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OpenTopography is a distributor of free high-resolution, Earth science-oriented topographic data, related tools, and resources. For more information, visit the About section.
The OpenTopography Portal does not require any software to use other than a standards-compliant browser.

OpenTopography Portal supports most standards-compliant browsers. We actively support, test and troubleshoot issues on Google Chrome, Internet Explorer, Firefox and Safari. The 3D point cloud browser visualization function is tested and working with Google Chrome, Firefox and Safari, but not yet in Internet Explorer browsers. It is expected that most WebGL-capable browsers should be able to support this visualization.

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.

All outlines indicate areas that have lidar coverage and are discoverable via OpenTopography. Areas outlined 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 models (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, GlobalMapper, or QGIS). These programs let you interact with and analyze the elevation data.

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 dataset's 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 a specific compressed file format with the extension "www.cronistalascolonias.com.ar". A "www.cronistalascolonias.com.ar" file is a compressed archive file format similar to the more familiar .ZIP. OpenTopography writes out custom DEM data and point cloud files as www.cronistalascolonias.com.ar files to make the files smaller and therefore convenient to download. Files downloaded from OpenTopography will look something like this: www.cronistalascolonias.com.ar, where the long number string is a unique identifier for the job, and the www.cronistalascolonias.com.ar 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 www.cronistalascolonias.com.ar file to access the www.cronistalascolonias.com.ar (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 www.cronistalascolonias.com.ar 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 double-click the name to automatically zoom in to the area of interest on the map.

Yes, OpenTopography offers bulk data download of point cloud and raster data for registered users. The system is designed for advanced users seeking to download large amounts of data quickly and who have the bandwidth, expertise, and software necessary to manage the terabytes of data available. Data are stored in SDSC's Universal Scale Storage (USS) service offering, a Qumulo hybrid cloud file storage system. We expect that users accessing bulk data have the ability to automate downloads using the AWS Command Line Interface or other compatible GUI clients. To access bulk data download, log into OpenTopography and navigate to your dataset of interest. A "bulk download" link is visible on the dataset metadata landing page and above the point cloud and raster data download and processing maps. Click the "Bulk Download" link - a pop-up with a link to the bulk interface as well as specific details on how to automate downloads using both the AWS Command Line Interface and Cyberduck is shown.

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.
Fourth return.
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 values. 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 bare-earth surface of the ground with regular spacing between the grid nodes (sometimes called the resolution). OpenTopography generally refers to models generated from first returns as DSMs.

Widely available DEMs are typically too coarse to provide adequate representation of small features (for example, the cell sizes in most USGS DEMs are 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 meters on a side, a cell may contain a channel and a hillslope but can only delineate one of them, while at 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. Each 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 the ArcGIS Assessing lidar coverage and sample density page to learn how to assess lidar coverage and 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 m resolutions with 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 ( million) and Power User ( 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.

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__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 _zip and uncompress it, it contains two directories:
fg_
ug_

Inside each of these directories are these files:
www.cronistalascolonias.com.ar
www.cronistalascolonias.com.ar
log
www.cronistalascolonias.com.ar
www.cronistalascolonias.com.ar
wadf
www.cronistalascolonias.com.ar

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 fg_ 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 fg_ directory to the wadf 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.

Software for do-it-yourself point cloud classification or filtering is relatively limited. There are various commercial software packages such as LAStools, 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 (), A multiscale curvature algorithm for classifying discrete return lidar in forested environments. IEEE Transactions on Geoscience and Remote Sensing 45(4) Download at: www.cronistalascolonias.com.ar

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.

Resources & Education

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 () 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, () article ("Illuminating Northern California's Active Faults") in Eos for this usage.