Individual Tree Detection (ITC)
From AWF-Wiki
(Difference between revisions)
(→Invert the CHM) |
|||
| Line 12: | Line 12: | ||
=Invert the CHM= | =Invert the CHM= | ||
Now the smoothed CHM will be inverted. | Now the smoothed CHM will be inverted. | ||
| − | * In the search engine of the Processing Toolbox, type {{typed|text=invert}} and select '''Invert | + | * In the search engine of the Processing Toolbox, type {{typed|text=invert}} and select '''Invert grid''' under Raster tools of SAGA. |
* Select the smoothed CHM raster data file from previous step as input layer. | * Select the smoothed CHM raster data file from previous step as input layer. | ||
| − | + | * Enter name and path for an output file. | |
| − | + | ||
| − | * Enter name and path for an | + | |
* Click on {{button|text=Run}}. | * Click on {{button|text=Run}}. | ||
| − | [[File: | + | [[File:Qgis_smooth_invert.png|300px]] |
| − | + | ||
=Watershed segmentation= | =Watershed segmentation= | ||
Revision as of 23:30, 6 January 2018
Contents |
Filter the CHM derived from LiDAR data
We use a Canopy Height Model (CHM) derived from LiDAR data as decribed here to detect individual tree crowns. Two preprocessing steps prepare a watershed segmentation approach: (1) Gaussian filtering and (2) inversion of a CHM.
- In the search engine of the Processing Toolbox, type smooth and select Smoothing (gaussian) under Image filtering of the Orfeo Toolbox.
- Select the CHM raster data file in GeoTiff format as input layer.
- The smoothing type is gaussian.
- The circular structuring element has a radius of 2 pixels.
- Enter name and path for an temporary output file.
- Click on Run.
Invert the CHM
Now the smoothed CHM will be inverted.
- In the search engine of the Processing Toolbox, type invert and select Invert grid under Raster tools of SAGA.
- Select the smoothed CHM raster data file from previous step as input layer.
- Enter name and path for an output file.
- Click on Run.
