New Parking Citations dataset here: https://data.lacity.org/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://www.conservation.ca.gov/cgs/rgm/state-plane-coordinate-system). For more information on Geographic vs Projected coordinate systems, read here: https://www.esri.com/arcgis-blog/products/arcgis-pro/mapping/gcs_vs_pcs/ For information on how to change map projections, read here: https://learn.arcgis.com/en/projects/make-a-web-map-without-web-mercator/

Statewide 2016 Lidar points colorized with 2018 NAIP imagery as a scene created by Esri using ArcGIS Pro for the entire State of Connecticut. This service provides the colorized Lidar point in interactive 3D for visualization, interaction of the ability to make measurements without downloading.Lidar is referenced at https://cteco.uconn.edu/data/lidar/ and can be downloaded at https://cteco.uconn.edu/data/download/flight2016/. Metadata: https://cteco.uconn.edu/data/flight2016/info.htm#metadata. The Connecticut 2016 Lidar was captured between March 11, 2016 and April 16, 2016. Is covers 5,240 sq miles and is divided into 23, 381 tiles. It was acquired by the Captiol Region Council of Governments with funding from multiple state agencies. It was flown and processed by Sanborn. The delivery included classified point clouds and 1 meter QL2 DEMs. The 2016 Lidar is published on the Connecticut Environmental Conditions Online (CT ECO) website. CT ECO is the collaborative work of the Connecticut Department of Energy and Environmental Protection (DEEP) and the University of Connecticut Center for Land Use Education and Research (CLEAR) to share environmental and natural resource information with the general public. CT ECO's mission is to encourage, support, and promote informed land use and development decisions in Connecticut by providing local, state and federal agencies, and the public with convenient access to the most up-to-date and complete natural resource information available statewide.Process used:Extract Building Footprints from Lidar1. Prepare Lidar - Download 2016 Lidar from CT ECO- Create LAS Dataset2. Extract Building Footprints from LidarUse the LAS Dataset in the Classify Las Building Tool in ArcGIS Pro 2.4.Colorize LidarColorizing the Lidar points means that each point in the point cloud is given a color based on the imagery color value at that exact location.1. Prepare Imagery- Acquire 2018 NAIP tif tiles from UConn (originally from USDA NRCS).- Create mosaic dataset of the NAIP imagery.2. Prepare and Analyze Lidar Points- Change the coordinate system of each of the lidar tiles to the Projected Coordinate System CT NAD 83 (2011) Feet (EPSG 6434). This is because the downloaded tiles come in to ArcGIS as a Custom Projection which cannot be published as a Point Cloud Scene Layer Package.- Convert Lidar to zlas format and rearrange. - Create LAS Datasets of the lidar tiles.- Colorize Lidar using the Colorize LAS tool in ArcGIS Pro. - Create a new LAS dataset with a division of Eastern half and Western half due to size limitation of 500GB per scene layer package. - Create scene layer packages (.slpk) using Create Cloud Point Scene Layer Package. - Load package to ArcGIS Online using Share Package. - Publish on ArcGIS.com and delete the scene layer package to save storage cost.Additional layers added:Visit https://cteco.uconn.edu/projects/lidar3D/layers.htm for a complete list and links. 3D Buildings and Trees extracted by Esri from the lidarShaded Relief from CTECOImpervious Surface 2012 from CT ECONAIP Imagery 2018 from CTECOContours (2016) from CTECOLidar 2016 Download Link derived from https://www.cteco.uconn.edu/data/download/flight2016/index.htm

Parking citations with latitude / longitude in Mercator map projection which is a variant of Web Mercator, Google Web Mercator, Spherical Mercator, WGS 84 Web Mercator or WGS 84/Pseudo-Mercator and is the de facto standard for Web mapping applications. Additional information about Meractor projections - https://en.wikipedia.org/wiki/Mercator_projection The official EPSG identifier for Web Mercator is EPSG:3857. Additional information on projections can be read here: https://webhelp.esri.com/arcgisdesktop/9.3/index.cfm?TopicName=Projection_basics_the_GIS_professional_needs_to_know For more information on Geographic vs Projected coordinate systems, read here: https://www.esri.com/arcgis-blog/products/arcgis-pro/mapping/gcs_vs_pcs/ For information on how to change map projections, read here: https://learn.arcgis.com/en/projects/make-a-web-map-without-web-mercator/

The U.S. Defense Department oversees the USA"s armed forces and manages over 30 million acres of land. With over 2.8 million service members and civilian employees the department is the world"s largest employer.Dataset SummaryPhenomenon Mapped: Lands managed by the U.S. Department of DefenseGeographic Extent: United States, Guam, Puerto RicoData Coordinate System: WGS 1984Visible Scale: The data is visible at all scalesSource: DOD Military Installations Ranges and Training Areas layer. Publication Date: May 2025This layer is a view of the USA Federal Lands layer. A filter has been used on this layer to eliminate non-Department of Defense lands. For more information on layers for other agencies see the USA Federal Lands layer.What can you do with this layer?This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "department of defense" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box expand Portal if necessary then select Living Atlas. Type "department of defense" in the search box, browse to the layer then click OK.In both ArcGIS Online and Pro you can change the layer's symbology and view its attribute table. You can filter the layer to show subsets of the data using the filter button in Online or a definition query in Pro.The data can be exported to a file geodatabase, a shape file or other format and downloaded using the Export Data button on the top right of this webpage.This layer can be used as an analytic input in both Online and Pro through the Perform Analysis window Online or as an input to a geoprocessing tool, model, or Python script in Pro.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.Questions?Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.

This webmap is a subset of Global Landcover 1992 - 2020 Image Layer. You can access the source data from here. This layer is a time series of the annual ESA CCI (Climate Change Initiative) land cover maps of the world. ESA has produced land cover maps for the years 1992-2020. These are available at the European Space Agency Climate Change Initiative website.Time Extent: 1992-2020Cell Size: 300 meterSource Type: ThematicPixel Type: 8 Bit UnsignedData Projection: GCS WGS84Mosaic Projection: Web Mercator Auxiliary SphereExtent: GlobalSource: ESA Climate Change InitiativeUpdate Cycle: Annual until 2020, no updates thereafterWhat can you do with this layer?This layer may be added to ArcGIS Online maps and applications and shown in a time series to watch a "time lapse" view of land cover change since 1992 for any part of the world. The same behavior exists when the layer is added to ArcGIS Pro.In addition to displaying all layers in a series, this layer may be queried so that only one year is displayed in a map. This layer can be used in analysis. For example, the layer may be added to ArcGIS Pro with a query set to display just one year. Then, an area count of land cover types may be produced for a feature dataset using the zonal statistics tool. Statistics may be compared with the statistics from other years to show a trend.To sum up area by land cover using this service, or any other analysis, be sure to use an equal area projection, such as Albers or Equal Earth.Different Classifications Available to MapFive processing templates are included in this layer. The processing templates may be used to display a smaller set of land cover classes.Cartographic Renderer (Default Template)Displays all ESA CCI land cover classes.*Forested lands TemplateThe forested lands template shows only forested lands (classes 50-90).Urban Lands TemplateThe urban lands template shows only urban areas (class 190).Converted Lands TemplateThe converted lands template shows only urban lands and lands converted to agriculture (classes 10-40 and 190).Simplified RendererDisplays the map in ten simple classes which match the ten simplified classes used in 2050 Land Cover projections from Clark University.Any of these variables can be displayed or analyzed by selecting their processing template. In ArcGIS Online, select the Image Display Options on the layer. Then pull down the list of variables from the Renderer options. Click Apply and Close. In ArcGIS Pro, go into the Layer Properties. Select Processing Templates from the left hand menu. From the Processing Template pull down menu, select the variable to display.Using TimeBy default, the map will display as a time series animation, one year per frame. A time slider will appear when you add this layer to your map. To see the most current data, move the time slider until you see the most current year.In addition to displaying the past quarter century of land cover maps as an animation, this time series can also display just one year of data by use of a definition query. For a step by step example using ArcGIS Pro on how to display just one year of this layer, as well as to compare one year to another, see the blog called Calculating Impervious Surface Change.Hierarchical ClassificationLand cover types are defined using the land cover classification (LCCS) developed by the United Nations, FAO. It is designed to be as compatible as possible with other products, namely GLCC2000, GlobCover 2005 and 2009.This is a heirarchical classification system. For example, class 60 means "closed to open" canopy broadleaved deciduous tree cover. But in some places a more specific type of broadleaved deciduous tree cover may be available. In that case, a more specific code 61 or 62 may be used which specifies "open" (61) or "closed" (62) cover.Land Cover ProcessingTo provide consistency over time, these maps are produced from baseline land cover maps, and are revised for changes each year depending on the best available satellite data from each period in time. These revisions were made from AVHRR 1km time series from 1992 to 1999, SPOT-VGT time series between 1999 and 2013, and PROBA-V data for years 2013, 2014 and 2015. When MERIS FR or PROBA-V time series are available, changes detected at 1 km are re-mapped at 300 m. The last step consists in back- and up-dating the 10-year baseline LC map to produce the 24 annual LC maps from 1992 to 2015.Source dataThe datasets behind this layer were extracted from NetCDF files and TIFF files produced by ESA. Years 1992-2015 were acquired from ESA CCI LC version 2.0.7 in TIFF format, and years 2016-2018 were acquired from version 2.1.1 in NetCDF format. These are downloadable from ESA with an account, after agreeing to their terms of use. https://maps.elie.ucl.ac.be/CCI/viewer/download.phpCitationESA. Land Cover CCI Product User Guide Version 2. Tech. Rep. (2017). Available at: maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdfMore technical documentation on the source datasets is available here:https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-land-cover?tab=doc*Index of all classes in this layer:10 Cropland, rainfed11 Herbaceous cover12 Tree or shrub cover20 Cropland, irrigated or post-flooding30 Mosaic cropland (>50%) / natural vegetation (tree, shrub, herbaceous cover) (<50%)40 Mosaic natural vegetation (tree, shrub, herbaceous cover) (>50%) / cropland (<50%)50 Tree cover, broadleaved, evergreen, closed to open (>15%)60 Tree cover, broadleaved, deciduous, closed to open (>15%)61 Tree cover, broadleaved, deciduous, closed (>40%)62 Tree cover, broadleaved, deciduous, open (15-40%)70 Tree cover, needleleaved, evergreen, closed to open (>15%)71 Tree cover, needleleaved, evergreen, closed (>40%)72 Tree cover, needleleaved, evergreen, open (15-40%)80 Tree cover, needleleaved, deciduous, closed to open (>15%)81 Tree cover, needleleaved, deciduous, closed (>40%)82 Tree cover, needleleaved, deciduous, open (15-40%)90 Tree cover, mixed leaf type (broadleaved and needleleaved)100 Mosaic tree and shrub (>50%) / herbaceous cover (<50%)110 Mosaic herbaceous cover (>50%) / tree and shrub (<50%)120 Shrubland121 Shrubland evergreen122 Shrubland deciduous130 Grassland140 Lichens and mosses150 Sparse vegetation (tree, shrub, herbaceous cover) (<15%)151 Sparse tree (<15%)152 Sparse shrub (<15%)153 Sparse herbaceous cover (<15%)160 Tree cover, flooded, fresh or brakish water170 Tree cover, flooded, saline water180 Shrub or herbaceous cover, flooded, fresh/saline/brakish water190 Urban areas200 Bare areas201 Consolidated bare areas202 Unconsolidated bare areas210 Water bodies

The National Insect and Disease Risk map identifies areas with risk of significant tree mortality due to insects and plant diseases. The layer identifies lands in three classes: areas with risk of tree mortality from insects and disease between 2013 and 2027, areas with lower tree mortality risk, and areas that were formerly at risk but are no longer at risk due to disturbance (human or natural) between 2012 and 2018. Areas with risk of tree mortality are defined as places where at least 25% of standing live basal area greater than one inch in diameter will die over a 15-year time frame (2013 to 2027) due to insects and diseases.The National Insect and Disease Risk map, produced by the US Forest Service FHAAST, is part of a nationwide strategic assessment of potential hazard for tree mortality due to major forest insects and diseases. Dataset Summary Phenomenon Mapped: Risk of tree mortality due to insects and diseaseUnits: MetersCell Size: 30 meters in Hawaii and 240 meters in Alaska and the Contiguous USSource Type: DiscretePixel Type: 2-bit unsigned integerData Coordinate System: NAD 1983 Albers (Contiguous US), WGS 1984 Albers (Alaska), Hawaii Albers (Hawaii)Mosaic Projection: North America Albers Equal Area ConicExtent: Alaska, Hawaii, and the Contiguous United States Source: National Insect Disease Risk MapPublication Date: 2018ArcGIS Server URL: https://landscape11.arcgis.com/arcgis/This layer was created from the 2018 version of the National Insect Disease Risk Map.What can you do with this Layer? This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "insects and disease" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "insects and disease" in the search box, browse to the layer then click OK.In ArcGIS Pro you can use raster functions to create your own custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro. For example, Zonal Statistics as Table tool can be used to summarize risk of tree mortality across several watersheds, counties, or other areas that you may be interested in such as areas near homes.In ArcGIS Online you can change then layer's symbology in the image display control, set the layer's transparency, and control the visible scale range.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.

In the United States, the federal government manages lands in significant parts of the country. These lands include 193 million acres managed by the US Forest Service in the nation's 154 National Forests and 20 National Grasslands, Bureau of Land Management lands that cover 247 million acres in Alaska and the Western United States, 150 million acres managed for wildlife conservation by the US Fish and Wildlife Service, 84 million acres of National Parks and other lands managed by the National Park Service and over 30 million acres managed by the Department of Defense. The Bureau of Reclamation manages a much smaller land base than the other agencies included in this layer but plays a critical role in managing the country's water resources.The agencies included in this layer are:Bureau of Land ManagementBureau of ReclamationDepartment of DefenseNational Park ServiceUS Fish and Wildlife ServiceUS Forest ServiceDataset SummaryPhenomenon Mapped: United States lands managed by six federal agencies Coordinate System: Web Mercator Auxiliary SphereExtent: 50 United States plus Puerto Rico, US Virgin Islands, Guam, American Samoa, and Northern Mariana Islands. The layer also includes National Monuments and Wildlife Refuges in the Pacific Ocean, Atlantic Ocean, and the Caribbean Sea.Visible Scale: The data is visible at all scales but draws best at scales greater than 1:2,000,000Source: BLM, DoD, USFS, USFWS, NPS, PADUS 2.1Publication Date: Various - Esri compiled and published this layer in May 2022. See individual agency views for data vintage.There are six layer views available that were created from this service. Each layer uses a filter to extract an individual agency from the service. For more information about the layer views or how to use them in your own project, follow these links:USA Bureau of Land Management LandsUSA Bureau of Reclamation LandsUSA Department of Defense LandsUSA National Park Service LandsUSA Fish and Wildlife Service LandsUSA Forest Service LandsWhat can you do with this Layer?This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "federal lands" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "federal lands" in the search box, browse to the layer then click OK.In both ArcGIS Online and Pro you can change the layer's symbology and view its attribute table. You can filter the layer to show subsets of the data using the filter button in Online or a definition query in Pro.The data can be exported to a file geodatabase, a shapefile or other format and downloaded using the Export Data button on the top right of this webpage.This layer can be used as an analytic input in both Online and Pro through the Perform Analysis window Online or as an input to a geoprocessing tool, model, or Python script in Pro.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.

Important Note: This item is in mature support as of September 2023 and will be retired in December 2025. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.The USGS Protected Areas Database of the United States (PAD-US) is the official inventory of public parks and other protected open space. The spatial data in PAD-US represents public lands held in trust by thousands of national, state and regional/local governments, as well as non-profit conservation organizations.GAP 1 and 2 areas are primarily managed for biodiversity, GAP 3 are managed for multiple uses including conservation and extraction, GAP 4 no known mandate for biodiversity protection. Provides a general overview of protection status including management designations. PAD-US is published by the U.S. Geological Survey (USGS) Science Analytics and Synthesis (SAS), Gap Analysis Project (GAP). GAP produces data and tools that help meet critical national challenges such as biodiversity conservation, recreation, public health, climate change adaptation, and infrastructure investment. See the GAP webpage for more information about GAP and other GAP data including species and land cover.The USGS Protected Areas Database of the United States (PAD-US) classifies lands into four GAP Status classes:GAP Status 1 - Areas managed for biodiversity where natural disturbances are allowed to proceedGAP Status 2 - Areas managed for biodiversity where natural disturbance is suppressedGAP Status 3 - Areas protected from land cover conversion but subject to extractive uses such as logging and miningGAP Status 4 - Areas with no known mandate for protectionIn the United States, areas that are protected from development and managed for biodiversity conservation include Wilderness Areas, National Parks, National Wildlife Refuges, and Wild & Scenic Rivers. Understanding the geographic distribution of these protected areas and their level of protection is an important part of landscape-scale planning. Dataset SummaryPhenomenon Mapped: Areas protected from development and managed to maintain biodiversity Coordinate System: Web Mercator Auxiliary SphereExtent: 50 United States plus Puerto Rico, the US Virgin Islands, the Northern Mariana Islands and other Pacific Ocean IslandsVisible Scale: 1:1,000,000 and largerSource: USGS Science Analytics and Synthesis (SAS), Gap Analysis Project (GAP) PAD-US version 3.0Publication Date: July 2022Attributes included in this layer are: CategoryOwner TypeOwner NameLocal OwnerManager TypeManager NameLocal ManagerDesignation TypeLocal DesignationUnit NameLocal NameSourcePublic AccessGAP Status - Status 1, 2, or 3GAP Status DescriptionInternational Union for Conservation of Nature (IUCN) Description - I: Strict Nature Reserve, II: National Park, III: Natural Monument or Feature, IV: Habitat/Species Management Area, V: Protected Landscape/Seascape, VI: Protected area with sustainable use of natural resources, Other conservation area, UnassignedDate of EstablishmentThe source data for this layer are available here. What can you do with this Feature Layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS OnlineAdd this layer to a map in the map viewer. The layer is limited to scales of approximately 1:1,000,000 or larger but a vector tile layer created from the same data can be used at smaller scales to produce a webmap that displays across the full range of scales. The layer or a map containing it can be used in an application.Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections and apply filters. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Change the layer’s style and filter the data. For example, you could set a filter for Gap Status Code = 3 to create a map of only the GAP Status 3 areas.Add labels and set their propertiesCustomize the pop-upArcGIS ProAdd this layer to a 2d or 3d map. The same scale limit as Online applies in ProUse as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class. Note that many features in the PAD-US database overlap. For example wilderness area designations overlap US Forest Service and other federal lands. Any analysis should take this into consideration. An imagery layer created from the same data set can be used for geoprocessing analysis with larger extents and eliminates some of the complications arising from overlapping polygons.Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of the Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

The National Hydrography Dataset Plus (NHDplus) maps the lakes, ponds, streams, rivers and other surface waters of the United States. Created by the US EPA Office of Water and the US Geological Survey, the NHDPlus provides mean annual and monthly flow estimates for rivers and streams. Additional attributes provide connections between features facilitating complicated analyses. For more information on the NHDPlus dataset see the NHDPlus v2 User Guide.Dataset SummaryPhenomenon Mapped: Surface waters and related features of the United States and associated territories not including Alaska.Coordinate System: Web Mercator Auxiliary Sphere Extent: The United States not including Alaska, Puerto Rico, Guam, US Virgin Islands, Marshall Islands, Northern Marianas Islands, Palau, Federated States of Micronesia, and American Samoa Visible Scale: Visible at all scales but layer draws best at scales larger than 1:1,000,000Resolution/Tolerance: 1 meter/2 meters Number of Features: 3,035,617 flowlines, 473,936 waterbodies, 16,658 sinksFeature Request Limit: 5,000Source: EPA and USGSPublication Date: March 13, 2019Prior to publication, the NHDPlus network and non-network flowline feature classes were combined into a single flowline layer. Similarly, the NHDPlus Area and Waterbody feature classes were merged under a single schema.Attribute fields were added to the flowline and waterbody layers to simplify symbology and enhance the layer's pop-ups. Fields added include Pop-up Title, Pop-up Subtitle, On or Off Network (flowlines only), Esri Symbology (waterbodies only), and Feature Code Description. All other attributes are from the original NHDPlus dataset. No data values -9999 and -9998 were converted to Null values for many of the flowline fields.What can you do with this Feature Layer?Feature layers work throughout the ArcGIS system. Generally your work flow with feature layers will begin in ArcGIS Online or ArcGIS Pro. Below are just a few of the things you can do with a feature service in Online and Pro.ArcGIS OnlineAdd this layer to a map in the map viewer. The layer is limited to scales of approximately 1:1,000,000 or larger but a vector tile layer created from the same data can be used at smaller scales to produce a webmap that displays across the full range of scales. The layer or a map containing it can be used in an application. Change the layer’s transparency and set its visibility rangeOpen the layer’s attribute table and make selections. Selections made in the map or table are reflected in the other. Center on selection allows you to zoom to features selected in the map or table and show selected records allows you to view the selected records in the table.Apply filters. For example you can set a filter to show larger streams and rivers using the mean annual flow attribute or the stream order attribute. Change the layer’s style and symbologyAdd labels and set their propertiesCustomize the pop-upUse as an input to the ArcGIS Online analysis tools. This layer works well as a reference layer with the trace downstream and watershed tools. The buffer tool can be used to draw protective boundaries around streams and the extract data tool can be used to create copies of portions of the data.ArcGIS ProAdd this layer to a 2d or 3d map. Use as an input to geoprocessing. For example, copy features allows you to select then export portions of the data to a new feature class. Change the symbology and the attribute field used to symbolize the dataOpen table and make interactive selections with the mapModify the pop-upsApply Definition Queries to create sub-sets of the layerThis layer is part of the ArcGIS Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

The US Fish and Wildlife Service manages the United States" 573 National Wildlife Refuges and thousands of small wetlands and other special management areas. These lands cover more than 150 million acres that protect fish, wildlife, plants, and their habitats.Dataset SummaryPhenomenon Mapped: United States lands managed by the US Fish and Wildlife ServiceGeographic Extent: 50 United States plus Puerto Rico, the US Virgin Islands, Guam, and the Northern Mariana Islands. The layer also includes Wildlife Refuges in the Pacific Ocean, Atlantic Ocean, and the Caribbean Sea.Data Coordinate System: WGS 1984Visible Scale: The data is visible at all scales.Source: USFWS Interest Simplified layerPublication Date: January 2024This layer is a view of the USA Federal Lands layer. A filter has been used on this layer to eliminate non-Fish and Wildlife Service lands. For more information on layers for other agencies see the USA Federal Lands layer.What can you do with this Layer?This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "fish and wildlife service" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box expand Portal if necessary then select Living Atlas. Type "fish and wildlife service" in the search box, browse to the layer then click OK.In both ArcGIS Online and Pro you can change the layer's symbology and view its attribute table. You can filter the layer to show subsets of the data using the filter button in Online or a definition query in Pro.The data can be exported to a file geodatabase, a shape file or other format and downloaded using the Export Data button on the top right of this webpage.This layer can be used as an analytic input in both Online and Pro through the Perform Analysis window Online or as an input to a geoprocessing tool, model, or Python script in Pro.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.Questions?Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.

One-eighth of the United States (247.3 million acres) is managed by the Bureau of Land Management. As part of the Department of the Interior, the agency oversees the 30 million acre National Landscape Conservation System, a collection of lands that includes 221 wilderness areas, 23 national monuments and 636 other protected areas. Bureau of Land Management Lands contain over 63,000 oil and gas wells and provide forage for over 18,000 grazing permit holders on 155 million acres of land. Dataset SummaryPhenomenon Mapped: United States lands managed by the Bureau of Land ManagementGeographic Extent: Contiguous United States and AlaskaData Coordinate System: WGS 1984Visible Scale: The data is visible at all scales but draws best at scales larger than 1:2,000,000.Source: BLM Surface Management Agency layer, Rasterized by Esri from features May 2025.Publication Date: December 2024This layer is a view of the USA Federal Lands layer. A filter has been used on this layer to eliminate non-Bureau of Land Management lands. For more information on layers for other agencies see the USA Federal Lands layer.What can you do with this layer?This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "bureau of land management" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box expand Portal if necessary then select Living Atlas. Type "bureau of land management" in the search box, browse to the layer then click OK.In both ArcGIS Online and Pro you can change the layer's symbology and view its attribute table. You can filter the layer to show subsets of the data using the filter button in Online or a definition query in Pro.The data can be exported to a file geodatabase, a shape file or other format and downloaded using the Export Data button on the top right of this webpage.This layer can be used as an analytic input in both Online and Pro through the Perform Analysis window Online or as an input to a geoprocessing tool, model, or Python script in Pro.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.Questions?Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.

Soil is the foundation of life on earth. More living things by weight live in the soil than upon it. It determines what crops we can grow, what structures we can build, what forests can take root.This layer contains the chemical soil variable organic carbon density (ocd) which measures carbon mass in proportion to volume of soil (mass divided by volume.)From Agriculture Victoria: Soil carbon provides a source of nutrients through mineralisation, helps to aggregate soil particles (structure) to provide resilience to physical degradation, increases microbial activity, increases water storage and availability to plants, and protects soil from erosion.This layer is a general, medium scale global predictive soil layer suitable for global mapping and decision support. In many places samples of soils do not exist so this map represents a prediction of what is most likely in that location. The predictions are made in six depth ranges by soilgrids.org, funded by ISRIC based in Wageningen, Netherlands.Each 250m pixel contains a value predicted for that area by soilgrids.org from best available data worldwide. Data for organic carbon density are provided at six depth ranges from the surface to 2 meters below the surface. Each variable and depth range may be accessed in the layer's multidimensional properties.Dataset SummaryPhenomenon Mapped: Organic carbon density in kg/m³Cell Size: 250 metersPixel Type: 32 bit float, converted from online data that is 16 Bit Unsigned IntegerCoordinate System: Web Mercator Auxiliary Sphere, projected via nearest neighbor from goode's homolosine land (250m)Extent: World land area except AntarcticaVisible Scale: All scales are visibleNumber of Columns and Rows: 160300, 100498Source: Soilgrids.orgPublication Date: May 2020Data from the soilgrids.org mean predictions for ocd were used to create this layer. You may access organic carbon density values in one of six depth ranges. To select one choose the depth variable in the multidimensional selector in your map client.Mean depth (cm)Actual depth range of data-2.50-5cm depth range-105-15cm depth range-22.515-30cm depth range-4530-60cm depth range-8060-100cm depth range-150100-200cm depth rangeWhat can you do with this Layer?This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map: In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "world soils soilgrids" in the search box and browse to the layer. Select the layer then click Add to Map. In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "world soils soilgrids" in the search box, browse to the layer then click OK.In ArcGIS Pro you can use the built-in raster functions or create your own to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro.Online you can filter the layer to show subsets of the data using the filter button and the layer's built-in raster functions.This layer is part of the Living Atlas of the World that provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.More information about soilgrids layersAnswers to many questions may be found at soilgrids.org (ISRIC) frequently asked questions (faq) page about the data.To make this layer, Esri reprojected the expected value of ISRIC soil grids from soilgrids' source projection (goode's land WKID 54052) to web mercator projection, nearest neighbor, to facilitate online mapping. The resolution in web mercator projection is the same as the original projection, 250m. But keep in mind that the original dataset has been reprojected to make this web mercator version.This multidimensional soil collection serves the mean or expected value for each soil variable as calculated by soilgrids.org. For all other distributions of the soil variable, be sure to download the data directly from soilgrids.org. The data are available in VRT format and may be converted to other image formats within ArcGIS Pro.Accessing this layer's companion uncertainty layerBecause data quality varies worldwide, the uncertainty of the predicted value varies worldwide. A companion uncertainty layer exists for this layer which you can use to qualify the values you see in this map for analysis. Choose a variable and depth in the multidimensional settings of your map client to access the companion uncertainty layer.

This layer is a subset of Global Landcover 1992- 2020 Layer. This layer is a time series of the annual ESA CCI (Climate Change Initiative) land cover maps of the world. ESA has produced land cover maps for the years 1992-2020. These are available at the European Space Agency Climate Change Initiative website.Time Extent: 1992-2020Cell Size: 300 meterSource Type: ThematicPixel Type: 8 Bit UnsignedData Projection: GCS WGS84Mosaic Projection: Web Mercator Auxiliary SphereExtent: GlobalSource: ESA Climate Change InitiativeUpdate Cycle: Annual until 2020, no updates thereafterWhat can you do with this layer?This layer may be added to ArcGIS Online maps and applications and shown in a time series to watch a "time lapse" view of land cover change since 1992 for any part of the world. The same behavior exists when the layer is added to ArcGIS Pro.In addition to displaying all layers in a series, this layer may be queried so that only one year is displayed in a map. This layer can be used in analysis. For example, the layer may be added to ArcGIS Pro with a query set to display just one year. Then, an area count of land cover types may be produced for a feature dataset using the zonal statistics tool. Statistics may be compared with the statistics from other years to show a trend.To sum up area by land cover using this service, or any other analysis, be sure to use an equal area projection, such as Albers or Equal Earth.Different Classifications Available to MapFive processing templates are included in this layer. The processing templates may be used to display a smaller set of land cover classes.Cartographic Renderer (Default Template)Displays all ESA CCI land cover classes.*Forested lands TemplateThe forested lands template shows only forested lands (classes 50-90).Urban Lands TemplateThe urban lands template shows only urban areas (class 190).Converted Lands TemplateThe converted lands template shows only urban lands and lands converted to agriculture (classes 10-40 and 190).Simplified RendererDisplays the map in ten simple classes which match the ten simplified classes used in 2050 Land Cover projections from Clark University.Any of these variables can be displayed or analyzed by selecting their processing template. In ArcGIS Online, select the Image Display Options on the layer. Then pull down the list of variables from the Renderer options. Click Apply and Close. In ArcGIS Pro, go into the Layer Properties. Select Processing Templates from the left hand menu. From the Processing Template pull down menu, select the variable to display.Using TimeBy default, the map will display as a time series animation, one year per frame. A time slider will appear when you add this layer to your map. To see the most current data, move the time slider until you see the most current year.In addition to displaying the past quarter century of land cover maps as an animation, this time series can also display just one year of data by use of a definition query. For a step by step example using ArcGIS Pro on how to display just one year of this layer, as well as to compare one year to another, see the blog called Calculating Impervious Surface Change.Hierarchical ClassificationLand cover types are defined using the land cover classification (LCCS) developed by the United Nations, FAO. It is designed to be as compatible as possible with other products, namely GLCC2000, GlobCover 2005 and 2009.This is a heirarchical classification system. For example, class 60 means "closed to open" canopy broadleaved deciduous tree cover. But in some places a more specific type of broadleaved deciduous tree cover may be available. In that case, a more specific code 61 or 62 may be used which specifies "open" (61) or "closed" (62) cover.Land Cover ProcessingTo provide consistency over time, these maps are produced from baseline land cover maps, and are revised for changes each year depending on the best available satellite data from each period in time. These revisions were made from AVHRR 1km time series from 1992 to 1999, SPOT-VGT time series between 1999 and 2013, and PROBA-V data for years 2013, 2014 and 2015. When MERIS FR or PROBA-V time series are available, changes detected at 1 km are re-mapped at 300 m. The last step consists in back- and up-dating the 10-year baseline LC map to produce the 24 annual LC maps from 1992 to 2015.Source dataThe datasets behind this layer were extracted from NetCDF files and TIFF files produced by ESA. Years 1992-2015 were acquired from ESA CCI LC version 2.0.7 in TIFF format, and years 2016-2018 were acquired from version 2.1.1 in NetCDF format. These are downloadable from ESA with an account, after agreeing to their terms of use. https://maps.elie.ucl.ac.be/CCI/viewer/download.phpCitationESA. Land Cover CCI Product User Guide Version 2. Tech. Rep. (2017). Available at: maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdfMore technical documentation on the source datasets is available here:https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-land-cover?tab=doc*Index of all classes in this layer:10 Cropland, rainfed11 Herbaceous cover12 Tree or shrub cover20 Cropland, irrigated or post-flooding30 Mosaic cropland (>50%) / natural vegetation (tree, shrub, herbaceous cover) (<50%)40 Mosaic natural vegetation (tree, shrub, herbaceous cover) (>50%) / cropland (<50%)50 Tree cover, broadleaved, evergreen, closed to open (>15%)60 Tree cover, broadleaved, deciduous, closed to open (>15%)61 Tree cover, broadleaved, deciduous, closed (>40%)62 Tree cover, broadleaved, deciduous, open (15-40%)70 Tree cover, needleleaved, evergreen, closed to open (>15%)71 Tree cover, needleleaved, evergreen, closed (>40%)72 Tree cover, needleleaved, evergreen, open (15-40%)80 Tree cover, needleleaved, deciduous, closed to open (>15%)81 Tree cover, needleleaved, deciduous, closed (>40%)82 Tree cover, needleleaved, deciduous, open (15-40%)90 Tree cover, mixed leaf type (broadleaved and needleleaved)100 Mosaic tree and shrub (>50%) / herbaceous cover (<50%)110 Mosaic herbaceous cover (>50%) / tree and shrub (<50%)120 Shrubland121 Shrubland evergreen122 Shrubland deciduous130 Grassland140 Lichens and mosses150 Sparse vegetation (tree, shrub, herbaceous cover) (<15%)151 Sparse tree (<15%)152 Sparse shrub (<15%)153 Sparse herbaceous cover (<15%)160 Tree cover, flooded, fresh or brakish water170 Tree cover, flooded, saline water180 Shrub or herbaceous cover, flooded, fresh/saline/brakish water190 Urban areas200 Bare areas201 Consolidated bare areas202 Unconsolidated bare areas210 Water bodies

This layer is a time series of the annual ESA CCI (Climate Change Initiative) land cover maps of the world. ESA has produced land cover maps for the years since 1992. These are available at the European Space Agency Climate Change Initiative website.Time Extent: 1992-2019Cell Size: 300 meterSource Type: ThematicPixel Type: 8 Bit UnsignedData Projection: GCS WGS84Mosaic Projection: Web Mercator Auxiliary SphereExtent: GlobalSource: ESA Climate Change InitiativeUpdate Cycle: AnnualWhat can you do with this layer?This layer may be added to ArcGIS Online maps and applications and shown in a time series to watch a "time lapse" view of land cover change since 1992 for any part of the world. The same behavior exists when the layer is added to ArcGIS Pro.In addition to displaying all layers in a series, this layer may be queried so that only one year is displayed in a map. This layer can be used in analysis. For example, the layer may be added to ArcGIS Pro with a query set to display just one year. Then, an area count of land cover types may be produced for a feature dataset using the zonal statistics tool. Statistics may be compared with the statistics from other years to show a trend.To sum up area by land cover using this service, or any other analysis, be sure to use an equal area projection, such as Albers or Equal Earth.Different Classifications Available to MapFive processing templates are included in this layer. The processing templates may be used to display a smaller set of land cover classes.Cartographic Renderer (Default Template)Displays all ESA CCI land cover classes.*Forested lands TemplateThe forested lands template shows only forested lands (classes 50-90).Urban Lands TemplateThe urban lands template shows only urban areas (class 190).Converted Lands TemplateThe converted lands template shows only urban lands and lands converted to agriculture (classes 10-40 and 190).Simplified RendererDisplays the map in ten simple classes which match the ten simplified classes used in 2050 Land Cover projections from Clark University.Any of these variables can be displayed or analyzed by selecting their processing template. In ArcGIS Online, select the Image Display Options on the layer. Then pull down the list of variables from the Renderer options. Click Apply and Close. In ArcGIS Pro, go into the Layer Properties. Select Processing Templates from the left hand menu. From the Processing Template pull down menu, select the variable to display.Using TimeBy default, the map will display as a time series animation, one year per frame. A time slider will appear when you add this layer to your map. To see the most current data, move the time slider until you see the most current year.In addition to displaying the past quarter century of land cover maps as an animation, this time series can also display just one year of data by use of a definition query. For a step by step example using ArcGIS Pro on how to display just one year of this layer, as well as to compare one year to another, see the blog called Calculating Impervious Surface Change.Hierarchical ClassificationLand cover types are defined using the land cover classification (LCCS) developed by the United Nations, FAO. It is designed to be as compatible as possible with other products, namely GLCC2000, GlobCover 2005 and 2009.This is a heirarchical classification system. For example, class 60 means "closed to open" canopy broadleaved deciduous tree cover. But in some places a more specific type of broadleaved deciduous tree cover may be available. In that case, a more specific code 61 or 62 may be used which specifies "open" (61) or "closed" (62) cover.CitationESA. Land Cover CCI Product User Guide Version 2. Tech. Rep. (2017). Available at: maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdfMore technical documentation on the source datasets is available here:https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-land-cover?tab=doc

This layer is a subset of Populated Footprint in 2020 Global Coverage for the Pacific Region. This layer represents an estimate of the footprint of human settlement in 2020. It is intended as a fast-drawing cartographic layer to augment base maps and to focus a map reader's attention on the location of human population. This layer is not intended for analysis.This layer was derived from the 2020 slice of the WorldPop Population Density 2000-2020 100m and 1km layers. WorldPop modeled this population footprint based on imagery datasets and population data from national statistical organizations and the United Nations. Zooming in to very large scales will often show discrepancies between reality and this or any model. Like all data sources imagery and population counts are subject to many types of error, thus this gridded footprint contains errors of omission and commission. The imagery base maps available in ArcGIS Online were not used in WorldPop's model. Imagery only informs the model of characteristics that indicate a potential for settlement, and cannot intrinsically indicate whether any or how many people live in a building. Also see the Urban Density Footprint layer, which like this layer, is intended to provide a fast-drawing cartographic context for urban populations.The following processing steps were used to produce this layer in ArcGIS Pro:1. Int tool (Spatial Analyst) to truncate double precision values; all values less than 0.99 become 0.2. Reclassify tool (Spatial Analyst) to set values 0 through 14 to NoData (Null) and all other values become 1. The figure of 14 was empirically derived as a good balance between reducing errors of commission, i.e., false-positive cells with lower values, while not introducing errors of omission by eliminating obviously populated cells.3. Copy Raster tool with Output Coordinate System environment set to Web Mercator, bit depth to 1 bit, and NoData Value to 0.Source:WorldPop Population Density 2000-2020 100m, which is created from WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation. The DOI for the original WorldPop.org total population population data is 10.5258/SOTON/WP00645.

Impervious surfaces are surfaces that do not allow water to pass through. Examples of these surfaces include highways, parking lots, rooftops, and airport runways. Instead of allowing rain to pass into the soil, impervious surfaces cause water to collect at the surface, then run off. An increase in impervious surface area causes an increase of water volume which needs to be managed by stormwater systems. With the flow come pollutants, which collect on impervious surfaces then discharge with the runoff into streams and the ocean. Runoff water does not enter the water table, and that can cause other management issues, such as interruptions in baseline stream flow.The NLCD imperviousness layer represents urban impervious surfaces as a percentage of developed surface over every 30-meter pixel in the United States. The layer is organized into a time series with years 2001, 2004, 2006, 2008, 2011, 2013, 2016, and 2019 for the lower 48 conterminous US states. This information may be used in conjunction with the USA NLCD Land Cover layer. Time SeriesBy default, this service will appear in your client with a time slider which allows you to play the series as an animation. The animation will advance year by year, but the layer only changes appearance every few years, in 2001, 2004, 2006, 2008, 2011, 2013, 2016, and 2019. To select just one year in the series, first turn the time series off on the time slider, then create a definition query on the layer which selects only the desired year.Time Series DescriptorMRLC issued a set of companion rasters with this impervious surface layer showing the reason why each pixel is impervious. This companion layer, called the Developed Imperviousness Descriptor, is not currently available in this map service. The descriptor layer identifies types of roads, core urban areas, and energy production sites for each impervious pixel to allow deeper analysis of developed features. The descriptor layer may be downloaded directly from MRLC and added to ArcGIS Pro.Alaska, Hawaii, and Puerto RicoAt this time Alaska, Hawaii, and Puerto Rico are not included in this time series. Only three years for a portion of Alaska around Anchorage are available from MRLC at this time. Furthermore, these rasters are produced with a different methodology, and are not set up to be directly compared the way the CONUS time series is. To analyze change between the latest two data years for this portion of Alaska, be sure to use the NLCD 2011 to 2016 Developed Impervious Change raster. For Hawaii and Puerto Rico, only the year 2001 is available for download at the MRLC.North America Albers ProjectionAll NLCD layers in the Living Atlas are projected into the North America Albers Projection before serving in the Living Atlas. This allows the coterminous USA, Puerto Rico, Hawaii, and Alaska to be served from a common projection and analyzed together. In tests performed by esri, the NLCD land cover classes after projection to North America Albers had the exact same number of pixels in input as output, but pixels had been slightly rearranged after projection.Processing TemplatesThis layer comes with two color schemes, cool and warm. The default is a cool gray color scheme, designed to look good on light and dark gray web maps. To choose a warm color scheme which was the default until 2021, change the processing template to the Impervious Surface Warm Renderer in your map client.Dataset SummaryPhenomenon Mapped: The proportion of the landscape that is impervious to waterUnits: PercentCell Size: 30 metersSource Type: DiscretePixel Type: Unsigned integerData Coordinate System: North America Albers Equal Area ConicExtent: Contiguous United StatesNoData Value: 127Source: Multi-Resolution Land Characteristics ConsortiumPublication Date: June 3, 2021ArcGIS Server URL: https://landscape10.arcgis.com/arcgis/The National Land Cover Database products are created through a cooperative project conducted by the Multi-Resolution Land Characteristics Consortium (MRLC). The MRLC Consortium is a partnership of federal agencies, consisting of the U.S. Geological Survey, the National Oceanic and Atmospheric Administration, the U.S. Environmental Protection Agency, the U.S. Department of Agriculture, the U.S. Forest Service, the National Park Service, the U.S. Fish and Wildlife Service, the Bureau of Land Management and the USDA Natural Resources Conservation Service.What can you do with this layer?This layer can be used to create maps and to visualize the underlying data. This layer can be used as an analytic input in ArcGIS Desktop.This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

Data CitationPlease cite this dataset as follows:Vasquez, V., Cushman, K., Ramos, P., Williamson, C., Villareal, P., Gomez Correa, L. F., & Muller-Landau, H. (2023). Barro Colorado Island 50-ha plot crown maps: manually segmented and instance segmented. (Version 2). Smithsonian Tropical Research Institute. https://doi.org/10.25573/data.24784053This data is licensed as CC BY 4.0 and is thus freely available for reuse with proper citation. We ask that data users share any resulting publications, preprints, associated analysis code, and derived data products with us by emailing mullerh@si.edu. We are open to contributing our expert knowledge of the study site and datasets to projects that use these data; please direct queries regarding potential collaboration to Vicente Vasquez, vasquezv@si.edu, and Helene Muller-Landau, mullerh@si.edu.Note that this dataset is part of a collection of Panama UAV data on Smithsonian Figshare, which can be viewed at https://smithsonian.figshare.com/projects/Panama_Forest_Landscapes_UAV/115572Additional information about this research can be found at the Muller-Landau lab web site at https://hmullerlandau.com/All required code is freely available at https://github.com/P-polycephalum/ForestLandscapes/blob/main/LandscapeScripts/segmentation.py and it can be cited as:Vicente Vasquez. (2023). P-polycephalum/ForestLandscapes: segmentwise (v0.0.2-beta). Zenodo. https://doi.org/10.5281/zenodo.10380517Data DescriptionThis dataset is part of a larger initiative monitoring forests in Panama using drones (unoccupied aerial vehicles), an initiative led by Dr. Helene Muller-Landau at the Smithsonian Tropical Research Institute. As part of this initiative, we have been collecting repeat imagery of the 50-ha forest dynamics plot on Barro Colorado Island (BCI), Panama, since October 2014 (see Garcia et al. 2021a, b for data products for 2014-2019).Contained within this dataset are two sets of field-derived crown maps, presented in both their raw and improved versions. The 2021 crown mapping campaign was overseen by KC Cushman, accompanied by field technician Pablo Ramos and Paulino Villarreal. Additionally, Cecilia Williamson and KC Cushman reviewed polygon quality and made necessary corrections. Image data occurred on August 1, 2020, utilizing a DJI Phantom 4 Pro at a resolution of 4cm per pixel. A total of 2454 polygons were manually delineated, encompassing insightful metrics like crown completeness and liana load.The 2023 crown mapping campaign, led by Vicente Vasquez and field technicians Pablo Ramos, Paulino Villarreal, involved quality revisions and corrections performed by Luisa Fernanda Gomez Correa and Vicente Vasquez. Image data collection occurred on September 29, 2022, utilizing a DJI Phantom 4 Pro drone at a 4cm per pixel resolution. The 2023 campaign integrated model 230103_randresize_full of the detectree2 model garden (Ball, 2023). Tree crown polygons were generated pre-field visit, with those attaining a field validation score of 7 or higher retained as true tree crowns.The data collection forms are prepared using ArcGIS field maps. The creator of the data forms uses the spatial points from the trees in the ForestGeo 50-ha censuses to facilitate finding the tree tags in the field (Condit et al., 2019). The field technicians confirm that the tree crown is visible from the drone imagery, they proceed to collect variables of interest and delineate the tree crown manually. In the case of the 2023 field campaign, the field technicians were able to skip manual delineation when the polygons generated by 230103_randresize_full were evaluated as true detection.The improved version of the 2023 and 2021 crown map data collection takes as input the raw crown maps and the globally aligned orthomosaics to refine the edges of the crown. We use the model SAM from segment-anything module developed my Meta AI (Krillov, 2023). We adapted the use of their instance segmentation algorithm to take geospatial imagery in the form of tiles. We inputted multiple bounding boxes in the form of CPU torch tensors for each of the files. Furthermore, we perform several tasks to clean the crowns and remove the polygons overlaps to avoid ambiguity. This results in a very well delineated crown map with no overlapping between tree crowns. Despite our diligent efforts in detecting, delineating, and evaluating all visible tree crowns from drone imagery, this dataset exhibits certain limitations. These include missing tags denoted as -9999, erroneous manual delineations or instance segmentation of tree crown polygons, duplicated tags, and undetected tree crowns. These limitations are primarily attributed to human error, logistical constraints, and the challenge of confirming individual tree crown emergence above the canopy. In numerous instances, particularly within densely vegetated areas, delineating polygons and assigning tags to numerous small trees posed significant challenges.MetadataThe dataset comprises four sets of crown maps bundled within .zip files, adhering to the naming convention MacroSite_plot_year_month_day_crownmap_type. As an illustration, a sample file name follows the structure: BCI_50ha_2020_08_01_improved.For a comprehensive understanding of variable nomenclature within each shapefile, exhaustive details are provided in the file named variables_description.csv. Additionally, our dataset incorporates visualization figures corresponding to both raw and refined crown maps.The raw crown maps contain:A GeoTiff-formatted raster image reflecting the image acquisition date during field data collection.The tiles folder housing all tiles utilized for instance segmentation.The most recent version of the raw crown map manually revised and retaining its original naming scheme.A reformatted iteration of the raw crown map, involving column renaming and the reprojection of its coordinate reference system.The improved crown maps contain:"_crownmap_segmented.shp" version: This subproduct has all polygons segmented via the SAM model from the segment-anything process."_crownmap_cleaned.shp" version: This subproduct features one polygon allocated per GlobalID, specifically the one with the highest segment-anything score."_crownmap_avoidance.shp" version: This subproduct is devoid of any overlapping polygons."_crownmap_improved.shp" version: The outcome of the instance crown segmentation workflow, incorporating all original crown map fields.Author contributionsVV wrote the code for standardized workflow for processing, alignment, and segmentation of the tree crowns. MG and MH led the drone imagery collection. HCM conceived the study, wrote the grant proposals to obtain funding, and supervised the research.AcknowledgmentsVicente Vasquez and KC Cushman created the field map forms and coordinated the 2023 and 2021 crown map field campaign. Milton Solano assistance with the ArcGIS platform. Field technicians Pablo Ramos, Paulino Villareal, and Melvin Hernandez delineated and evaluated tree crown polygons. Luisa Gomez-Correa and Cecilia Williamson assisted with quality assurance and quality control after field data collection. Milton Garcia and additional interns in the Muller-Landau lab assisted with drone data collection. Funding and/or in-kind support was provided by the Smithsonian Institution Scholarly Studies grant program (HCM), the Smithsonian Institution Equipment fund (HCM), Smithsonian ForestGEO, the Smithsonian Tropical Research Institute.ReferencesBall, J.G.C., Hickman, S.H.M., Jackson, T.D., Koay, X.J., Hirst, J., Jay, W., Archer, M., Aubry-Kientz, M., Vincent, G. and Coomes, D.A. (2023), Accurate delineation of individual tree crowns in tropical forests from aerial RGB imagery using Mask R-CNN. Remote Sens Ecol Conserv. 9(5):641-655. https://doi.org/10.1002/rse2.332Condit, Richard et al. (2019). Complete data from the Barro Colorado 50-ha plot: 423617 trees, 35 years [Dataset]. Dryad. https://doi.org/10.15146/5xcp-0d46Garcia, M., J. P. Dandois, R. F. Araujo, S. Grubinger, and H. C. Muller-Landau. 2021b. Surface elevation models and associated canopy height change models for the 50-ha plot on Barro Colorado Island, Panama, for 2014-2019. . In Smithsonian Figshare, edited by S. T. R. Institute. https://doi.org/10.25573/data.14417933Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A. C., Lo, W.-Y., Dollár, P., & Girshick, R. (2023). Segment Anything. arXiv preprint arXiv:2304.02643.Scheffler D, Hollstein A, Diedrich H, Segl K, Hostert P. AROSICS: An Automated and Robust Open-Source Image Co-Registration Software for Multi-Sensor Satellite Data. Remote Sensing. 2017; 9(7):676.

The US National Park Service manages 84.4 million acres that include the nation's 59 national parks, many national monuments, and other conservation and historical properties. These lands range from the 13 million acre Wrangell-St. Elias National Park and Preserve in Alaska to the 0.02 acre Thaddeus Kosciuszko National Memorial in Pennsylvania.Dataset SummaryPhenomenon Mapped: Administrative boundaries of units in the United States National Park Service system. Not all lands within the administrative boundaries are owned by the National Park Service.Coordinate System: Web Mercator Auxiliary SphereExtent: 50 United States, District of Columbia, Puerto Rico, US Virgin Islands, Guam, American Samoa, and Northern Mariana IslandsVisible Scale: The data is visible at all scalesSource: NPS Administrative Boundaries National Park System Units layerPublication Date: January 2024This layer is a view of the USA Federal Lands layer. A filter has been used on this layer to eliminate non-Park Service lands. For more information on layers for other agencies see the USA Federal Lands layer.What can you do with this layer? This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "national park service" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box expand Portal if necessary then select Living Atlas. Type "national park service" in the search box, browse to the layer then click OK.In both ArcGIS Online and Pro you can change the layer's symbology and view its attribute table. You can filter the layer to show subsets of the data using the filter button in Online or a definition query in Pro.The data can be exported to a file geodatabase, a shape file or other format and downloaded using the Export Data button on the top right of this webpage.This layer can be used as an analytic input in both Online and Pro through the Perform Analysis window Online or as an input to a geoprocessing tool, model, or Python script in Pro.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.

In the United States, the federal government manages approximately 28% of the land in the United States. Most federal lands are west of the Mississippi River, where almost half of the land by area is managed by the federal government. Federal lands include 193 million acres managed by the US Forest Service in 154 National Forests and 20 National Grasslands, Bureau of Land Management lands that cover 247 million acres in Alaska and the Western United States, 150 million acres managed for wildlife conservation by the US Fish and Wildlife Service, 84 million acres of National Parks and other lands managed by the National Park Service, and over 30 million acres managed by the Department of Defense. The Bureau of Reclamation manages a much smaller land base than the other agencies included in this layer but plays a critical role in managing the country's water resources. The agencies included in this layer are:Bureau of Land ManagementDepartment of DefenseNational Park ServiceUS Fish and Wildlife ServiceUS Forest ServiceDataset SummaryPhenomenon Mapped: United States federal lands managed by six federal agenciesGeographic Extent: 50 United States and the District of Columbia, Puerto Rico, US Virgin Islands, Guam, American Samoa, and Northern Mariana Islands. The layer also includes National Monuments and Wildlife Refuges in the Pacific Ocean, Atlantic Ocean, and the Caribbean Sea.Data Coordinate System: WGS 1984Visible Scale: The data is visible at all scales but draws best at scales greater than 1:2,000,000Source: BLM, DOD, USFS, USFWS, NPS, PADUS 3.0Publication Date: Various - Esri compiled and published this layer in May 2025. See individual agency views for data vintage.There are six layer views available that were created from this service. Each layer uses a filter to extract an individual agency from the service. For more information about the layer views or how to use them in your own project, follow these links:USA Bureau of Land Management LandsUSA Department of Defense LandsUSA National Park Service LandsUSA Fish and Wildlife Service LandsUSA Forest Service LandsWhat can you do with this Layer?This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "federal lands" in the search box and browse to the layer. Select the layer then click Add to Map.In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "federal lands" in the search box, browse to the layer then click OK.In both ArcGIS Online and Pro you can change the layer's symbology and view its attribute table. You can filter the layer to show subsets of the data using the filter button in Online or a definition query in Pro.The data can be exported to a file geodatabase, a shapefile or other format and downloaded using the Export Data button on the top right of this webpage.This layer can be used as an analytic input in both Online and Pro through the Perform Analysis window Online or as an input to a geoprocessing tool, model, or Python script in Pro.The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.Questions?Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.