Registered scans of the maps from the Language Atlas of the Pacific Area (excluding the maps of Japan) are made available through the Electronic Cultural Atlas Initiative (ECAI) Metadata Clearinghouse as a result of cooperation between Academia Sinica and the ECAI Austronesian Atlas Team led by David Blundell and Lawrence Crissman. The Australian Academy of the Humanities, which owns the copyright to the available maps, has graciously permitted their reproduction and distribution in this digital format, and we are grateful for their support. Any public use of the maps should acknowledge their source and copyright ownership.

This collection is a legacy product that is no longer supported. It may not meet current government standards. The North American Atlas data are standardized geospatial data sets at 1:10,000,000 scale. A variety of basic data layers (e.g. roads, railroads, populated places, political boundaries, hydrography, bathymetry, sea ice and glaciers) have been integrated so that their relative positions are correct. This collection of data sets forms a base with which other North American thematic data may be integrated. The North American Atlas data are intended for geographic display and analysis at the national and continental level. Any data outside of Canada, Mexico, and the United States of America included in the North American Atlas data sets is strictly to complete the context of the data.

The GIS HydroAtlas of Madagascar is the final output from the small hydro resource mapping component of the activity “ Renewable Energy Resource Mapping and Geospatial Planning – Madagascar” [Project ID: P145350]. You can find more information about the project here: https://www.esmap.org/re_mapping_madagascar Please cite as: [Data/information/map obtained from the] “World Bank via ENERGYDATA.info, under a project funded by the Energy Sector Management Assistance Program (ESMAP). For more information: Madagascar Small Hydro GIS Atlas, 2017, https://energydata.info/dataset/madagscar-small-hydro-gis-atlas-2017"

The Digital Atlas of Micronesia is the foremost source of maps and geospatial information for the Federated States of Micronesia. People searching for any sort of geospatial information can come to this web-based Atlas to identify, visualize, query, analyze, and acquire datasets relevant to their interests. At the core of the Atlas are web-enabled GIS and searchable database that allow users to view and manipulate hundreds of layers of geospatial information. In addition to serving as a data repository, the Atlas is also an informational tool and incorporates hundreds of pre-made maps, charts, and datasets related to the natural and human environment of Micronesian islands.

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. The MANZ spatial database and map layer was produced by CTI from 2010 imagery using 21 map units that were directly cross-walked or matched to their corresponding rUSNVC plant association/alliance or land cover types. The final map layer was assessed for thematic accuracy by creating contingency tables and the final overall accuracy of the map layer was determined to be 96% with a Kappa value of 95%. The vegetation mapping was conducted at MANZ in two phases. The first phase conducted by the USGS Fort Collins Science Center created the primary vegetation and associated spatial data layers using the 2005 NAIP Manzanar NE DOQQ imagery (acquired on September 3, 2005 from the Cal-Atlas Geospatial Clearinghouse at http://atlas.ca.gov/). Preliminary mapping was conducted by the USGS through a semi-automated process using a combination of the ENVI Feature Extraction Module (ITT Visual Information Systems, 2008) and ArcGIS software (ESRI, 2008).

The GIS Biomass Atlas of Pakistan is the final output from the biomass resource mapping component of the activity “ Renewable Energy Resource Mapping and Geospatial Planning – Pakistan” [Project ID: P146140]. You can find more information about the project here: https://www.esmap.org/re_mapping_pakistan To visualize the geospatial data generated in this study, please access: https://irena.masdar.ac.ae/GIS/?map=2636 Please cite as: [Data/information/map obtained from the] “World Bank via ENERGYDATA.info, under a project funded by the Energy Sector Management Assistance Program (ESMAP). For more information: Pakistan Biomass GIS Atlas, 2016, https://energydata.info/dataset/pakistan-biomass-gis-atlas"

The GIS database has been developed under the project "Renewable Energy Mapping: Small Hydro Tanzania". This study is part of a technical assistance project, ESMAP funded, being implemented by Africa Energy Practice of the World Bank in Tanzania which aims at supporting resource mapping and geospatial planning for small hydro. Please refer to the country project page for additional outputs and reports: http://esmap.org/re_mapping_TNZ The GIS database contains the following datasets: Administrative Boundaries Hydrology Protected Areas Satellite Imagery Land Cover Geology Topography Population Infrastructure: Power/ Transport each accompanied by a metadata file Please cite as: [Data/information/map obtained from the] “World Bank via ENERGYDATA.info, under a project funded by the Energy Sector Management Assistance Program (ESMAP). For more information: Tanzania Small Hydro GIS Atlas, 2018, https://energydata.info/dataset/tanzania-small-hydro-gis-database-2018"

The Surface Earth System Analysis and Modeling Environment (SESAME) Human-Earth Atlas includes hundreds of variables capturing both human and non-human aspects of the Earth system on two common spatial grids of 1- and 0.25-degree resolution. The Atlas is structured by common spheres, and many variables resolve changes over time. Many of the national-level tabular human system variables are downscaled to spatial grids using dasymetric mapping, accounting for country boundary changes over time. An associated software toolbox allows users to add raster, point, line, polygon, and tabular datasets, transforming them onto a standardized spatial grid at the desired resolution as well as to work conveniently with jurisdictional (e.g. country) data.

File Description: atlas: Contains netCDF files at 1-degree resolution in netCDF format. atlas_p25: Contains selected netCDF files at 0.25-degree resolution. genscripts: Original Jupyter notebook scripts used to generate the atlas. SESAME_Atlas_Documentation_v1.pdf: Documentation file for the SESAME Human-Earth Atlas. SESAME_Human-Earth_Atlas_v1.xlsx: Comprehensive summary and documentation for the SESAME Human-Earth Atlas, including details on pre- and post-processing steps.

View the diversity of challenges and opportunities across America's counties within different types of rural regions and communities. Get statistics on people, jobs, and agriculture.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Data file GIS API Services Interactive map Zip of CSV files For complete information, please visit https://data.gov.

A joint venture involving the National Atlas programs in Canada (Natural Resources Canada), Mexico (Instituto Nacional de Estad stica Geograf a e Inform tica), and the United States (U.S. Geological Survey), as well as the North American Commission for Environmental Co-operation, has led to the release (June 2004) of several new products: an updated paper map of North America, and its associated geospatial data sets and their metadata. These data sets are available online from each of the partner countries both for visualization and download. The North American Atlas data are standardized geospatial data sets at 1:10,000,000 scale. A variety of basic data layers (e.g. roads, railroads, populated places, political boundaries, hydrography, bathymetry, sea ice and glaciers) have been integrated so that their relative positions are correct. This collection of data sets forms a base with which other North American thematic data may be integrated. Any data outside of Canada, Mexico, and the United States of America included in the North American Atlas data sets is strictly to complete the context of the data. The North American Atlas - Political Boundaries data set shows political entities in North America as polygons representing jurisdictional areas, and as lines representing political boundaries, including International boundaries, Provincial boundaries, State or territory boundaries, and the International Date Line. This data set was produced using digital files supplied by Natural Resources Canada, Instituto Nacional de Estad stica Geograf a e Inform tica, and the U.S. Geological Survey.

DC Atlas Pro is a mapping tool that contains hundreds of different data layers, organized by category. DC Atlas Pro is the updated version of DC Atlas Plus, both of which were created by OCTO GIS, as an easy way to view geographic information about the District of Columbia. This new and improved version of DC Atlas allows you to search for addresses, intersections, or place names; analyze and identify data; and create maps that you can share. For detailed instructions on how to use DC Atlas Pro, please visit the Get Help / How to Use This Map section of the application.

The National Zoning Atlas is a collaborative project digitizing, demystifying, & democratizing ~30,000 U.S. zoning codes. It was founded by Cornell University professor Sara Bronin and has involved over 300 zoning and geospatial analysts. WHAT: Zoning laws, adopted by perhaps 30,000 local governments across the country, dictate much of what can be built in the United States. The National Zoning Atlas is helping us better understand these sometimes-opaque but incredibly influential laws by depicting their key attributes in an online, user-friendly map. As a federated academic enterprise, the National Zoning Atlas encompasses several disciplines. It is a legal research project, as it delves deeply into the regulatory frameworks that dictate so much of the way we use our land. It is a data science project, and it deploys novel systems of collecting, analyzing, and displaying geospatial and regulatory data. It is a digital humanities project, innovative in its methodology and having the potential to unlock new research on the central instrument that shapes our urban built environment, social relations and hierarchies, and geographies of opportunity. It is a social science project that will improve our understanding of our politics, society, and economy - and expand our collective ability to reimagine future, alternative, and reparative trajectories. And it is a computer science project, deploying machine learning and natural language processing to expand our understanding of how algorithms can read complex regulatory texts. WHY: Zoning laws have direct impacts on housing availability, transportation systems, the environment, economic opportunity, educational opportunity, and our food supply. Despite codes’ importance, ordinary people can’t make heads or tails of them. They are too complex and inscrutable. The National Zoning Atlas will help people better understand zoning, which would in turn broaden participation in land use decisions, identify opportunities for zoning reform, and narrow a wide information gap that currently favors land speculators, institutional investors, and homeowners over socioeconomically disadvantaged groups. It would also enable comparisons across jurisdictions, illuminate regional and statewide trends, and strengthen national planning for housing production, transportation infrastructure, and climate response. To understand the kinds of things a zoning atlas can show, review this research paper documenting the findings of the Connecticut Zoning Atlas (the first statewide atlas) and this research paper in HUD Cityscape describing the motivations of the project. HOW: To date, this project has relied on manual reviews of thousands of pages of zoning code texts and their corresponding maps. A how-to guide for these reviews is available for free download. The project is also using grant funding from the National Science Foundation and the U.S. Department of Housing and Community Development Community Block Grant Disaster Recovery Program to automate this process so we can more quickly map the 30,000 localities estimated to use zoning. Our basic operating principles are: Deploy data for the public good ​Evaluate and adapt methods and approaches ​Collaborate broadly ​Cultivate up-and-coming talent ​Assume that this is a solvable problem, worth solving ​WHO: Project participants overwhelmingly include representatives of academic institutions, nonprofits, and government agencies, with students providing important support. In addition, private partners may participate on specific geographic teams or provide data. Because this project aims to expand knowledge for the public good, its resulting online atlases will remain free to view regardless of who pitches in to create them.

The purpose of the�Natural Resources Atlas�is to provide geographic information about environmental features and sites that the Vermont Agency of Natural Resources manages, monitors, permits, or regulates. In addition to standard map navigation tools, this site allows you to link from sites to documents where available, generate reports, export search results, import data, search, measure, mark-up, query map features, and print PDF maps.

A joint venture involving the National Atlas programs in Canada (Natural Resources Canada), Mexico (Instituto Nacional de Estad stica Geograf a e Inform tica), and the United States (U.S. Geological Survey), as well as the North American Commission for Environmental Co-operation, has led to the release (June 2004) of several new products: an updated paper map of North America, and its associated geospatial data sets and their metadata. These data sets are available online from each of the partner countries both for visualization and download. The North American Atlas data are standardized geospatial data sets at 1:10,000,000 scale. A variety of basic data layers (e.g. roads, railroads, populated places, political boundaries, hydrography, bathymetry, sea ice and glaciers) have been integrated so that their relative positions are correct. This collection of data sets forms a base with which other North American thematic data may be integrated. Any data outside of Canada, Mexico, and the United States of America included in the North American Atlas data sets is strictly to complete the context of the data. The North American Atlas - Glaciers data set shows areas of permanent ice found on the North America landmass including Greenland, and also shows areas of land found within glaciers. No distinction is made between major glaciers, ice fields, and the Greenland ice cap. The only permanent ice shown on land areas outside of North America and Greenland is on Iceland.

Layers derived from geospatial analysis results conducted for the development of the Atlas of Unburnable Oil for supply-side climate policies. It encompasses layers depicting the overlap between global sedimentary oil basins and various socio-environmental criteria used to define exclusion areas for oil extraction, where oil resources should be left untapped in order to keep global warming under 1.5 °C. These criteria include biodiversity hotspots, centers of terrestrial and marine endemic species richness, natural protected areas, urban areas, and the territories of Indigenous Peoples in voluntary isolation.

Developed by SOLARGIS (https://solargis.com) and provided by the Global Solar Atlas (GSA), this data resource contains diffuse horizontal irradiation (DIF) in kWh/m² covering the globe. Data is provided in a geographic spatial reference (EPSG:4326). The resolution (pixel size) of solar resource data (GHI, DIF, GTI, DNI) is 9 arcsec (nominally 250 m), PVOUT and TEMP 30 arcsec (nominally 1 km) and OPTA 2 arcmin (nominally 4 km). The data is hyperlinked under 'resources' with the following characeristics: DIF - LTAy_AvgDailyTotals (GeoTIFF) Data format: GEOTIFF File size : 198.94 MB There are two temporal representation of solar resource and PVOUT data available: • Longterm yearly/monthly average of daily totals (LTAym_AvgDailyTotals) • Longterm average of yearly/monthly totals (LTAym_YearlyMonthlyTotals) Both type of data are equivalent, you can select the summarization of your preference. The relation between datasets is described by simple equations: • LTAy_YearlyTotals = LTAy_DailyTotals * 365.25 • LTAy_MonthlyTotals = LTAy_DailyTotals * Number_of_Days_In_The_Month For individual country or regional data downloads please see: https://globalsolaratlas.info/download (use the drop-down menu to select country or region of interest) For data provided in AAIGrid please see: https://globalsolaratlas.info/download/world. For more information and terms of use, please, read metadata, provided in PDF and XML format for each data layer in a download file. For other data formats, resolution or time aggregation, please, visit Solargis website. Data can be used for visualization, further processing, and geo-analysis in all mainstream GIS software with raster data processing capabilities (such as open source QGIS, commercial ESRI ArcGIS products and others).

A joint venture involving the National Atlas programs in Canada (Natural Resources Canada), Mexico (Instituto Nacional de Estadística Geografía e Informática), and the United States (U.S. Geological Survey), as well as the North American Commission for Environmental Co-operation, has led to the release (June 2004) of several new products: an updated paper map of North America, and its associated geospatial data sets and their metadata. These data sets are available online from each of the partner countries both for visualization and download. The North American Atlas data are standardized geospatial data sets at 1:10,000,000 scale. A variety of basic data layers (e.g. roads, railroads, populated places, political boundaries, hydrography, bathymetry, sea ice and glaciers) have been integrated so that their relative positions are correct. This collection of data sets forms a base with which other North American thematic data may be integrated. Any data outside of Canada, Mexico, and the United States of America included in the North American Atlas data sets is strictly to complete the context of the data. The North American Atlas - Populated Places data set shows a selection of named populated places suitable for use at a scale of 1:10,000,000. Places, which refer to individual municipalities, are always shown using point symbols. These symbols have been fitted to the North American Atlas roads, railroads, and hydrography layers, so that the points represent the approximate locations of places relative to data in these other layers. The selection of populated places was based on local importance (as shown by population size), importance as a cross-border point, and, occasionally, on other factors. All capital cities (national, provincial, territorial or State) are shown for Canada, Mexico, and the United States of America. Attributes were added to the data to reflect population class, name, and capital. Cartographic considerations were taken into account so that names do not overlap in crowded areas, nor are there too many names shown for sparsely-populated areas.

The Idaho Rangeland Atlas is a collaboration of the University of Idaho Library and the University of Idaho Rangeland Center. Its purpose is to provide simple, clear information about Idaho's rangelands using open, accessible web technologies. Leveraging the University of Idaho's investements in geospatial data and infrastructure enable us to present this information. We believe that if an Idaho citizen wants to understand the basic facts of rangeland ecology and space in our state, those facts should be available without the need to engage in advanced analysis or obtain new skills.The lack of an aggregating resource, like a statistical abstract, adds time to process of discovery and delays the ability of users to move on, either to advanced research questions, as they have to answer and prove more fundamental ones first, or to other tasks based on the information that they now have. Given the increasing accessibility of web-based geospatial processing, and the improvement in technology to provide rich, informative, web-based queries of spatial data, the opportunity exists to re-invent the statistical abstract for natural resource and agricultural questions, providing a simple interface to gather facts about the state of Idaho’s rangelands.

This deposit offers a comprehensive collection of geospatial and metadata files that constitute the Seatizen Atlas dataset, facilitating the management and analysis of spatial information. To navigate through the data, you can use an interface available at seatizenmonitoring.ifremer.re, which provides a condensed CSV file tailored to your choice of metadata and the selected area.To retrieve the associated images, you will need to use a script that extracts the relevant frames. A brief tutorial is available here: Tutorial.All the scripts for processing sessions, creating the geopackage, and generating files can be found here: SeatizenDOI github repository.The repository includes:

seatizen_atlas_db.gpkg: geopackage file that stores extensive geospatial data, allowing for efficient management and analysis of spatial information.
session_doi.csv: a CSV file listing all sessions published on Zenodo. This file contains the following columns:

session_name: identifies the session.
session_doi: indicates the URL of the session.
place: indicates the location of the session.
date: indicates the date of the session.
raw_data: indicates whether the session contains raw data or not.
processed_data: indicates whether the session contains processed data.
metadata_images.csv: a CSV file describing all metadata for each image published in open access. This file contains the following columns:

OriginalFileName: indicates the original name of the photo.
FileName: indicates the name of the photo adapted to the naming convention adopted by the Seatizen team (i.e., YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number_originalimagename).
relative_file_path: indicates the path of the image in the deposit.
frames_doi: indicates the DOI of the version where the image is located.
GPSLatitude: indicates the latitude of the image (if available).
GPSLongitude: indicates the longitude of the image (if available).
GPSAltitude: indicates the depth of the frame (if available).
GPSRoll: indicates the roll of the image (if available).
GPSPitch: indicates the pitch of the image (if available).
GPSTrack: indicates the track of the image (if available).
GPSDatetime: indicates when frames was take (if available).
GPSFix: indicates GNSS quality levels (if available).
metadata_multilabel_predictions.csv: a CSV file describing all predictions from last multilabel model with georeferenced data.

FileName: indicates the name of the photo adapted to the naming convention adopted by the Seatizen team (i.e., YYYYMMDD_COUNTRYCODE-optionalplace_device_session-number_originalimagename).
frames_doi: indicates the DOI of the version where the image is located.
GPSLatitude: indicates the latitude of the image (if available).
GPSLongitude: indicates the longitude of the image (if available).
GPSAltitude: indicates the depth of the frame (if available).
GPSRoll: indicates the roll of the image (if available).
GPSPitch: indicates the pitch of the image (if available).
GPSTrack: indicates the track of the image (if available).
GPSFix: indicates GNSS quality levels (if available).
prediction_doi: refers to a specific AI model prediction on the current image (if available).
A column for each class predicted by the AI model.
metadata_multilabel_annotation.csv: a CSV file listing the subset of all the images that are annotated, along with their annotations. This file contains the following columns:

FileName: indicates the name of the photo.
frame_doi: indicates the DOI of the version where the image is located.
relative_file_path: indicates the path of the image in the deposit.
annotation_date: indicates the date when the image was annotated.
A column for each class with values:

1: if the class is present.
0: if the class is absent.
-1: if the class was not annotated.
seatizen_atlas.qgz: a qgis project which formats and highlights the geopackage file to facilitate data visualization.
darwincore_multilabel_annotations.zip: a Darwin Core Archive (DwC-A) file listing the subset of all the images that are annotated, along with their annotations.

The Food Access Research Atlas presents a spatial overview of food access indicators for low-income and other census tracts using different measures of supermarket accessibility, provides food access data for populations within census tracts, and offers census-tract-level data on food access that can be downloaded for community planning or research purposes.This record was taken from the USDA Enterprise Data Inventory that feeds into the https://data.gov catalog. Data for this record includes the following resources: Interactive map GIS API Services Data file For complete information, please visit https://data.gov.