Model describes the potential distribution range of Fucus spp in the Finnish coast. Model was produced using extensive data (~140,000 samples) on the Finnish Inventory Programme for Underwater Marine Environment (VELMU). Model was built using Boosted regression trees (BRT), and resulting models describe the probability of detecting a habitat-forming species in a cell. Environmental predictors include for instance (and are not only restricted to): bathymetry, euphotic depth, salinity, substrate, and wave exposure. As more accurate information is gained by diving than from video methods, dive data was used as the primary source for modelling with 75ÔÇô90% for model training and 10ÔÇô25% for validation. The secondary source, video data, was used only for species clearly identifiable from videos with additional subsets (25%) from targeted inventories. Dive and video data are limited to rather shallow depths (typically 20ÔÇô30 m), leading to a situation where there are not enough samples from deep areas (below 50 m). To avoid artefacts in the models, a randomized absence dataset for areas deeper than 50 m was used during the modelling process. These points were used only as absences in macrophytes models, based on the knowledge that macrophytes do not live at such depths in the Baltic Sea due to habitat constraints and lack of light.

The "Distributed Generation SP Distribution Heat Maps - SPD Grid Substations" dataset provides an indication of SPEN’s network capabilities and potential opportunities to connect Distributed Generation (DG) to the 11kV and 33kV network for the SP Distribution (SPD) licence area (covering Central & Southern Scotland).Each substation and circuit are assigned to one of the following categories:Green: All operational factors are within tolerable limits and so opportunities may exist to connect additional DG without reinforcing the network (subject to detailed studies).Amber: At least one factor is nearing its operational limit and hence, depending on the nature of the application, network reinforcement may be required. However, this can only be confirmed by detailed network analysis.Red: At least one factor is close to its operational limit and so installation of most levels of DG and a local connection is highly unlikely. It may also require extensive reinforcement works or given the lack of a local connection, require an extensive amount of sole user assets to facilitate such a connection.For additional information on column definitions, please click on the Dataset schema link below.Disclaimer: Whilst all reasonable care has been taken in the preparation of the information and data presented within these pages, SP Energy Networks is not responsible for any loss that may be attributed to the use of the data.Download dataset metadata (JSON)If you wish to provide feedback at a dataset or row level, please click on the “Feedback” tab above.Data TriageAs part of our commitment to enhancing the transparency, and accessibility of the data we share, we publish the results of our Data Triage process.Our Data Triage documentation includes our Risk Assessments; detailing any controls we have implemented to prevent exposure of sensitive information. Click here to access the Data Triage documentation for the Distributed Generation Heat Maps dataset. To access our full suite of Data Triage documentation, visit the SP Energy Networks Data & Information.

This map displays recreation information for the Hiawatha National Forest. It is used in the Region 9 National Forests mobile app. All data layers are authoritative.

The "Distributed Generation SP Manweb Heat Maps - SPM Super Grid Substations" dataset provides an indication of SPEN’s network capabilities and potential opportunities to connect Distributed Generation (DG) to the 11kV, 33kV and 132kV network in the SP Manweb (SPM) licence area (covering Cheshire, Merseyside, North Shropshire, North Wales).Each substation and circuit are assigned one of the following categories:Green:All operational factors are within tolerable limits and so opportunities may exist to connect additional DG without reinforcing the network (subject to detailed studies). Amber:At least one factor is nearing its operational limit and hence, depending on the nature of the application, network reinforcement may be required. However, this can only be confirmed by detailed network analysis. Red:At least one factor is close to its operational limit and so installation of most levels of DG and a local connection is highly unlikely. It may also require extensive reinforcement works or given the lack of a local connection, require an extensive amount of sole user assets to facilitate such a connection.For additional information on column definitions, please click on the Dataset schema link below.Disclaimer: Whilst all reasonable care has been taken in the preparation of the information and data presented within these pages, SP Energy Networks is not responsible for any loss that may be attributed to the use of the data.Download dataset metadata (JSON)If you wish to provide feedback at a dataset or row level, please click on the “Feedback” tab above.Data TriageAs part of our commitment to enhancing the transparency, and accessibility of the data we share, we publish the results of our Data Triage process.Our Data Triage documentation includes our Risk Assessments; detailing any controls we have implemented to prevent exposure of sensitive information. Click here to access the Data Triage documentation for the Distributed Generation Heat Maps dataset. To access our full suite of Data Triage documentation, visit the SP Energy Networks Data & Information.

This dataset series shows the distribution map (raster format: geotiff) of Betula spp. (whole genus Betula, i.e. all observed species in that genus). The distribution map is provided for Europe (EU28 plus part of other countries within the spatial extent), computed using the FISE harmonised European dataset of taxa presence/absence (based on the integration and harmonisation of the datasets by European National Forestry Inventories; BioSoil; Forest Focus/Monitoring; EUFGIS; GeneticDiversity). The distribution is estimated by means of statistical interpolation (Constrained Spatial Multi-Frequency Analysis, C-SMFA). Available years: 2006. The maps are available in the Forest Information System for Europe (FISE). FISE is run by the European Commission, Joint Research Centre. See the field Lineage for further information.

When using these data, please cite the relevant data sources. A suggested citation is included in the following:

• Various authors, 2016. Betula pendula, Betula pubescens and other birches in Europe: an outline on distribution, habitat, importance and threats. In: Online European Atlas of Forest Tree Species. FISE Comm. Publications Office of the European Union. pp. e010226+. (Under review: please, check the current status at: https://w3id.org/mtv/FISE-Comm/v01/e010226)

• de Rigo, D., Caudullo, G., Houston Durrant, T., San-Miguel-Ayanz, J., 2016. The European Atlas of Forest Tree Species: modelling, data and information on forest tree species. In: San-Miguel-Ayanz, J., de Rigo, D., Caudullo, G., Houston Durrant, T., Mauri, A. (Eds.), European Atlas of Forest Tree Species. Publ. Off. EU, Luxembourg, pp. e01aa69+. https://w3id.org/mtv/FISE-Comm/v01/e01aa69

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Search 3DEP products and source data. Search results, in download-URL form, are provided in CSV format.

The Mapping Ocean Wealth data viewer is a live online resource for sharing understanding of the value of marine and coastal ecosystems to people. It includes global maps, regionally-specific studies, reference data, and a number of “apps” providing key data analytics. Maps and apps can be opened according to key themes or geographies. The navigator the left of the maps enables you to add or remove any additional map layers as you explore. Information keys explain how the maps were made and provide additional links. Further information and resources can be found on Oceanwealth.org

• Recreation and Tourism App - Explore the value of healthy ecosystems to the tourism industry
• Natural Coastal Protection App - Discover the coastal protection benefits of coral reefs around the world
• Blue Carbon App - View Mangrove Carbon Storage
• Coral Reef Fisheries App - Learn about the status of coral reef fisheries
• Regional Planning
• Mangrove Restoration

This interactive zoning map provides a visual representation of the base zoning districts within the City of Seven Hills. It is designed to support planning, development, and public understanding of local land use regulations. The map is produced and maintained by the Cuyahoga County Planning Commission in collaboration with the City of Seven Hills.The City of Seven Hills, in collaboration with Cuyahoga County Planning Commission, provides this geographic data and related analytical results as a free public service on an "as is" basis. The City of Seven Hills and the Cuyahoga County Planning Commission make no guarantee(s) or warranty(ies) as to the accuracy, completeness, timeliness, or fitness for any particular use of the information contained herein, and said information is not intended to, nor does it, constitute an official public record of the City of Seven Hills or the Cuyahoga County Planning Commission. The official records of the office or agency from which they were compiled remain the official record of any such office or agency. By accessing, viewing, or using any part of the City of Seven Hills or the Cuyahoga County Planning Commission GIS data, you expressly acknowledge you have read, agree to, and consent to be bound by all of the terms and conditions listed in this disclaimer statement.

Web mapping application intended for use by both public and City of Eugene staff. This applications was created so people can look up a site by address or taxlot number and get information returned for that site. Information that is returned includes if the site is within certain tax exemption boundaries, planning boundaries, zoning,if the property is in city limits, and who the city councilor is. This was created using the web app builder in ArcGIS online.

The Taiwan e-Map has been created in offline map file (MBTiles format) to meet the demand for offline maps on mobile map apps. If you need to integrate the service, please refer to the "Taiwan General Electronic Map (with contour lines, scales smaller than 1:18,000)" or "Taiwan General Electronic Map (without contour lines, scales smaller than 1:18,000)" datasets.

The "Distributed Generation SP Distribution Heat Maps - SPD Primary" dataset provides an indication of SPEN’s network capabilities and potential opportunities to connect Distributed Generation (DG) to the 11kV and 33kV network for the SP Distribution (SPD) licence area (covering Central & Southern Scotland).Each substation and circuit are assigned to one of the following categories:Green: All operational factors are within tolerable limits and so opportunities may exist to connect additional Distributed Generation without reinforcing the network (subject to detailed studies).Amber: At least one factor is nearing its operational limit and hence, depending on the nature of the application, network reinforcement may be required. However, this can only be confirmed by detailed network analysis.Red: At least one factor is close to its operational limit and so installation of most levels of Distributed Generation and a local connection is highly unlikely. It may also require extensive reinforcement works or given the lack of a local connection, require an extensive amount of sole user assets to facilitate such a connection.For additional information on column definitions, please click on the Dataset schema link below.Disclaimer: Whilst all reasonable care has been taken in the preparation of the information and data presented within these pages, SP Energy Networks is not responsible for any loss that may be attributed to the use of the data.Download dataset metadata (JSON)If you wish to provide feedback at a dataset or row level, please click on the “Feedback” tab above.Data TriageAs part of our commitment to enhancing the transparency, and accessibility of the data we share, we publish the results of our Data Triage process.Our Data Triage documentation includes our Risk Assessments; detailing any controls we have implemented to prevent exposure of sensitive information. Click here to access the Data Triage documentation for the Distributed Generation Heat Maps dataset. To access our full suite of Data Triage documentation, visit the SP Energy Networks Data & Information.

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.

The DC Office of the Chief Financial Officer (OCFO), Office of Tax and Revenue (OTR), Real Property Tax Administration (RPTA) values all real property in the District of Columbia. This public interactive Real Property Assessment map application accompanies the OCFO MyTax DC and OTR websites. Use this mapping application to search for and view all real property, assessment valuation data, assessment neighborhood areas and sub-areas, detailed assessment information, and many real property valuation reports by various political and administrative areas. View by other administrative areas such as DC Wards, ANCs, DC Squares, and by specific real property characteristics such as property type and/or sale date. If you have questions, comments, or suggestions regarding the Real Property Assessment Map, contact the Real Property Assessment Division GIS Program at (202) 442-6484 or maps.title@dc.gov.

CAL FIRE's Fire and Resource Assessment Program (FRAP) annually maintains and distributes an historical fire perimeter dataset from across public and private lands in California. The GIS data is developed with the cooperation of the United States Forest Service Region 5, the Bureau of Land Management, the National Park Service and the United States Fish and Wildlife Service and is released in the spring with added data from the previous calendar year. Although the dataset represents the most complete digital record of fire perimeters in California, it is still incomplete, and users should be cautious when drawing conclusions based on the data. This app contains three pages of maps and documentation of the historical fire perimeter metadata: Historical Fire Perimeters: The landing page highlights the recent large fires (≥5,000 acres) on a backdrop of all of the dataset's documented fire perimeters dating back to 1878. This map includes perimeters symbolized by decade, county boundaries, California Vegetation, and NAIP imagery back to 2005. This page provides users the ability to add their own data or filter the fire perimeter data. It cleanly lists fire perimeters shown on the map with their name, year, and GIS calculated acreage. The user can navigate to the CAL FIRE current incident webpage or provide comments to the dataset's steward. Times Burned: The second page provides a map showing an analysis performed annually on the fire perimeter dataset to show case burn frequency from 1950 to present for fires greater than one acre. Fire Across Time: This third page provides a time enabled layer of the fire perimeter dataset, featuring a time slider to allow users to view the perimeter dataset across time. The final page provides the user with the dataset's metadata, including its most current data dictionary. For any questions, please contact the data steward:Kim Wallin, GIS SpecialistCAL FIRE, Fire & Resource Assessment Program (FRAP)kimberly.wallin@fire.ca.gov

Runs of homozygosity (ROH) are successive homozygous segments of the genome where the two haplotypes inherited from the parents are identical-by-descent. A key focus of this project is to investigate ROH distribution patterns in the genomes of outbred fruit crops using pear as a study case

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.

The SI maps of four larch species was defined in WGS1984 geographic coordinate system with a spatial resolution of 90 m. It is in a GeoTIFF format. The spatial extent of SI maps includes mainland China.

Jounal: submit to Scientific Data
Title:A gridded 90m dataset of site index for site quality assessment of four larch species in China

Performance of models of Culicoides spp. occurrence and abundance in Spain.

Where, KNN: k-nearest neighbors for classification; ABC: AdaBoost for classification; RFC: random forest for classification. The mean and standard deviation (std) is provided for each measure.

To create this app: