Inference using HighResCanopyHeight

HighResCanopyHeight is a Regression Model, it generates tree height maps. Using TreeEyed multiple relevant layers can be generated.

Direct result:

• Grayscale raster (tree heights)

Derived results:

• Binary raster (tree/non tree)

• Polygons vector layer

• Bounding Boxes vector layer

• Centroids vector layer

Input

For this example we will use this image of a silvopastoral system. This image was extracted from a bigger raster image. In particular the important characteristic is:

Input image features

Feature	Value	Unit
Spatial resolution	0.5	m
Width	1835	px
Height	1001	px

The images can be downloaded here.

Configuration

Input

• Select the appropiate Input layer from the dropdown menu.

• For Extent select Layer extent.

Output

• Select the appropiate Output directory and Output name.

Processing

• Go to the Inference tab

  • Select HighResCanopyHeight model from the dropdown menu

  • Select the desired Result types, the direct result type for this model is Grayscale

  • You can leave the default parameters or adjust them

    type: you can choose between Satellite or or Aerial for your corresponding input theshold: percentage of to threshold the result for the binay raster result

  • Press Process to start the inference process

Results

The resulting added layers depend on the selected Result types

Direct result:

Processing Result	Result Type	Result
RASTER LAYERS
Derived result	Binary
Direct result	Grayscale
VECTOR LAYERS
Derived result	Polygons
Derived result	Bounding Boxes
Derived result	Centroids