= Lidar QC Procedure = This page describes the procedure for the QC of the LIDAR data. ------ == QC Procedure == As it stands this is the Lidar data QC procedure. This could be improved and added to as time allows. === Remove noisy points === The first stage of the QC is to check the data and remove erroneous points. This can be done in Microstation/TerraSolid by creating a macro. It should be straightforward to script this into a GIS such as GRASS too. Start Microstation and goto Utilities -> MDL Applications -> Terrascan[[BR]] In Terrascan goto Tools -> Macro Press Add to add routines to the Macro. * Change all classes to default class (Action: Classify Points, Routine: by class) * Classify groups of low points (Action: Classify Points, Routine: low points) * Classify single low points (Action: Classify Points, Routine: low points) * Classify isolated points (Action: Classify Points, Routine: isolated points) To run on large projects use "selected files" instead of reading all LAS files into memory. Ensure that the output format under 'Save As:' is .LAS (1.0 if possible- may be issues with las2txt.sh and LAS 1.1). Check the result to see what points have been selected. To delete the points: Point -> Delete -> by class ['''This should not be done for operational processing of data'''] Can select/deselect points using the Add Point To Ground tool from the Classify menu. Individually select points which were missed or wrongly classified by the classification algorithms. To remove haze layers, use elevation to threshold (Routine: by absolute elevation). Select an elevation range whose minimum is well above any ground targets and maximum above the haze layer. === Check overlap of neighbouring lines === The first thing to do here is to load up all lines into a viewer (or if runs out of memory load them up in pairs) and see how well they overlap in the horizontal plane. The Fugro viewer is probably best for this because it also allows Shapefiles to be read in (though you can also just use Terrascan with "Colour by intensity"). Check along features that cross between flight lines, for example, roads/field boundaries/hedgerows do they continue unbroken or are they offset between flight lines. Also, compare against the vectors (if available) for any gross offsets. The elevation between neighbouring flight lines must be checked too. This can be done in various ways: * examining profiles over the overlapping regions: allows measurements of the height difference to be made (in Terrascan/Microstation) * Re-order points in Terrascan: reorder 'by elevation (Z)' and colour by flightline. This will ideally show a mix of colours in the overlap region. If only one solid colour is shown then this flightline is consistently higher than the the other. If the elevations are offset consistently between flight lines then this probably means an error with the calibration values (boresight or range correction). This should be corrected. If the offsets are random per flight line then the average offset per flight line should be noted but not corrected for (unless ground control points are available) === Check against OS vector maps === If not done in the above step then the flight lines must be checked against vectors (if available). To check in Envi: Create an ascii with las2txt.sh (may not work with LAS 1.1) and then an intensity image with make_lidardem_or_intensity.sh [wiki:Processing/CreateTifs Instructions Here] To check in Terrascan: You need to convert the .shp vectors into .dgn. Instructions [wiki:Processing/shapesintoterrascan here]