This data collection of the 3D Elevation Program (3DEP) consists of Lidar Point Cloud (LPC) projects as provided to the USGS. These point cloud files contain all the original lidar points collected, with the original spatial reference and units preserved. These data may have been used as the source of updates to the 1/3-arcsecond, 1-arcsecond, and 2-arcsecond seamless 3DEP Digital Elevation Models (DEMs). The 3DEP data holdings serve as the elevation layer of The National Map, and provide foundational elevation information for earth science studies and mapping applications in the United States. Lidar (Light detection and ranging) discrete-return point cloud data are available in LAZ format. The LAZ format is a lossless compressed version of the American Society for Photogrammetry and Remote Sensing (ASPRS) LAS format. Point Cloud data can be converted from LAZ to LAS or LAS to LAZ without the loss of any information. Either format stores 3-dimensional point cloud data and point attributes along with header information and variable length records specific to the data. Millions of data points are stored as a 3-dimensional data cloud as a series of geo-referenced x, y coordinates and z (elevation), as well as other attributes for each point. Additonal information about the las file format can be found here: https://www.asprs.org/divisions-committees/lidar-division/laser-las-file-format-exchange-activities. All 3DEP products are public domain.

Lidar point cloud data with classifications – unclassified (1), ground (2), low vegetation (3), medium vegetation (4), high vegetation (5), buildings (6), low point - noise (7), reserved – model keypoint (8), high noise (18).

This dataset contains linework of lineaments mapped on 4 <1-m-resolution lidar datasets and the 10-m-resolution National Elevation Dataset digital elevation models in the Pit River region of northeastern California. Lineaments are classified by confidence in tectonic origin, map certainty, and the ages of the bedrock and surficial deposits they cross.

Digital Surface Model (DSM) has three layers. Two layers come from the rasterisation of the building and vegetation classes among all the points of the LiDAR file .las; and the third layer is the hydrography of the Geographical Reference Information. By applying a suitable colour for each layer, the final product is visualised. ECW file format. ETRS89 reference geodetic system (in the Canary Islands REGCAN95, compatible with ETRS89) and EPSG projection: 3857 throughout the national territory

This web map allows for the download of KyFromAbove LiDAR data by 5k tile in LAZ format. This point cloud data was acquired during the typical leaf-off acquisition period (winter-spring) over a period of several years and may be provided as LAS version 1.1, 1.2, or 1.4 depending upon the acquisition period. Users will need to download the LAZIP.exe in order to decompress each tile. LiDAR data specifications adopted by the KyFromAbove Technical Advisory Committee can be found here. This is the source data used to create the Commonwealth's 5 foot digital elevation model (DEM) and its associated derivatives. More information regarding this data resource can be found on the KyGeoPortal.

The LIDAR Composite DTM (Digital Terrain Model) is a raster elevation model covering ~99% of England at 1m spatial resolution. The DTM (Digital Terrain Model) is produced from the last or only laser pulse returned to the sensor. We remove surface objects from the Digital Surface Model (DSM), using bespoke algorithms and manual editing of the data, to produce a terrain model of just the surface.

Produced by the Environment Agency in 2022, the DTM is derived from a combination of our Time Stamped archive and National LIDAR Programme surveys, which have been merged and re-sampled to give the best possible coverage. Where repeat surveys have been undertaken the newest, best resolution data is used. Where data was resampled a bilinear interpolation was used before being merged.

The 2022 LIDAR Composite contains surveys undertaken between 6th June 2000 and 2nd April 2022. Please refer to the metadata index catalgoues which show for any location which survey was used in the production of the LIDAR composite.

The data is available to download as GeoTiff rasters in 5km tiles aligned to the OS National grid. The data is presented in metres, referenced to Ordinance Survey Newlyn and using the OSTN’15 transformation method. All individual LIDAR surveys going into the production of the composite had a vertical accuracy of +/-15cm RMSE.

LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. Using a combination of laser rangefinding, GPS positioning and inertial measurement technologies; LIDAR instruments are able to make highly detailed Digital Elevation Models (DEMs) of the earth's terrain, man-made structures and vegetation. This data was collected at submeter resolution to provide nominal 1m spacing of collected points. Two returns were recorded for each pulse in addition to an intensity value. Original contact information: Contact Org: NOAA Office for Coastal Management Phone: 843-740-1202 Email: coastal.info@noaa.gov

Map displays LiDAR grids in region to assist with ordering LiDAR data. Background imagery used in this map is Esri's World Imagery service and is not indicative of LiDAR products for sale by H-GAC. To order individual tiles or entire sets of LiDAR data from H-GAC, please visit the H-GAC LiDAR Imagery website.

This is a 2-m shaded relief map for Kansas created using LiDAR coverage for the state mostly current as of 10-Feb-2018.

This dataset is a footprint of the current available LiDAR data over for the State of Queensland compiled from numerous LiDAR projects captured on or after the year 2008.

This resource contains Lidar-DEM collection status shapefiles from the Texas Natural Resources Information System (TNRIS) [http://tnris.org]. November 2023 updates: this year, TNRIS changed its name to Texas Geographic Information Office (TxGIO). The domain name hasn't changed yet, but the data hub is continually evolving. See [1], [2] for current downloadable data.

For purposes of Hurricane Harvey studies, the 1-m DEM for Harris County (2008) has also been uploaded here as a set of 4 zipfiles containing the DEM in tiff files. See [1] for a link to the current elevation status map and downloadable DEMs.
Project name: H-GAC 2008 1m Datasets: 1m Point Cloud, 1M Hydro-Enforced DEM, 3D Breaklines, 1ft and 5ft Contours Points per sq meter: 1 Total area: 3678.56 sq miles Source: Houston-Galveston Area Council (H-GAC) Acquired by: Merrick, QA/QC: Merrick Catalog: houston-galveston-area-council-h-gac-2008-lidar

References: [1] TNRIS/TxGIO StratMap elevation data [https://tnris.org/stratmap/elevation-lidar/] [2] TNRIS/TxGIO DataHub [https://data.tnris.org/]

Many Ontario lidar point cloud datasets have been made available for direct download by the Government of Canada through the federal Open Government Portal under the LiDAR Point Clouds – CanElevation Series record. Instructions for bulk data download are available in the Download Instructions document linked from that page. To download individual tiles, zoom in on the map in GeoHub and click a tile for a pop-up containing a download link. See the LIO Support - Large Data Ordering Instructions to obtain a copy of data for projects that are not yet available for direct download. Data can be requested by project area or a set of tiles. To determine which project contains your area of interest or to view single tiles, zoom in on the map above and click. For bulk tile orders follow the link in the Additional Documentation section below to download the tile index. Data sizes by project area are listed below. The Ontario Point Cloud (Lidar-Derived) consists of points containing elevation and intensity information derived from returns collected by an airborne topographic lidar sensor. The minimum point cloud classes are Unclassified, Ground, Water, High and Low Noise. The data is structured into non-overlapping 1-km by 1-km tiles in LAZ format. This dataset is a compilation of lidar data from multiple acquisition projects, as such specifications, parameters, accuracy and sensors vary by project. Some projects have additional classes, such as vegetation and buildings. See the detailed User Guide and contractor metadata reports linked below for additional information, including information about interpreting the index for placement of data orders. Raster derivatives have been created from the point clouds. These products may meet your needs and are available for direct download. For a representation of bare earth, see the Ontario Digital Terrain Model (Lidar-Derived). For a model representing all surface features, see the Ontario Digital Surface Model (Lidar-Derived). You can monitor the availability and status of lidar projects on the Ontario Lidar Coverage map on the Ontario Elevation Mapping Program hub page. Additional DocumentationOntario Classified Point Cloud (Lidar-Derived) - User Guide (DOCX) Ontario Classified Point Cloud (Lidar-Derived) - Tile IndexOntario Lidar Project Extents (SHP) OMAFRA Lidar 2016-18 - Cochrane - Additional Metadata (PDF)OMAFRA Lidar 2016-18 - Peterborough - Additional Metadata (PDF)OMAFRA Lidar 2016-18 - Lake Erie - Additional Metadata (PDF)CLOCA Lidar 2018 - Additional Contractor Metadata (PDF)South Nation Lidar 2018-19 - Additional Contractor Metadata (PDF)OMAFRA Lidar 2022 - Lake Huron - Additional Metadata (PDF)OMAFRA Lidar 2022 - Lake Simcoe - Additional Metadata (PDF)Huron-Georgian Bay Lidar 2022-23 - Additional Metadata (Word)Kawartha Lakes Lidar 2023 - Additional Metadata (Word)Sault Ste Marie Lidar 2023-24 - Additional Metadata (Word)Thunder Bay Lidar 2023-24 - Additional Metadata (Word)Timmins Lidar 2024 - Additional Metadata (Word) OMAFRA Lidar Point Cloud 2016-18 - Cochrane - Lift Metadata (SHP)OMAFRA Lidar Point Cloud 2016-18- Peterborough - Lift Metadata (SHP)OMAFRA Lidar Point Cloud 2016-18 - Lake Erie - Lift Metadata (SHP)CLOCA Lidar Point Cloud 2018 - Lift Metadata (SHP)South Nation Lidar Point Cloud 2018-19 - Lift Metadata (SHP)York-Lake Simcoe Lidar Point Cloud 2019 - Lift Metadata (SHP)Ottawa River Lidar Point Cloud 2019-20 - Lift Metadata (SHP)OMAFRA Lidar Point Cloud 2022 - Lake Huron - Lift Metadata (SHP)OMAFRA Lidar Point Cloud 2022 - Lake Simcoe - Lift Metadata (SHP)Eastern Ontario Lidar Point Cloud 2021-22 - Lift Medatadata (SHP)DEDSFM Huron-Georgian Bay Lidar Point Cloud 2022-23 - Lift Metadata (SHP)DEDSFM Kawartha Lakes Lidar Point Cloud 2023 - Lift Metadata (SHP)DEDSFM Sault Ste Marie Lidar Point Cloud 2023-24 - Lift Metadata (SHP)DEDSFM Sudbury Lidar Point Cloud 2023-24 - Lift Metadata (SHP)DEDSFM Thunder Bay Lidar Point Cloud 2023-24 - Lift Metadata (SHP)DEDSFM Timmins Lidar Point Cloud 2024 - Lift Metadata (SHP)DEDSFM Cataraqui Lidar Point Cloud 2024 - Lift Metadata (SHP)DEDSFM Chapleau Lidar Point Cloud 2024 - Lift Metadata (SHP)DEDSFM Dryden Lidar Point Cloud 2024 - Lift Metadata (SHP)DEDSFM Ignace Lidar Point Cloud 2024 - Lift Metadata (SHP)DEDSFM Sioux Lookout Lidar Point Cloud 2024 - Lift Metadata (SHP)DEDSFM Northeastern Ontario Lidar Point Cloud 2024 - Lift Metadata (SHP)DEDSFM Atikokan Lidar Point Cloud 2024 - Lift Metadata (SHP)GTA 2023 - Lift Metadata (SHP) Data Package SizesLEAP 2009 - 22.9 GBOMAFRA Lidar 2016-18 - Cochrane - 442 GBOMAFRA Lidar 2016-18 - Lake Erie - 1.22 TBOMAFRA Lidar 2016-18 - Peterborough - 443 GBGTA 2014 - 57.6 GBGTA 2015 - 63.4 GBBrampton 2015 - 5.9 GBPeel 2016 - 49.2 GBMilton 2017 - 15.3 GBHalton 2018 - 73 GBCLOCA 2018 - 36.2 GBSouth Nation 2018-19 - 72.4 GBYork Region-Lake Simcoe Watershed 2019 - 75 GBOttawa River 2019-20 - 836 GBLake Nipissing 2020 - 700 GBOttawa-Gatineau 2019-20 - 551 GBHamilton-Niagara 2021 - 660 GBOMAFRA Lidar 2022 - Lake Huron - 204 GBOMAFRA Lidar 2022 - Lake Simcoe - 154 GBBelleville 2022 - 1.09 TBEastern Ontario 2021-22 - 1.5 TBHuron Shores 2021 - 35.5 GBMuskoka 2018 - 72.1 GBMuskoka 2021 - 74.2 GBMuskoka 2023 - 532 GBDigital Elevation Data to Support Flood Mapping 2022-26:Huron-Georgian Bay 2022 - 1.37 TBHuron-Georgian Bay 2023 - 257 GBHuron-Georgian Bay 2023 Bruce - 95.2 GBKawartha Lakes 2023 - 385 GBSault Ste Marie 2023-24 - 1.15 TBSudbury 2023-24 - 741 GBThunder Bay 2023-24 - 654 GBTimmins 2024 - 318 GBCataraqui 2024 - 50.5 GBChapleau 2024 - 127 GBDryden 2024 - 187 GBIgnace 2024 - 10.7 GBNortheastern Ontario 2024 - 82.3 GBSioux Lookout 2024 - 112 GBAtikokan 2024 - 64 GBGTA 2023 - 985 GB StatusOn going: Data is continually being updated Maintenance and Update FrequencyAs needed: Data is updated as deemed necessary ContactOntario Ministry of Natural Resources - Geospatial Ontario, geospatial@ontario.ca

The link: Access the data directory is available in the section*Dataset Description Sheets; Additional Information*. The dendrometric lidar map presents various dendrometric characteristics useful in particular in forest planning. It is a product in vector format that is complementary to the results of forest compilations found in the Original Ecoforest Map and Current Inventory Results and in the Results of forest compilations by forel. The geometric entities defined from the lidar data are at a finer scale than those in the ecoforest map. The main variables predicted and accessible in the product are as follows: + Usable volume per hectare by species, species group and certain diameter groups + Volume per hectare distributed by product for certain species groups + Basal area and number of stems per hectare for certain species groups for certain species groups + Average usable volume per stem and average diameter for certain species groups The volumes compiled in the lidar dendrometric map are variables distinct from the gross volume per hectare for certain species groups + Average usable volume per stem and average diameter for certain species groups The volumes compiled in the lidar dendrometric map are variables distinct from the gross volume per merchant on Predicted foot in others results of forest compilations, in the Tariff of cubing and prediction models and for the stems counted in the sample plots of the ecoforestry inventory of southern Quebec, for example in the Temporary sample plots of the fifth inventory. This distinct volume is here qualified as “usable” and it excludes woody material between 9.1 cm in diameter without bark and 9.1 cm with bark. The published literature clarifies the differences between volume variables. This product is available for territories (planning unit, private forest development agency or residual forest territory) with a lidar acquisition and affecting the bioclimatic domains of fir to yellow birch, fir to white birch and spruce moss. Product coverage is not complete and will evolve over the years depending on lidar acquisition. _ ⚠️ Notes: _ It is possible to use the lidar dendrometric data preparation tool to study one or more sectors at a finer scale than that of the ecoforest map. The Lidar dendrometric tool user guide presents the methodology for its application to meet the needs of operational forest harvest planning.**This third party metadata element was translated using an automated translation tool (Amazon Translate).**

Note: The files can be downloaded from the Attachments section below. Please note that the total size is 180GB, so the download may take some time depending on your system’s capabilities and configuration. You can also visit https://finder.nyc.gov/orthoimagery to download raw LiDAR data for specific tiles. Topographic and bathymetric LiDAR data was collected for New York City in 2017. Topographic data was collected for the entire city, plus an additional 100 meter buffer, using a Leica ALS80 sensor equipped to capture at least 8 pulse/m2. Dates of capture for topographic data were between 05/03/2017 and 05/17/2017 during 50% leaf-off conditions. Bathymetric data was collected in select areas of the city (where bathymetric data capture was expected) using a Riegl VQ-880-G sensor equipped to capture approximately 15 pulses/m2 (1.5 Secchi depths). Dates of capture for bathymetric were between 07/04/2017 - 07/26/2017. LiDAR data was tidally-coordinated and captured between mean lower low water (+30% of mean tide) ranges. The horizontal datum for all datasets is NAD83, the vertical datum is NAVD88, Geoid 12B, and the data is projected in New York State Plane - Long Island. Units are in US Survey Feet. To learn more about these datasets, visit the interactive “Understanding the 2017 New York City LiDAR Capture” Story Map -- https://maps.nyc.gov/lidar/2017/ Please see the following link for additional documentation on this dataset -- https://github.com/CityOfNewYork/nyc-geo-metadata/blob/master/Metadata/Metadata_LiDAR_Summary.md

Zoom in on the map above and click your area of interest or use the Tile Index linked below to determine which package(s) you require for download.The DTM data is available in the form of 1-km by 1-km non-overlapping tiles grouped into packages for download.This dataset is a compilation of lidar data from multiple acquisition projects, as such specifications, parameters and sensors may vary by project. See the detailed User Guide linked below for additional information.You can monitor the availability and status of lidar projects on the Ontario Lidar Coverage map on the Ontario Elevation Mapping Program hub page. Now also available through a web service which exposes the data for visualization, geoprocessing and limited download. The service is best accessed through the ArcGIS REST API, either directly or by setting up an ArcGIS server connection using the REST endpoint URL. The service draws using the Web Mercator projection. For more information on what functionality is available and how to work with the service, read the Ontario Web Raster Services User Guide. If you have questions about how to use the service, email Geospatial Ontario (GEO) at geospatial@ontario.ca.Service Endpointshttps://ws.geoservices.lrc.gov.on.ca/arcgis5/rest/services/Elevation/Ontario_DTM_LidarDerived/ImageServerhttps://intra.ws.geoservices.lrc.gov.on.ca/arcgis5/rest/services/Elevation/Ontario_DTM_LidarDerived/ImageServer (Government of Ontario Internal Users)Additional Documentation Ontario DTM (Lidar-Derived) - User Guide (DOCX) OMAFRA Lidar 2016-2018 - Cochrane - Additional Contractor Metadata (PDF)OMAFRA Lidar 2016-2018 - Peterborough - Additional Contractor Metadata (PDF)OMAFRA Lidar 2016-2018 - Lake Erie - Additional Contractor Metadata (PDF)CLOCA Lidar 2018 - Additional Contractor Metadata (PDF)South Nation Lidar 2018-19 - Additional Contractor Metadata (PDF)OMAFRA Lidar 2022 - Lake Huron - Additional Contractor Metadata (PDF)OMAFRA Lidar 2022 - Lake Simcoe - Additional Contractor Metadata (PDF)Huron-Georgian Lidar 2022-23 - Additional Contractor Metadata (Word)Kawartha Lakes Lidar 2023 - Additional Contractor Metadata (Word)Sault Ste Marie Lidar 2023-24 - Additional Contractor Metadata (Word)Thunder Bay Lidar 2023-24 - Additional Contractor Metadata (Word)Timmins Lidar 2024 - Additional Contractor Metadata (Word) Ontario DTM (Lidar-Derived) - Tile Index (SHP)Ontario Lidar Project Extents (SHP) OMAFRA Lidar DTM 2016-2018 - Cochrane - Breaklines (SHP)OMAFRA Lidar DTM 2016-2018 - Peterborough - Breaklines (SHP)OMAFRA Lidar DTM 2016-2018 - Lake Erie - Breaklines (SHP)CLOCA Lidar DTM 2018 - Breaklines (SHP)South Nation Lidar DTM 2018-19 - Breaklines (SHP)Ottawa-Gatineau Lidar DTM 2019-20 - Breaklines (SHP)OMAFRA Lidar DTM 2022 - Lake Huron - Breaklines (SHP)OMAFRA Lidar DTM 2022 - Lake Simcoe - Breaklines (SHP)Eastern Ontario Lidar DTM 2021-22 - Breaklines (SHP)Muskoka Lidar DTM 2018 - Breaklines CGVD2013 (SHP) / CGVD28 (SHP)Muskoka Lidar DTM 2021 - Breaklines CGVD2013 (SHP) / CGVD28 (SHP)Muskoka Lidar DTM 2023 - Breaklines CGVD2013 (SHP) / CGVD28 (SHP)DEDSFM Huron-Georgian Bay 2022-23 - Breaklines (SHP)DEDSFM Kawartha Lakes 2023 - Breaklines (SHP)DEDSFM Sault Ste Marie 2023-24- UTM16 - Breaklines (SHP)DEDSFM Sault Ste Marie 2023-24- UTM17 - Breaklines (SHP)DEDSFM Sudbury 2023-24 - Breaklines (SHP)DEDSFM Thunder Bay 2023-24 - Breaklines (SHP)DEDSFM Timmins 2024 - Breaklines (SHP)DEDSFM Cataraqui 2024 - Breaklines (SHP)DEDSFM Chapleau 2024 - Breaklines (SHP)DEDSFM Dryden 2024 - Breaklines (SHP)DEDSFM Ignace 2024 - Breaklines (SHP)DEDSFM Sioux Lookout 2024 - Breaklines (SHP)DEDSFM Northeastern Ontario 2024 - Breaklines (SHP)DEDSFM Atikokan 2024 - Breaklines (SHP)Product PackagesDownload links for the Ontario DTM (Lidar-Derived) (Word)Projects:LEAP 2009GTA 2014-18OMAFRA 2016-18CLOCA 2018South Nation CA 2018-19Muskoka 2018-23York-Lake Simcoe 2019Ottawa River 2019-20Ottawa-Gatineau 2019-20Lake Nipissing 2020Hamilton-Niagara 2021Huron Shores 2021Eastern Ontario 2021-22OMAFRA Lake Huron 2022OMAFRA Lake Simcoe 2022Belleville 2022Digital Elevation Data to Support Flood Mapping 2022-26Huron-Georgian Bay 2022-23Kawartha Lakes 2023Sault Ste Marie 2023-24Sudbury 2023-24Thunder Bay 2023-24Timmins 2024Cataraqui 2024Chapleau 2024Dryden 2024Ignace 2024Northeastern Ontario 2024Sioux Lookout 2024Atikokan 2024Greater Toronto Area Lidar 2023StatusOn going: Data is continually being updatedMaintenance and Update FrequencyAs needed: Data is updated as deemed necessaryContactOntario Ministry of Natural Resources - Geospatial Ontario, geospatial@ontario.ca

This web map provides an index for ​identifying subsets of LiDAR data acquired for the greater metropolitan Phoenix region in 2014 via a (non-3DEP) USGS LiDAR program.Two index layers are included in this web map: (1) Point Cloud Index, (2) Raster Index. Another layer, Maricopa County Municipalities, is included as an additional geographic reference aid. LiDAR Point Cloud Index The Point Cloud Index layer indexes the raw LiDAR point cloud data (available in las/laz file formats). Each tile's file name can be identified by clicking on a particular tile.DEM Raster IndexThe Raster Index layer indexes the LiDAR-derived bare earth digital elevation model (DEM) surface data (available in tif file format). Users can click on a particular tile within the index to identify its ID.Once you have identified your file name or ID of interest, please submit a quick service request through the Map and Geospatial Hub's Service Request Form.Technical SpecificationsHorizontal Projection: UTM 12N WGS 84 (meters)Vertical Datum: NAVD 1988 (meters) Geoid 12APoint Spacing (minimum): 0.5 m / 1.64 ftAbove Ground Level (AGL) average flight height: 1700 m / 5,579 ftMean Sea Level (MSL) average flying height: 1981 m / 6500 ftAverage Ground Speed: 140 knots / 161 mphField of View (full): 28 degreesPulse Rate: 312.2 kHzScan Rate: 54.8 HzSide Lap (Minimum): 25%

This metadata record describes the lidar point cloud data encompassing Southern New Jersey, collected as 2 areas of interest through the USGS projects titled 'NJ South 4-County' and 'NJ South FEMA' by the Sanborn Map Company, Inc. NOAA's Office for Coastal Management retrieved the data from the USGS' rockyftp website and processed it to the Digital Coast.

Product: These lidar data are process...

This data release consists of three child items distinguishing the following types of data: light detection and ranging (lidar) point clouds (LPCs), digital elevation models (DEMs), and snow depth raster maps. These three data types are all derived from lidar data collected on small, uncrewed aircraft systems (sUAS) at study areas in the Upper Colorado River Basin, Colorado, from 2020 to 2022. These data were collected and generated as part of the U.S. Geological Survey's (USGS) Next Generation Water Observing Systems (NGWOS) Upper Colorado River Basin project.

During the Fall of 2016 AGRC and the Utah Geological Survey acquired ~205 square miles of 8 points per meter Quality Level 1 LiDAR of The Frontier Observatory for Research in Geothermal Energy (FORGE) area around Milford, Utah in Beaver and Millard Counties in western Utah. The 0.5 meter resolution bare earth DEMs and first-return/highest-hit DSMs in .img format have a 10.0cm vertical RMSE accuracy and are available for download. The LAS classified point clouds are also available by request Rick Kelson from AGRC at RKelson@utah.gov or The National Map. This elevation data was collected between October 26 and November 3, 2016 and has a UTM NAD83 (2011) zone 12 north meter NAVD88(GEOID12) projection.

LiDAR elevation data that can be downloaded by selections of tiles using individual, box graphic, polygon graphic, or by GIS polygon features.

Constraints:
Not to be used for navigation, for informational purposes only. See full disclaimer for more information.