Meintest du modell?
KISSMig ist ein einfaches, rasterbasiertes Modell für die dynamische Modellierung von Artverbreitungen in der Programmiersprache R. Ausgehend von einer Ausgangsverbreitung generiert KISSMig zukünftige Verbreitungen unter konstanten oder sich ändernden Umweltbedingungen.
Startseite Services und Produkte Zurück … a „Keep It Simple Species Migration model
Processes”, different research groups at the WSL/SLF will develop knowledge and models
seasonal and (3) climate scale using different types of models depending on required model
Gastwissenschafter, WSL Lausanne, WSL Site de Lausanne c/o EPFL-ENAC-PERL, Station 2, 1015 Lausanne
Model ecosystems are natural and semi-natural man-used sensitive and altered terrestrial
Peruvian glaciers are an important water resource for downstream populations and have shrunk significantly in recent decades in response to climatic change. This project investigates the impacts of ongoing and projected climatic change on glacier retreat and water resources in Peru’s most glacierise
Workpackage 3: led by Martín Timaná and Tim Hess This team aims to model the associated
The results of the scenario modelling are available in raster format for non-commercial use by interested parties. PDF versions of maps for each scenario are available here for download.
modelling framework we incorporate socio-economic and bio-geographical variables to model
Spatial modelling of drought effects on Swiss forests
To spatially model forest drought risk in Switzerland under a variety of expected
PostDoc, SLF Davos, WSL-Institut für Schnee- und Lawinenforschung SLF, Flüelastrasse 11, 7260 Davos Dorf
Changes in precipitation variability across time scales in multiple global climate model
TRAMM war ein Forschungsprojekt im Rahmen des ETH-Kompetenzzentrums für Umwelt und Nachhaltigkeit (CCES) von 2006 bis 2015 mit dem Ziel, Auslöse- und Transportprozesse von Hangrutschungen, Murgängen und Lawinen besser zu verstehen.
Catchment scale hydromechanical model for landslide triggering – Representing localization
Wir engagieren und vorwiegend in der Erfassung, Analyse, Bewertung und Entwicklungsprognosen der Ressourcen des Waldes.
Sentinel-2 (S2) images, an Airborne Laser Scanning (ALS)-based Digital Terrain Model
The project aims at developing, testing and implementing machine learning routines applied to typical geological datasets to automatically identify structural feature traces and surfaces and differentiate discontinuity types.
significantly influence the classification decisions made by the machine learning model
