Quick links

Processing Options Default Templates

Follow

Here is a description of the available processing templates:

Processing Options Template

Characteristics

Outputs generated
Standard    
3D Maps Generates a 3D map (point cloud, 3D textured mesh), as well as a DSM and an orthomosaic.
Image acquisition: nadir or oblique flight.
Typical input: aerial images acquired using a grid flight plan with high overlap.
Outputs quality/reliability: high.
Processing speed: slow.
Application examples: quarries, cadaster, etc.

Orthomosaic

DSM

3D Mesh

Point Cloud
3D Models Generates a 3D model (point cloud, 3D textured mesh).
Image acquisition: oblique flight or terrestrial.
Typical input: any images with high overlap.
Outputs quality/reliability: high.
Processing speed: slow.
Application examples: 3D models of buildings, objects, ground imagery, indoor imagery, inspection, etc.

3D Mesh

Point Cloud

 
Ag Multispectral  Generates reflectance, index (such as NDVI), classification and application maps.
Image acquisition: nadir flight with a multispectral camera.
Typical input: images taken with a multispectral camera (Sequoia, Micasense RedEdge, Multispec 4C, etc).
Outputs quality/reliability: high.
Processing speed: slow.
Application examples: precision agriculture.

Reflectance Map

Index Map

Application Map
Rapid    
3D Maps - Rapid/Low Res Faster processing of the 3D Maps template for assessing the quality of the acquired dataset.
Outputs quality/reliability: low.
Processing speed: fast.

Orthomosaic

DSM

3D Mesh

Point Cloud
3D Models - Rapid/Low Res Faster processing of the 3D Models template for assessing the quality of the acquired dataset.
Output quality/reliability: low.
Processing speed: fast.

3D Mesh

Point Cloud
Ag Modified Camera - Rapid/Low Res Faster processing of the Ag Modified Camera template for assessing the quality of the acquired dataset.
Output quality/reliability: low.
Processing speed: fast.

Reflectance Map

Index Map

Application Map
Ag RGB - Rapid/Low Res Faster processing of the Ag RGB template for assessing the quality of the acquired dataset.
Output quality/reliability: low.
Processing speed: fast.		 Orthomosaic
Advanced    
Ag Modified Camera Generates reflectance, index (such as NDVI), classification and application maps.
Image acquisition: nadir flight with a modified RGB camera.
Typical input: images taken with a modified RGB camera.
Outputs quality/reliability: high.
Processing speed: slow.
Application examples: precision agriculture.

Reflectance Map

Index Map

Application Map
Ag RGB Generates an orthomosaic for precision agriculture.
Image acquisition: nadir flight over flat terrain with an RGB camera.
Typical input: images taken with an RGB camera for agriculture (Sequoia RGB).
Outputs quality/reliability: high.
Processing speed: average.
Application examples: digital scouting, report claiming for precision agriculture.		 Orthomosaic
Thermal Camera Generates a thermal reflectance map.
Image acquisition: nadir flight with a thermal camera.
Typical input: images taken with a thermal camera (such as Tau 2 based cameras: FLIR Vue Pro, FLIR XT).
Output quality/reliability: high.
Processing speed: slow.		 Thermal Index Map
ThermoMAP Camera Generates a thermal reflectance map.
Image acquisition: nadir flight with a thermoMAP camera.
Typical input: images taken with a thermoMAP camera.
Output quality/reliability: high.
Processing speed: slow.		 Thermal Index Map
 
Note: In the window Processing Options Template, a section titled Personal appears above the Standard section when a new personal template has been created by the user.

 

3D Maps
3dmaps.jpg
3D Models
3dmodel.jpg
Ag Multispectral 
ag_multispectral.jpg
3D Maps - Rapid/Low Res
3d_maps_low.jpg
3D Models - Rapid/Low Res
3d_models_low.jpg
Ag Modified Camera - Rapid/Low Res
ag_modified_low.jpg
Ag RGB - Rapid/Low Res
ag_rgb_low.jpg
Ag Modified Camera
ag_modified.jpg
Ag RGB
ag_rgb.jpg
Thermal Camera
thermal.jpg
ThermoMAP Camera
thermomap.jpg
Was this article helpful?
11 out of 12 found this helpful

Related articles

Article feedback (for troubleshooting, post here)

3 comments

  • den camacho

    noce

  • Ivis Marín

    Hola

    El software al procesar las imágenes realiza algún conteo automático de objetos?, ejemplo al realizar un estudio de capacidades carga de playa se necesita saber como dato la cantidad de personas que se encuentran  y quisiera saber si este conteo se realiza automáticamente para así evitar el conteo manual 

  • Fernanda Bosmediano

    Estimado Ivis,

    Muchas gracias por compartir esta interesante aplicación con nosotros. Pix4Dmapper no realiza un recuento automático de objetos. En Pix4Dmapper, se puede contar objetos manualmente (o semi-manualmente):

    • Se podria contar el numero de objetos o en este caso el número de personas en el ortomosaico y las nubes de puntos. (manualmente)
    • En el caso de que no fueran personas pero por ejemplo árboles, se podría dibujar una línea de perfil en el DSM que genera Pix4Dmapper. Luego podría contar los árboles en esta línea de perfil y multiplicar el número por el número de líneas de perfil. Este método supone que los árboles están bien distribuidos. (semi-manualmente)

     

    El primer método sería más preciso pero más lento, mientras que el segundo sería más rápido y más fácil pero menos preciso. Quizás puede sugerirnos esto como una nueva funcionalidad en uno de nuestros software. Para eso, se puede crear una sugerencia en nuestra comunidad: https://community.pix4d.com/t/how-to-vote-for-your-favorite-pix4dmapper-feature-requests-suggestions/10032 Estamos siempre monitoreando los requerimientos de nuestros usuarios.

    Saludos,

Article is closed for comments.