Remote sensing data; monitoring; Detection; Software

Mensaje de error

Notice: Undefined index: #markup in bootstrap_preprocess_field() (line 92 of /data/www/rosewood.admin.v4/sites/all/themes/bootstrap/template.php).

Idioma Inglés

Innovación

Yes

Correo electrónico del autor o propietario

luuk.dorren@bfh.ch

Sitio web principal

https://www.bfh.ch/hafl/en/

Dominio

Inventory, monitoring

Forest management, ecosystem, resilience

Research and development

Voting

Palabras clave

Remote sensing data; monitoring; Detection; Software

Título (abreviación)

FINT-CH

Descripción breve

<table border="0" cellpadding="0" cellspacing="0" style="width:600px;" width="600"> <tbody> <tr height="60"> <td height="60" style="height:60px;width:600px;">In the project FINT-CH a methodology for the large-scale characterization of forest structures, thereon a better detection of single trees on the basis of remote sensing data, is under development. Top height, cover and mixture ratio get determined. </td> </tr> </tbody> </table>

Solución digital

Yes

Tipo de solución

Sensors, measurement equipment

Resumen

In the project FINT-CH a methodology for the large-scale characterization of forest structures, thereon a better detection of single trees on the basis of remote sensing data, is under development. By using segmentation, stand boundaries and the corresponding top height, cover and mixture ratio get determined. This forms the basis for the specific single tree detection using forest structures. Large-scale geodata with valuable forest information can be generated. Their usage in practice are demonstrated on the basis of four examples.Vector-geodata (type polygon) with stand boundaries and the following attributes:
- Basic shape (uniform, unequally)
- Top height (hdom)
- Cover ratio
- Mixture ratio
- Stem number of upper-class trees
- Basal area of upper-class trees Vector-geodata (type points) with detected single trees and the following attributes:
- Top height
- BHD
- Social status in the upper-class
-Z-trees

Vector-geodata (type polygon) with forest gaps, boundaries and aisle The methodology should be able to get a simple and large-scale investigation every 5 to 10 years regarding the mentioned data attributes mentioned beforehand. With these attributes conclusions are possible regarding stem numbers of different classes, protective forest investigations, mapping of forest gaps, boundaries and aisle as well as on stock estimations and finally operational planning (allowable cut, activity planning… )

Organización autora o propietaria de la buena práctica

BFH Bern University of Applied Sciences

Nombre del autor o propietario

Luuk Dorren

Web del autor o propietario

https://www.bfh.ch/hafl/en/

Organización intermediaria de contacto

BFH Berne University of Applied Sciences

Persona de contacto del intermediario

Moritz Dreher

Correo electrónico del intermediario

moritzkaspar.dreher@bfh.ch