would like to add this map as a layer in other maps you are creating, you may use the layers referenced in this map.