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Python scripts for processing lidar surveys from the Central Coast.

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README.md

Central Coast aerial lidar processing

Python scripts for cleaning, classifying, and extracting survey profiles from las point clouds.

1. Enter input parameters

Input parameters are entered into excel spreadsheets, e.g. param-files/survey-1.xlsx. The python scripts take their input in yaml format. The spreadsheets can be converted to yaml by running:

python excel_to_yaml.py

2. Manipulate las data

las_manipulation.py does the following to the input las file:

clip to beach extent
classify ground points (so vegetation and buildings can be removed later)
draw a polygon to remove swash zone interference

Example usage:

# Process single survey at specific beach
python las_manipulation.py param-files/survey-1-avoca.yaml

# Process single survey at multiple beaches
python las_manipulation.py param-files/survey-1-avoca.yaml param-files/survey-1-pearl.yaml

# Process all surveys at specific beach
python las_manipulation.py param-files/*avoca.yaml

# Process all beaches for specific survey date
python las_manipulation.py param-files/survey-1*.yaml

3. Check swash clipping mask

The swash clipping mask should be checked visually to ensure it is correct.

4. Export results

las_outputs.py does the following, based on the outputs of las_manipulation.py:

remove swash zone
extract elevations from point cloud at profile locations
complete volume analysis based on Nielsen et al. (1992)
save figures of profile cross sections
save raster of ground surface

Example usage:

# Process single survey at specific beach
python las_outputs.py param-files/survey-1-avoca.yaml

# Process single survey at multiple beaches
python las_outputs.py param-files/survey-1-avoca.yaml param-files/survey-1-pearl.yaml

# Process all surveys at specific beach
python las_outputs.py param-files/*avoca.yaml

# Process all beaches for specific survey date
python las_outputs.py param-files/survey-1*.yaml