OpenTopography is a distributor of free high-resolution, Earth science-oriented topographic data, related tools, and resources. For more information, visit the About section.
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You do not need an OpenTopography account to access and process lidar datasets. However, registering for an OpenTopography account has the following advantages:
1. Access to a personalized workspace.
2. Real-time status updates for your lidar jobs.
3. Access to previously submitted point cloud jobs.
4. Overview of point cloud processing statistics from your lidar jobs.
Log in to your myOpenTopo account and click the "Update Profile / Change Password" link under "My Account".
After filling out the registration form, you will be sent a confirmation notice to the email address provided. Click the link provided in the confirmation email to activate your account. Check your spam inbox if you cannot find the e-mail right away. if you still have trouble logging in to your myOpenTopo account, please email us at firstname.lastname@example.org
All outlines indicate areas that have lidar coverage and are discoverable via OpenTopography. Areas outline in red represent data available through OpenTopography for download. Yellow outlines are data that have been contributed to OpenTopography through the Community Contributed Data feature. If you zoom in, the dots become polygons indicating lidar data coverage.
You can view images representing the digital elevation model (DEMs) as hillshades (where the DEM is artificially illuminated) on your home computer using Google Earth. For more specialized work a geographic information system (GIS) is needed (e.g.ArcGIS, Fledermaus, or GlobalMapper). These programs let you interact with and analyze the elevation data.
No. Lidar data are available for many regions covering various Earth science-related disciplines such as hydrology, biology, and geomorphology. Please visit our Data page for a complete list of lidar datasets available on OpenTopography.
Currently, two datasets on OpenTopography have concurrent orthoimagery
The B4 dataset had orthophotos collected concurrently with the lidar survey. However, they are not available through OpenTopography because they were not acquired with a true photogrammetric camera and thus require additional processing. High-resolution aerial imagery is available via the U.S. Department of Agriculture National Agriculture Imagery Program (NAIP).
At present, OpenTopography does not host full waveform lidar data because the community we serve have not yet taken delivery of these data. However, OpenTopography is working with NASA full waveform lidar sensors (LVIS and GLAS) as part of the NASA Lidar Access System (NLAS). OpenTopography's long-term research goals include incorporating full waveform lidar data as part of our community support. For more information on waveform lidar data, visit the NASA LVIS and Pulse Waves Google group pages.
From the data page, zoom in to the area of interest highlighted on the map using the navigation bars on the left. When you are close enough, click the blue "Select a Region" button below the zoom bar. Left-click and drag your mouse to create a box over your area of interest. Once you've selected the area, a list of available datasets and product formats for that area will appear below the map. Click the datasets product format and navigate to the dataset landing page. Beside each step in the workflow, there is a grey "?" which has more information about the data products and concepts applied in that step.
Visit our Tutorials & Videos page for comprehensive OpenTopography guides and tutorials.
Lidar topographic data processed and delivered as a standard digital elevation model (DEM) at the optimum resolution for the dataset often fit many users' needs. These data are typically delivered as bare earth (ground) and full feature (all returns) surfaces organized into tiles (e.g. 1 km2). The DEMs are in a GIS-compatible format and are compressed (zipped) to reduce their size.
Point cloud data are the first result from the laser scanner and may be the laser returns from the canopy, structures, and Earth's surface and are thus x,y,z points plus attributes. Creating a custom DEM from point cloud data lets the user define the area of interest and set the DEM-processing parameters which allows for more versatility and greater control over the dataset.
Visit our Tutorials & Videos page for comprehensive OpenTopography guides and tutorials.
OpenTopography distributes some data as "tarballs," which is specific compressed file format with the extension ".tar.gz". A ".tar.gz" file is a compressed archive file format similar to the more familiar .ZIP. OpenTopography writes out custom DEM data and point cloud files as .tar.gz files to make the files smaller and therefore convenient to download. Files downloaded from OpenTopography will look something like this: 1266365984583406150039.tar.gz, where the long number string is a unique identifier for the job, and the .tar.gz indicates that it is a .tar file compressed with gzip compression. To work with a custom DEM product produced in OpenTopography, you first need to uncompress the .tar.gz file to access the .arc.asc (the actual DEM) file which can be imported into a GIS.
There are several programs you can use to unzip lidar data. We generally use WinRAR since it is free and can handle a variety of compressed formats. The native Windows compression utility will not work on the tar.gz files. Other decompression programs include 7-Zip and IZArc.
After clicking the "Download Google Earth Hillshades," Google Earth should open automatically (Google Earth needs to be installed for this to work). If Google Earth does not take you to your area of interest automatically, check the access window on the left-hand side of the screen. The new file should be under "Places." Click the box next to the file to turn it on and then zoom in to the area of interest on the map.
One of OpenTopography's primary goals is to democratize the distribution of lidar data to the Earth science community. For OpenTopography to achieve this, the collective needs of Earth science community must be made known to OpenTopography. For example, what are some aspects of lidar technology in terms of data discovery, access, and integration prevent the Earth science community from being able to carry out research in an efficient and timely manner? What new lidar tools and datasets does the Earth science community feel the need to be developed/made available? We invite members of the Earth science community to provide us with feedback that we hope will help shape the future of OpenTopography. Contact us for more information.
The OpenTopography Tool Registry provides a community-populated clearinghouse of software, utilities, and tools oriented towards handling, processing, and analysis of lidar data. Registered tools range from source code to full-featured software applications. We welcome contributions to the registry via the Contribute a Tool page.
OpenTopography data can be downloaded in LAS, LAZ or ASCII file formats. The following list describes each dataset type.
LAS: (from ASPRS: "The LAS file format is a public file format for the interchange of 3-dimensional point cloud data between data users. Although developed primarily for exchange of lidar point cloud data, this format supports the exchange of any 3-dimensional x,y,z tuplet. This binary file format is an alternative to proprietary systems or a generic ASCII file interchange system used by many companies. The problem with proprietary systems is obvious in that data cannot be easily taken from one system to another. There are two major problems with the ASCII file interchange. The first problem is performance because the reading and interpretation of ASCII elevation data can be very slow and the file size can be extremely large, even for small amounts of data. The second problem is that all information specific to the lidar data is lost. The LAS file format is a binary file format that maintains information specific to the lidar nature of the data while not being overly complex."
LAZ: The compressed form of a LAS file.
ASCII: Stands for American Standard Code for Information Interchange. ASCII files are text files containing information about the points in a dataset organized into columns. To define a point cloud, ASCII files must have x,y, and z point columns. The ASCII format is not unique to 3-dimensional point cloud data.
All datasets available via OpenTopography are multiple returns. Depending on the dataset, you can choose to download and produce DEMs for: bare earth points, vegetation returns, structure returns, or all returns. We retain all attributes for the datasets that we host, so if you choose to download the point cloud data you will find attribution for classification as well as return number. Intensity is occasionally available as well. To find out more about the classification of a specific dataset, access the full metadata and survey reports.
Up to four returns can be recorded for each laser pulse. The "number_of_returns" attribute is the total returns for a pulse (up to a maximum of 4). The "return_number" attribute is assigned as a number from 1 to 7 in a scheme that identifies which return is the last return recorded for a pulse:
First return with subsequent returns detected.
Second return with subsequent returns detected.
Third return with subsequent returns detected.
First return with no subsequent returns detected.
Second return with no subsequent returns detected.
Third return with no subsequent returns detected.
You should not expect each set of returns to have the same x and y position because the laser scanner is only perfectly vertical (at nadir) once per scan. For the rest of the scan the laser is pointing off nadir and hence the laser pulse passes obliquely through vegetation and will result in different x and y positions for returns from the same outgoing pulse. It is important to keep in mind that the point cloud is composed of multiple passes of the scanner over a survey area and therefore when you download points from OpenTopography, you are getting a merged point cloud back that represents all returns for the area you selected.
"Pulse number" is another way of saying collection time. Typically, each lidar point has an attribute indicating when the point was collected (in GPS time) in addition to the x,y, and z value. Sorting the data by collection time can be useful for identifying the geometry of the data acquisition, amount of swath overlap, and places where you may have edge artifacts from swath edges.
A digital elevation model (DEM) is a gridded representation of the surface of the ground with regular spacing between the nodes (sometimes called the resolution). A DEM may also be referred to as a digital terrain model (DTM) or a digital surface model (DSM).
Widely available DEMs are typically too coarse to provide adequate representation of small features (for example, the cell sizes in most USGS DEMs are 10-30 meters on a side). DEMs created from lidar datasets have a much higher resolution (often sub-meter), which allows the user to see more details of the landscape. They permit us to represent the landscape at the appropriate scale in which landforms can be delineated individually (in other words, at 10-30 meters on a side, a cell may contain a channel and a hillslope, but at 0.5 m individual channels and hillslopes can be identified).
OpenTopography has a step in the workflow (step 3a, "Calculate point count grid") to calculate and visualize the point count for a given area. Grid cell is populated with the number of points within the user defined search radius. This product can be exceptionally useful for evaluating lidar return concentration and allows users to better understand what resolution DEM the dataset will support.
In addition, ArcGIS has several tools for handling point cloud data. Assessing lidar coverage may be important before beginning any major processing on your machine. Visit this ArcGIS Resources page to learn how to asses lidar coverage and sample density.
This typically happens when either (1) the user-defined search radius is not large enough, or (2) the density of the original point cloud is low. There are various factors that control the density of point clouds. These include the speed at which the scanner was flown, the scanning rate, the aircraft's average altitude, and the amount of overlap between each swath. As a result, point clouds contain a heterogeneous distribution of point densities. When you create a DEM in OpenTopography, elevation values of the spatially heterogeneous points are used to interpolate a regularly gridded surface. As a result, areas that do not have a sufficiently dense point coverage will produce "holes" in the DEM. There are two ways to handle this: (1) increase the search radius of the gridding method, or (2) use the null filling feature.
There is no precise rule about grid resolution, but ideally you would like each grid cell to be representative of at least a single elevation value. In most cases with lidar data, the cell value is calculated from a few points. Points2Grid (P2G), the gridding software developed by OpenTopography, essentially assumes that grid resolution is greater than point spacing (i.e. a 1 m DEM can be created from 3 shot/m2 data density), and thus it is appropriate to perform a local operation on the points (e.g. take the mean values in a search area around the grid cell center). If your shot spacing is greater than the grid resolution, you will need to use a true interpolator like a spline or kriging to fit a surface to the points and to fill the holes. Take a look at this page and this page to learn more about how P2G works.
Note that for fairly dense data sets like the GeoEarthScope and B4 projects, you can reliably make DEMs at 0.25-0.5 m resolutions with 0.8-1 m search radii. The advantage of using the OpenTopography custom DEM functionality comes in the ability to simultaneously run a number of jobs using various search radii and grid resolutions. Once the jobs are complete, you can determine which DEM is optimal for your project's needs.
While some datasets have standard DEM options for downloading larger GIS files, we do not yet offer this service. However, there are three options available that might help:
Use OT to make much larger seamless grids from the point data. Consider your options through the OT portal. For example, if you're building a ground model, see how many ground points are available in the dataset by selecting to query only ground points. Keep in mind that using the TIN algorithm when making bare earth grids does a better job interpolating surfaces through low point density areas. Also note that you have access to more points as a registered myOpenTopo user (150 million) and Power User (200 million). To become a power user, log in to your myOpenTopo account and click "Point Cloud Authorization Status" under the User Account section.
If you do not want to produce a new DEM from the points, then you could consider using GDAL VRTs. You will still be required to download and unzip all individual tiles from OpenTopography. However, the VRT approach will allow you to manage and operate on the tiles as a "virtual" grid without ever merging them.
Download the LAS point cloud data and then grid the data outside of OpenTopography if you have other DEM-generating tools or software.
A .kmz file is a zipped .kml file (Keyhole Markup Language). KML is a file format used to display geographic data in an Earth browser, such as Google Earth and Google Maps. KML files are used to pinpoint locations, add image overlays or outline an area. For more information, visit the Google kml page.
Yes. In your Google Earth access window on the left side of the screen below the "Places" tab there is a slide bar that will allow you to fade between Google Earth and lidar.
This will depend on how the slopeshade imagery was created. OpenTopography produces hillshade KMZs as part of the visualization step. For some datasets (e.g., EarthScope, Tahoe), slopeshades are pre-generated and accessible via the OpenTopography Google Earth imagery files. To create slopeshade imagery for your area of interest, check the "slope" box on the job submission page.
For raster terrain products that were produced outside of OpenTopography, you will need to use other software to convert your hillshade or slopeshade imagery to the KMZ format. Simply saving the file as a .tiff or other graphics format will not work. There are various software that have this functionality and include Global Mapper, MapTiler, and ArcMap.
The Google Earth lidar KMZs simply show imagery derived from the DEM data. There is no elevation information associated with the imagery when viewed as a KMZ in Google Earth. Google Earth will only display elevation information for the native elevation mesh which is derived from a variety of sources (USGS National Elevation Dataset, SRTM, etc). Rarely are the native Google Earth elevations as accurate as those from the lidar data. If your project requires the use of accurate elevation values, you will need to use a true GIS software package (e.g., Global Mapper, ArcGIS).
The EarthScope lidar data are in ellipsoidal elevations, not the more commonly used orthometric (height above sea-level) elevations. The ellipsoid heights are measured along the ellipsoid normal in contrast to the orthometric heights, which adjust for Earth's gravity through a geoid model. In many applications, the term elevation most commonly refers to the orthometric height of a point. This page from ESRI provides a more detailed discussion.
Ellipsoid heights from GPS surveys are converted to traditional orthometric values by applying a geoid height using the latest geoid model from the National Geodetic Survey (NGS). You can calculate the geoid separation using this page. Once you have the separation value, you can "move" the DEM into the correct orthometric location using raster math (e.g., the raster calculator in ArcGIS).
The Corps of Engineers Coordinate Conversion (CORPSCON) tool can be used to transform the point data (XYZ ASCII) ellipsoid heights into NAVD88 elevations using various GEOID models, including the latest iteration, GEOID12A. The converted point data files can be then re-gridded to the ArcInfo raster format using your preferred interpolation technique.
This is a known issue with the early deliveries of the NoCal data and has been resolved for the later deliveries. However, for older deliveries the fix here is to use the "Define Projection" tool in ArcToolbox to redefine the projection for the misaligned tiles to what it should be (WGS_1984_UTM_Zone_10N). Note that you want to redefine the projection NOT reproject the data. The data in the file have the correct coordinates, ArcMap just gets confused and puts it in the wrong place because the projection definition is wrong.
The geometries of some active fault datasets on OpenTopography are generally long, narrow swaths that are parallel to the major faults in the region (e.g., the San Andreas fault system). These data are arbitrarily tiled into 1 km2 tiles regardless of how many points are in each tile. For tiles that fall on the edge of the point cloud, there may be very little data in a tile. You can see this issue clearly if you overlay the hillshade data on the tile index in Google Earth (both files are available in the Google Earth files page.
There are two DEM files that are generated for each zip file downloaded from either the Google Map or KML (Google Earth) interfaces: bare earth (vegetation removed) and full feature (vegetation, buildings, etc. still present). The bare earth DEMs are prepended with "fg" (for "filtered grid") and the full feature are "ug" (for "unfiltered grid"). For example:
When you download file 443_4443.zip and uncompress it, it contains two directories:
Inside each of these directories are these files:
The ESRI Binary Grid format (aka Arc/Info Binary Grid) is the collection of the files listed above. ArcGIS treats the directory containing the files as the grid (DEM). In the above example, when you attempt to load fg443_4443 into ArcGIS, the software sees that directory as a single DEM, not as a directory containing other files. For more information on the file format and to learn more about each of the above files, visit this ESRI Knowledge Base article, this ESRI help page, and this page.
Software other than ArcGIS (Global Mapper for example) does not see the whole directory as a single DEM and instead requires that you point it towards the appropriate *.adf file. In this case, you need to navigate into the fg443_4443 directory to the w001001.adf file in order for the software to load the DEM.
Finally, if you don't have access to software that will read the ESRI binary grid format, GDAL is an excellent and free tool that will allow you to convert these files into a format that is compatible with whatever software you are using. See our tutorial on this topic in Exercise 6.
The EarthScope lidar data were delivered in ASCII format with the following schema:
X, Y, Z, GPSTIME, INTENSITY, CLASSIFICATION, FLIGHT_LINE
As you can see, return number is not included. Classification is included however. The LAS files are generated on the fly by OpenTopography and are written using the information delivered by the data provider. As such, the schemas for point cloud data can vary greatly.
There are no pre-generated DEMs available for the B4 dataset. You will have to generate your own custom DEMS from the B4 point cloud data in OpenTopography. Alternatively, you can view 1 m hillshade images in Google Earth that were generated by the Scripps Institution of Oceanography Visualization Center.
Some datasets were collected in long, narrow swaths (e.g., parallel to major fault zones such as the San Andreas fault). The data are arbitrarily tiled out into 1 km2 tiles regardless of how many data points fall in each tile. For tiles that fall on the edge of the data acquisition, there may be few data points in a tile. When creating finer-resolution DEM grids with this specific geometry, the algorithm used to build grid files calculate the entire area of a tile rather than only where there are elevation data. Although the number of points do not surpass OpenTopography's processing threshold, the total area of the tiles can cause the system to time out and not complete a job. To manage this issue, run smaller jobs that cover your area of interest instead of running a few large jobs.
This is a common challenge encountered by the terrestrial laser scanning (TLS) community. OpenTopography's DEM-generating algorithms were designed to process "2.5D" datasets (i.e., every x,y coordinate has one and only one z value). These algorithms have a hard time processing true 3D datasets (i.e., an x,y coordinate may have multiple z values). There exist several software packages that are specifically designed to handle TLS data.
Examples of such software include Polyworks Pro, RiScan (companion to Riegl TLS scanners, and Leica Cyclone. You may also find other software solutions available in the computer aided design community (e.g. AutoCAD 3D Studio Max, Geomagic) since TLS is increasingly being used in urban modeling and engineering applications. For volumetric data representation, netCDF is a good format and has been used in seismic tomography and other 3D geophysical applications.
OpenTopography hosts the following datasets that cover dune fields:
The NOAA Digital Coast site also contains datasets that cover dune fields along U.S. coastlines.
The point cloud coverage for the Hawaii dataset is discontinuous because in includes project-specific datasets that were collected for various Principal Investigators.
Software for do-it-yourself point cloud classification or filtering is relatively limited. There are various commercial software packages such as Terrasolid and MARS that are designed for production environments (i.e. for use by a lidar vendor). Another commercial alternative is Tiffs.
In the free/open-source realm, GRASS GIS may have a robust point cloud classification capability.
Finally, you might want to take a look at this paper: Evans, J.S., and A.T. Hudak (2007), A multiscale curvature algorithm for classifying discrete return lidar in forested environments. IEEE Transactions on Geoscience and Remote Sensing 45(4):1029-1038. Download at: http://www.treesearch.fs.fed.us/pubs/29032.
Intensity is a measure, collected for every point, of the return strength of the laser pulse that generated the point. It is based on the reflectivity of the object struck by the pulse. Other descriptions for intensity include "return pulse amplitude" and "backscattered intensity of reflection". Intensity is used as an aid in feature detection and extraction, lidar point classification, and as a substitute for aerial imagery when none is available. If your lidar points include intensity values you can make images from them that look similar to black and white aerial photographs. To learn about creating an intensity image, visit this page.
There is no consensus as far as we can tell. At present, "lidar", "LIDAR" and "LiDAR" are used interchangeably in publications, industry websites and agency websites. For example, recent publications in Science (e.g., the Oskin et al.'s (2012) paper on differencing of the El Mayor-Cucapah pre- and post-earthquake lidar datasets have used "LIDAR". At OpenTopography, we are moving toward using "lidar" for the same reason "radar" is not spelled "RADAR" (which is an acronym for radio detection and ranging). See Prentice et al.'s, (2009) article ("Illuminating Northern California's Active Faults") in Eos for this usage.
There are various lesson plans and short courses that are designed for teaching about lidar data and applications in the classroom. Please visit our Resources for Educators page for information on how to contact us about sharing your teaching resources.
For Earth science-oriented lidar terms, you might want to subscribe to Arizona State University's lidar group and the UNAVCO list, both of which are announcement lists. OpenTopography also has a newsletter that you can subscribe to. Also follow OpenTopography on Facebook or Twitter for announcements. There are also various lidar groups on professional networking sites such as LinkedIn including the OpenTopography LinkedIn group.