(Mature Support) This item is in mature support and is no longer updated. Available for historical reference only. Please visit njgin.nj.gov/edata/elevation for the latest information on elevation products available for download. This is a GIS polygon layer defining the geographic extents for all the LiDAR projects and DEM products in New Jersey. This layer was derived from the original LiDAR extents layer generated by NJDEP 20161230. Features were created from tile extents, project-specific boundaries provided in the deliverables, and county boundaries. Attributes were populated from LiDAR project metadata and fact sheets.

Raw lidar data consist of positions (x, y) and intensity values. They must undergo a classification process before individual points can be identified as belonging to ground, building, vegetation, etc., features. By completing this tutorial, you will become comfortable with the following skills:Converting .zlas files to .las for editing,Reassigning LAS class codes,Using automated lidar classification tools, andUsing 2D and 3D features to classify lidar data.Software Used: ArcGIS Pro 3.3Time to Complete: 60 - 90 minutesFile Size: 57mbDate Created: September 25, 2020Last Updated: September 27, 2024

Latest LIDAR Projects required for statewide within New York State. More information for existing LIDAR collections can be found at https://gis.ny.gov/lidar. Last updated 9/5/25. Feature and map services available:https://elevation.its.ny.gov/arcgis/rest/services/indexes/Latest_LiDAR_Collections/FeatureServer https://elevation.its.ny.gov/arcgis/rest/services/indexes/Latest_LiDAR_Collections/MapServer For Historic Collections, see:https://elevation.its.ny.gov/arcgis/rest/services/indexes/Historic_LiDAR_Collections/FeatureServer https://elevation.its.ny.gov/arcgis/rest/services/indexes/Historic_LiDAR_Collections/MapServer Please contact nysgis@its.ny.gov if you have any questions.

Lidar (light detection and ranging) imagery provides valuable information in the field of remote sensing, allowing users to determine elevation, vegetation structure, and terrain with remarkable levels of detail. This manual will lead ArcGIS Pro users through the tools and methods needed to access, process, and analyze lidar data through a series of step-by-step tutorials. By completing this series of tutorials, you will be able to: •Manipulate data to create maps and map templates in ArcGIS Pro •Obtain and display lidar imagery •Use ArcGIS Pro tools to process and analyze lidar data •Classify lidar points using different classification methods • Process lidar point clouds to create digital elevation models

Detroit Street View (DSV) is an urban remote sensing program run by the Enterprise Geographic Information Systems (EGIS) Team within the Department of Innovation and Technology at the City of Detroit. The mission of Detroit Street View is ‘To continuously observe and document Detroit’s changing physical environment through remote sensing, resulting in freely available foundational data that empowers effective city operations, informed decision making, awareness, and innovation.’ LiDAR (as well as panoramic imagery) is collected using a vehicle-mounted mobile mapping system.

Due to variations in processing, index lines are not currently available for all existing LiDAR datasets, including all data collected before September 2020. Index lines represent the approximate path of the vehicle within the time extent of the given LiDAR file. The actual geographic extent of the LiDAR point cloud varies dependent on line-of-sight.

Compressed (LAZ format) point cloud files may be requested by emailing gis@detroitmi.gov with a description of the desired geographic area, any specific dates/file names, and an explanation of interest and/or intended use. Requests will be filled at the discretion and availability of the Enterprise GIS Team. Deliverable file size limitations may apply and requestors may be asked to provide their own online location or physical media for transfer.

LiDAR was collected using an uncalibrated Trimble MX2 mobile mapping system. The data is not quality controlled, and no accuracy assessment is provided or implied. Results are known to vary significantly. Users should exercise caution and conduct their own comprehensive suitability assessments before requesting and applying this data.

Sample Dataset: https://detroitmi.maps.arcgis.com/home/item.html?id=69853441d944442f9e79199b57f26fe3

Click here to access the data directly from the Illinois State Geospatial Data Clearinghouse. These lidar data are processed Classified LAS 1.4 files, formatted to 2,117 individual 2500 ft x 2500 ft tiles; used to create Reflectance Images, 3D breaklines and hydro-flattened DEMs as necessary. Geographic Extent: Lake county, Illinois covering approximately 466 square miles. Dataset Description: WI Kenosha-Racine Counties and IL 4 County QL1 Lidar project called for the Planning, Acquisition, processing and derivative products of lidar data to be collected at a derived nominal pulse spacing (NPS) of 1 point every 0.35 meters. Project specifications are based on the U.S. Geological Survey National Geospatial Program Base Lidar Specification, Version 1.2. The data was developed based on a horizontal projection/datum of NAD83 (2011), State Plane, U.S Survey Feet and vertical datum of NAVD88 (GEOID12B), U.S. Survey Feet. Lidar data was delivered as processed Classified LAS 1.4 files, formatted to 2,117 individual 2500 ft x 2500 ft tiles, as tiled Reflectance Imagery, and as tiled bare earth DEMs; all tiled to the same 2500 ft x 2500 ft schema. Ground Conditions: Lidar was collected April-May 2017, while no snow was on the ground and rivers were at or below normal levels. In order to post process the lidar data to meet task order specifications and meet ASPRS vertical accuracy guidelines, Ayers established a total of 66 ground control points that were used to calibrate the lidar to known ground locations established throughout the WI Kenosha-Racine Counties and IL 4 County QL1 project area. An additional 195 independent accuracy checkpoints, 116 in Bare Earth and Urban landcovers (116 NVA points), 79 in Tall Grass and Brushland/Low Trees categories (79 VVA points), were used to assess the vertical accuracy of the data. These checkpoints were not used to calibrate or post process the data. Users should be aware that temporal changes may have occurred since this dataset was collected and that some parts of these data may no longer represent actual surface conditions. Users should not use these data for critical applications without a full awareness of its limitations. Acknowledgement of the U.S. Geological Survey would be appreciated for products derived from these data. These LAS data files include all data points collected. No points have been removed or excluded. A visual qualitative assessment was performed to ensure data completeness. No void areas or missing data exist. The raw point cloud is of good quality and data passes Non-Vegetated Vertical Accuracy specifications.Link Source: Illinois Geospatial Data Clearinghouse

This shaded relief image was generated from the lidar-based bare-earth digital elevation model (DEM). A shaded relief image provides an illustration of variations in elevation using artificial shadows. Based on a specified position of the sun, areas that would be in sunlight are highlighted and areas that would be in shadow are shaded. In this instance, the position of the sun was assumed to be 45 degrees above the northwest horizon.The shaded relief image shows areas that are not in direct sunlight as shadowed. It does not show shadows that would be cast by topographic features onto the surrounding surface.Using ERDAS IMAGINE, a 3X3 neighborhood around each pixel in the DEM was analyzed, and a comparison was made between the sun's position and the angle that each pixel faces. The pixel was then assigned a value between -1 and +1 to represent the amount of light reflected. Negative numbers and zero values represent shadowed areas, and positive numbers represent sunny areas. In ArcGIS Desktop 10.7.1, the image was converted to a JPEG 2000 format with values from 0 (black) to 255 (white).See the MassGIS datalayer page to download the data as a JPEG 2000 image file.View this service in the Massachusetts Elevation Finder.MassGIS has also published a Lidar Shaded Relief tile service (cache) hosted in ArcGIS Online.

These lidar data are processed classified LAS 1.4 files at USGS QL2 covering the District of Columbia. Voids exist in the data due to data redaction conducted under the guidance of the United States Secret Service. This dataset provided as an ArcGIS Image service. Please note, the download feature for this image service in Open Data DC provides a compressed PNG, JPEG or TIFF. The individual LAS point cloud datasets are available under additional options when viewing downloads.

On November 7, 2021, NV5 collected Quality Level 1 (QL1) lidar data across the preliminary CAL FIRE defined fire perimeter for the CZU lightning complex fire in San Mateo and Santa Cruz counties. The technical report for the lidar data collection is available here: https://fuelsmapping.com/czu_postfire_lidar_report From the QL1 postfire lidar, NV5 and Tukman Geospatial developed a set of derivatives. These derivatives are a Digital Terrain Model (DTM), a Digital Surface Model (DSM), a Hillshade derived from the DTM, a lidar intensity image, a Normalized Digital Surface Model (nDSM), a Canopy Cover raster, and a lidar intensity image. The derivatives will be used to study the effects of the CZU wildfire on the natural landscape, forests, and shrublands of Santa Cruz and San Mateo Counties. The lidar derivatives are provided as GeoTiffs available for download from ArcGIS Online and as dynamic image services. Table 1 provides more information (including download information) for the derivatives produced. The GeoTiffs can be used in desktop GIS software packages such as ArcGIS Pro and ERDAS Imagine; the image services can be used in web maps and web mapping applications by both GIS users and non-GIS users. Table 1. lidar derivatives for the CZU lightning fire footprint in San Mateo and Santa Cruz Counties

  Dataset


  Description


  Link to GeoTiff


  Link to Image Service






  Digital Terrain Model (DTM)


  Hydroflattened digital terrain model. Pixel values represent elevation above sea level of the ground.


  https://vegmap.press/czu_postfire_dtm_tif


  https://vegmap.press/czu_postfire_dtm




  Digital Surface Model (DSM)


  Pixel values in the DSM represent elevations above sea level of the ‘highest hit’ surface. The DSM provides elevation above sea level of the top of the tree canopy, the top of buildings, and the top of other features.


  https://vegmap.press/czu_postfire_dsm_tif


  https://vegmap.press/czu_postfire_dsm




  Hillshade


  The hillshade is derived from the DTM and provides a ‘shaded relief’ visualization of the earth’s surface.


  https://vegmap.press/czu_postfire_hillshade_tif


  https://vegmap.press/czu_postfire_hillshade




  Lidar Intensity


  Lidar intensity, scaled to 8-bit resolution.


  https://vegmap.press/czu_postfire_intensity_tif


  https://vegmap.press/czu_postfire_lidar_intensity




  Normalized Digital Surface Model (nDSM)


  In the nDSM, pixel values represent the maximum normalized height in feet of features such as vegetation and structures. For areas with aboveground features, pixel values represent the aboveground height of the tallest part of the feature in the 3x3 foot pixel. For areas with no aboveground features, the nDSM has pixel values of 0. 


  https://vegmap.press/czu_postfire_nDSM_tif


  https://vegmap.press/czu_postfire_nDSM




  Canopy Height Model


  The canopy height model is the normalized digital surface model, with building footprints and a small buffer surrounding them set to 0 normalized height. Building footprint data came from the prefire CHM. The datasheet for the prefire CHM is available here: https://vegmap.press/sc_chm As such, this raster mostly represents the aboveground height of the vegetation canopy.  Note that it also includes some noise (e.g., powerlines and other objects that are not vegetation), as well as some structures that weren't captured as building footprints.


  https://vegmap.press/czu_postfire_chm_tif


  https://vegmap.press/czu_postfire_chm




  Canopy Cover


  This is the Canopy Height Model, thresholded to show pixel values greater than or equal to 15 feet aboveground as 1, and all other areas as 0. As such, it is a proxy for tree canopy cover. 


  https://vegmap.press/czu_postfire_cc_tif


  https://vegmap.press/czu_postfire_cc

Related Datasets: The QL1 point cloud, from which these deliverables were acquired, is available as laz files. The laz files are downloadable by tile. See this datasheet for more information: CZU postfire QL1 point cloudCZU postfire 4-band imagery

Product: These lidar data are processed Classified LAS 1.4 files, formatted to 23,381 individual 2,500 ft x 2,500 ft tiles; used to create intensity images, 3D breaklines and hydro-flattened DEMs as necessary. Geographic Extent: CT Statewide covering approximately 5,241 square miles. Dataset Description: CT Statewide GIS Services Lidar project called for the Planning, Acquisition, proces...

This data subset contains1. a subset of spatial data (gis layers for the California Madera County and NEON SOAP and SJER sites). 2. Some other general spatial boundary layers from natural earth3. NEON lidar data and insitu measurements for SOAP and SJER sites. The data are used in both the Earth Analytics R and python courses. The Lidar data can be used to teach uncertainty given there are ground measurements available.

Virginia LiDARThe Virginia LiDAR Inventory Web Mapping Application provides access to LiDAR point cloud and individual project metadata collected in the Commonwealth of Virginia according to the USGS 3DEP specification. Data is obtained from NOAA and USGS data portals. LiDAR Point Clouds are compressed for file storage and transfer. Informational Access Type:1) LiDAR Project Metadata: To download individual LiDAR project Metadata, click on a LiDAR inventory polygon for link to the host FTP site. Once at the host site, locate appropriate directory and .zip file to receive project documentation and accompanying project files. For use within ArcGIS, the geospatial grid and inventory data powering the VGIN LiDAR download inventory services can be downloaded under conversion and analysis resources below.2) LiDAR Point Clouds (Single): To download individual tiles, zoom in on the map until the tile grid appears. The VGIN Composite Geocoding service is available to use when querying by physical address, feature, or community anchor institution name. Click a tile to identify grid information for individual LiDAR Point clouds. Columns note where the LiDAR is hosted and what format is available for download. In many instances, multiple results are returned due to multiple file formats and flight years. If LiDAR data is missing spatial reference information please refer to the metadata in step 1 above. Tile grids are stacked so you will need to scroll through selections:3) LiDAR Point Clouds (Bulk): To download multiple files in a single FTP directory folder, which can be a necessity in many instances, consider the use of a multi-file download manager plugin to use with your browser in conjunction with the URLs provided on the LiDAR inventory polygon. If LiDAR data is missing spatial reference information please refer to the metadata in step 1 above. For use within ArcGIS, the geospatial grid and inventory data powering the VGIN LiDAR Download Inventory Services can be downloaded under conversion and resources below.Conversion and Resources:Convert to LAS from USGS/NOAA hosted .LAZ filesDownload LiDAR Inventory Data Project FootprintsDownload LiDAR Inventory Tile GridContact:For questions about the data please contact USGS For questions about the application please contact vbmp@vdem.virginia.gov

Sangamon Data:

• Sangamon Aquarius Hillshade U 1m HS - Green Lidar. 1 meter Hillshade including canopy. QA/QC: By NCALM.

• Sangamon Aquarius Hillshade F 1m HS - Green Lidar. 1 meter Hillshade of topography, no canopy. QA/QC: By NCALM.

• Sangamon Waveform CSD Digitizer - Green Lidar. Raw Full Waveform Lidar data. QA/QC: None.

• Sangamon LAS Tiles Classified Final - Green Lidar. Classified point cloud data in 1000x1000 meter tiles. QA/QC: By NCALM.

• Sangamon ESRI AQ - Green Lidar. DEM data with and without canopy. QA/QC: By NCALM.

• Sangamon Gemini Waveform - Near Infra-red (NIR) Lidar. Raw Full Waveform Lidar data. QA/QC: None.

• Sangamon Hyperspectral Data - Hyperspectral Lidar data. QA/QC: QAed no QC.

Historic LIDAR Projects within New York State. New York State has access to and distributes many of the older LIDAR collections within New York State. These historic projects have been fully replaced with more recent LIDAR projects. More information for existing LIDAR collections can be found at https://gis.ny.gov/lidar. Last updated 8/2/24.Feature and map services available:https://elevation.its.ny.gov/arcgis/rest/services/indexes/Historic_LiDAR_Collections/FeatureServerhttps://elevation.its.ny.gov/arcgis/rest/services/indexes/Historic_LiDAR_Collections/MapServerFor Latest Collections, see:https://elevation.its.ny.gov/arcgis/rest/services/indexes/Latest_LiDAR_Collections/FeatureServerhttps://elevation.its.ny.gov/arcgis/rest/services/indexes/Latest_LiDAR_Collections/MapServerPlease contact nysgis@its.ny.gov if you have any questions.

Tiles of datasets available for the MOA 2015 Photography and Lidar

The District of Columbia government requires a comprehensive range of GIS data and photogrammetric mapping to support a wide variety of applications through the DC GIS program. Due to technology advances, expanding user base needs, and aging data, DC GIS acquired new LIDAR data in spring 2015 to establish a more thorough and better quality core LIDAR dataset The LiDAR data products are suitable for 1 foot (or less) contour generation. Intensity images generated from the RPC data for the DC OCTO 2015 LiDAR project covering approximately 80 square miles, in which its extents cover Arlington County in Washington DC. Intensity is a measure, collected for every point, of the return strength of the laser pulse that generated the point. It is based, in part, on the reflectivity of the object struck by the laser pulse. This project consists of deliverables in accordance with USGS v1.2 specifications and meets or exceeds the level of quality for QL1 (8 points per meter).

Urban green spaces are closely related to the abundance and biodiversity of birds by providing important habitats and together contribute to ecosystem health. This project aims to guide the University of British Columbia Botanical Garden to create Bird-friendly green spaces by using LiDAR data to analyze and map UBCBG's bird habitat suitability and create a 3D digital twin model of UBCBG in the open source game engine Minetest to increase 3D visualization and aid in landscape planning. By extracting the Canopy Height Model (CHM) using LiDAR data and performing individual tree segmentation, the derived metrics were used to identify trees with the highest bird habitat suitability index. The results showed that the suitability index ranges from -0.0016 to 0.5187, with a mean value of 0.2051. There are 68 trees with high suitability above the 0.4 intervals which have significance to bird populations and are worthy of being protected, accounting for only 3.38% of the total trees. They usually have a low vertical complexity index and foliage height diversity but are characterized by very tall trees with relatively large tree crowns. The Digital Elevation Model (DEM), Canopy Height Model (CHM) generated by LiDAR data were visualized in Minetest's UBCBG's 3D digital twin model using real terrain mod as topography and vegetation layers, while bird habitat suitability was used to symbolize the tree canopy layer. This study is highly relevant for landscape adaptation and planning in conjunction with other management considerations to support bird-friendly green spaces. The digital twin model can be used for educational and promotional purposes, and for landscape planning and aesthetic design with the consideration of bird conservation.

Digital Elevation Model from Lidar (2013-2021), with values in meters and feet. Image service published by MassGIS from ArcGIS Server.The DEM was created from Light Detection and Ranging (Lidar) terrain and elevation data that cover the entirety of Massachusetts. This DEM is based on the best available lidar data, as described at the Lidar Terrain Data page. The DEM is a 16-bit signed integer raster dataset and has a 0.5 meter pixel resolution.This image service is the source for the values appearing in the popup in the Massachusetts Elevation Finder application.

This zip file contains LIDAR, Digital Terrain Models (DTM's), surface, and breakline datasets covering the extent of Peoria County. The LIDAR data was captured during spring leaf-off in 2008. There are eight databases in Esri's file geodatabase format which are broken down by eight areas in the County. The DTM's conform to the ASPRS Class I Standards using the Illinois State Plane West coordinate system. Please contact us if you would like a copy of the data.More recent LIDAR data for Peoria County, IL was captured in 2012 by the State of Illinois through the Illinois Height Modernization Program (ILHMP). Please click Here to read about the program and data available for download.Contact InformationPeoria County GISEmail: gis@peoriacounty.orgPhone: 309-495-4840This data is bound to the Peoria County GIS Open Data License Agreement which can be found here: https://data-peoriacountygis.opendata.arcgis.com/pages/peoria-county-gis-open-data-license-agreement.

Digital Surface Model - 1m resolution. The dataset contains the 1m Digital Surface Model for the District of Columbia. These lidar data are processed classified LAS 1.4 files at USGS QL1 covering the District of Columbia. Some areas have limited data. The lidar dataset redaction was conducted under the guidance of the United States Secret Service. All data returns were removed from the dataset within the United States Secret Service redaction boundary except for classified ground points and classified water points.