Importing the Data
Imagery taken with RedEdge will be automatically recognized since the camera is in the Pix4Dmapper camera database.
- Create a new project. (?)
- Import all of the images for each band (blue, green, red, rededge and NIR imagery)
- In the Edit Camera Model window, ensure the Global Shutter model is selected. (?)
- Choose the Ag Multispectral processing template. (?)
Radiometric Processing and Calibration
On the Menu bar, click Process > Processing Options...,
the Processing Options pop-up appears. Press 3. DSM, Orthomosaic and Index
Select the Index Calculator tab:
Under Radiometric Processing and Calibration, you can choose the following options, some of which may not be available for RedEdge data. Please check with Pix4d Support to confirm:
- No correction: no radiometric correction will be done
- Camera only: corrections will be applied for the parameters that are written in the EXIF metadata and relate to the camera (vignetting, dark current, ISO, etc...).
- Camera and Sun Irradiance: corrections will be applied for the camera parameters from the point above as well as for the sun irradiance information written in the XMP.Camera.Irradiance EXIF tag.
- Camera, Sun Irradiance and Sun angle: corrections will be applied to take into account the sun position, as well as the camera information and the irradiance data. This option should only be chosen for flights that were done in clear sky conditions.
The camera used is displayed. Users can calibrate the sensor to perform an illumination adjustment in order to obtain more accurate reflectance values. If there are more than one camera models in the project, all the cameras will be listed in the Radiometric Processing and Calibration section.
Using the Calibration Panel
The Calibrate button allows users to take into account the information from a picture with radiometric calibration target if such a target was used during the project.
Obtaining your panel's reflectance values
If you have a MicaSense Reflectance Panel, you can get the reflectance values for your panel by filling out this form.
This procedure will need to be done for each of the five bands, with the corresponding "albedo" value provided for each band. Please note the band order (Blue, Green, Red, RedEdge, NIR) and ensure you are entering the appropriate value for each band.
After clicking Calibrate for a camera model, the Radiometric Calibration pop-up appears.
If a radiometric calibration target is used, make sure that the radiometric target data is taken into account by ensuring the symbol in the Processing Options is a green checkmark (?).
In File Name, the Browse button, opens the Select a radiometric calibration image pop-up. This pop-up allows the user to select the image in which the radiometric calibration target appears.
When an image is browsed, the user can draw a region on the image that will define the radiometric calibration. The Reset button, resets the area drawn by the user.
Use the left mouse button to draw the first three points, then draw the final point with the right mouse button.
After configuring Pix4D to use the calibration data, you can continue to process your dataset. You will need to generate a reflectance map. For up-to-date details on processing, please see the Pix4D knowledge base.
Once you have generated a reflectance map, see How to export to Atlas from Pix4D to export the final output to Atlas for analytics.
Merging the Reflectance Map
The reflectance map generates a GeoTIFF for each band. To combine these into one multi-band image, you can either upload the data to Atlas and download the GeoTIFF, or use external software:
- gdal_merge via the command line
- QGIS Virtual Raster Builder
Using Gdal Merge
gdal_merge.py -o BGREN_Output.tif -separate Pix4D_output_transparent_reflectance_blue.tif Pix4D_output_transparent_reflectance_green.tif Pix4D_output_transparent_reflectance_red.tif Pix4D_output_transparent_reflectance_red_edge.tif Pix4D_output_transparent_reflectance_nir.tif
Or, simply, if you are in the Pix4D output folder:
gdal_merge.py -o BGREN_Output.tif -separate *.tif
If your results are tiled, you would have to first merge the tiles for each band:
gdal_merge.py -o blue.tif *blue*.tif
gdal_merge.py -o green.tif *green*.tif
gdal_merge.py -o red.tif *red*.tif
gdal_merge.py -o rededge.tif *rededge*.tif
gdal_merge.py -o nir.tif *nir*.tif
Then merge the five outputs with -separate
gdal_merge.py -o BGREN_Output.tif -separate blue.tif green.tif red.tif rededge.tif nir.tif
Using QGIS Virtual Raster Builder
Note: This method does not create a new raster. It is a way to organize your existing rasters into one catalog for easy access and visualization.
Load the GeoTIFFs for each band into the Layers Panel (drag and drop or Layer > Add layer > Add raster layer...)
- Ensure that the individual band geoTIFFs are in the correct order by dragging and dropping
- Correct order: Blue, Green, Red, RedEdge, NIR
- Select (turn on) all geoTIFFs
Open Virtual Raster Builder from the QGIS menu bar: Raster > Miscellaneous > Build Virtual Raster (Catalog)...
The Virtual Raster Builder dialog opens (see below).
- Since all geoTIFFs are activated in QGIS, select the option to use visible raster layers for input.
- Select an output file location for the virtual raster file.
- In order to create a virtual raster with 5 discrete bands in one file, select the Separate option.
- The output file will automatically load into QGIS unless this box is deselected.
- Press OK to build the virtual raster.
The new virtual raster is added to the Layers Panel in QGIS. Now we can move on to editing the layer properties to display properly.
From the Layers Panel, right click on the new virtual raster layer and select Properties. Within the Layer Properties, navigate to the “Style” tab. Ensure you are in the “Multiband color” option. Using the drop down menu for each band, you will see that this layer now contains 5 bands. Change the Red band to “Band 3”, Green band to “Band 2”, and Blue band to “Band 1”.
Now, copy the smallest "Min" value and paste it into the other "Min" value boxes. Then copy the largest "Max" value and paste it into the other "Max" value boxes. The above example will then look like the example below. This step is not necessary but stretching these values generally helps to create a more visually pleasing image for the human eye.