Analyze height for regions in a geojson shapefile using regional percentiles

Vectorize approach to height estimation per region in a shapefile using a digital elevation model (DEM) or digital surface model (DSM). Calculates the soil elevation as the lower percentile and uses the upper percentile as plot elevation.

plantcv.geospatial.analyze.height_percentile(dsm, geojson, lower=25, upper=90, label=None)

returns Debug image with regions drawn on the input DSM (digital surface model).

  • Parameters:

    • dsm - DSM image object, likely read in with geo.read_geotif
    • lower - Lower percentile cut off, default lower=25
    • upper - Upper percentile cut off, default upper=90
    • geojson - Path to the shapefile/GeoJSON containing the plot boundaries. Can be Polygon or MultiPolygon geometry.
    • label - Optional label parameter, modifies the variable name of observations recorded. Can be a prefix, or list (default = pcv.params.sample_label)

  • Context:

    • This function will utilize the geojson's ID attribute for Outputs labels if available.
    • Output data stored: Data ('soil_elevation', 'plant_elevation', 'plant_height') automatically gets stored to the Outputs class when this function is run. These data can be accessed during a workflow (example below). For more detail about data output see Summary of Output Observations.

  • Example use:

import plantcv.geospatial as gcv
import plantcv.plantcv as pcv

# Read in dsm as geotif
dsm = gcv.read_geotif(filename="./data/example_dsm.tif", bands=[0])
# Analyze coverage for each region in the geojson
bounds = gcv.analyze.height_percentile(dsm=dsm,
                           geojson="./shapefiles/experimental_plots.geojson",
                           lower=25,
                           upper=90,
                           label="default")

# To access individual observation values:
print(pcv.outputs.observations["default_0"]["plant_height"]["value"])

Screenshot

Source Code: Here