If you are looking for a specific how to in the LiDAR process then I hope that you can find it below. If however you are a complete newb like I was I would recommend looking at these portfolio pieces which go through how to load up TerraScan modules, import *.las files, create projects, calibrate sensors and classify points. Create a Project and Classify Points, Calibrate Sensors.
MicroStation can only read PXYZ (point, easting, northing elevation (orthometric height)) files. You must first change your files to this format and save as *.csv. Load in a vector (*.shp file) of control point locations. This can aid in determining accuracy issues. Go to MicroStation–>Tools–>Toolboxes and select it. Turn on XYZ Text Next you […]
Open up Terrascan and Read Points. It’s important to only open every 100th point for processing time. The next step is to export a lattice model. Grid spacing of 500m is acceptable because the geoid model has km long arcs. Filling gaps will prevent gaps in your TIN. Three decimal places will give you mm […]
Correct Flightline Errors The measure match tool is used to determine flightline shift. The find match tool is then run to determine necessary corrections After the find match tool finishes analyzing your dataset, apply the corrections Run the measure match tool a second time to see the decrease in flightline shift. RMS error should be […]
Causes of Errors include positional erros with the GPS/IMU, range, scan angle, boresight angles, lever-arm offsets. These are systematic errors and corrections can be applied over the entire dataset. Range Errors – Not corrected for, occur due to recording of the time between emission and return of laser – centimeter scale. Beam Divergence – Common […]
This tutorial goes through how to direct your project to your trajectories folder and then how to open up the trajectory window and display the trajectory in your main viewer/add it to your project. It then discusses how to clip the trajectory by an area of interest and give individual flightline names. Import Trajectories Tutorial
Radar imagery interpretation is difficult and variable without ground truthing. It is not based on a spectral response that we are similar with (visible, infrared or thermal) but is instead based on polarized microwaves. What this means is that it is sensitive to the roughness and orientation and nature of the ground surface. Radarsat can […]
LiDAR : Classifying Points Typical Classes 1 – Unclassified 2 – Ground Solid 3 – Low Vegetation 4 – Medium Vegetation 5 – High Vegetation 6 – Building 7 – Low Point (noise) 8 – Model Keypoints (mass point) 9 – Water If the point class you want is not already defined…DEFINE IT! Don’t forget […]