There are several parameters that can be tweaked to affect the resulting DEM depending on what the data will be used for. GISGeography is an excellent resource for understanding how IDW works. Also, because the points are irregularly dispersed across the study area and there are significantly sized areas that do not have elevation readings, we will use a mathematical method called Inverse Distance Weighting (IDW) to calculate an appropriate elevation value for each raster cell. We know from the statistics performed in the previous steps that the majority of the cells have enough point readings per cell (~4) to use a 1 meter resolution for the DEM. In this step we will use the GRASS GIS v.surf.idw tool to create a DEM. TIFFTAG_SOFTWARE=GRASS GIS 7.4.2 with GDAL 2.3.2 PROJCS["UTM Zone 15, Northern Hemisphere", Set the computation region to match the new raster map=Checkedįiles: //file/path/Texas-TrinityRiver/point-density.tif Use the extent of the input for the raster extent=Checked Lidar Raster=/output/file/path/lidar_density.tif Only import points of selected class(es)=2 Storage type for resultant raster map=CELLįilter range for z data=-10000, 10000 (use large values to ensure all points fall within the range)įilter range for intensity values=-10000, 10000 Statistics to use for raster values=n (i.e. The key parameters to enter into the tool are:
Next, click on the gear shaped "Toolbox" button in the tool bar to open the "Processing Toolbox".
Open a new QGIS project ( download and install a free copy now if you have not done so already! Once the program is open make sure you set the default spatial reference system/projection/EPSG to match that of the LiDAR dataset. Hydrologically correct DEM with pits filled: No Hydrologic Terrain Analysis (TauDEM) Products:
Title: Trinity River, Texas 2015 - Practiceĭescription:This LiDAR data set is intended for practicing how to generate elevation products over forested terrain.ĭownload point cloud data in ASCII format: Noĭownload point cloud data in LAS format: Yesĭownload point cloud data in LAZ format: No Vertical Coordinates: NAVD88 (GEOID 12a) Horizontal Coordinates: UTM Zone 15N NAD83 (2011) National Center for Airborne Laser Mapping (NCALM), distributed by OpenTopography.ĭata Access Acknowledgement: This material is based on services provided by the OpenTopography Facility with support from the National Science Foundation under NSF Award Numbers 1226353 & 1225810 (2015): Trinity River, Texas 2015 airborne lidar. NCALM funding provided by NSF's Division of Earth Sciences, Instrumentation and Facilities Program. LiDAR data acquisition and processing completed by the National Center for Airborne Laser Mapping (NCALM). QGIS is ideal because comes with GRASS tools integrated into it (possibly not for macOS) This is adventitious as analysis becomes more complicated at which point you can start creating scripts and tools to automate a lot of the time consuming and repetitive processes (a topic for a future tutorial). I like using this method because all of the processing, analysis, visualization and mapping can be done with one environment. There are several ways to process LiDAR with free and open source solutions. In order to accomplish this we will use QGIS 3.4 which has access to the GRASS GIS 7.4 tools. The DEM/DSM is the base data that can be used in many types of environmental and terrain modeling such as calculating watersheds, flood areas, viewsheds, slopes and terrain feature identification. As a first step in breaking down the accessibility barriers to LiDAR, this article will walk through the common task of creating a Digital Elevation Model (DEM) or more specifically a Digital Surface Model (DSM) which is a raster/image/gridded representation of the ground topography with the vegetation and buildings removed.