MSc thesis handed in on predicting forest understory canopy cover

MSc thesis handed in on predicting forest understory canopy cover

May 9, 2016

A M.Sc thesis was written by Bastian Schumann under the supervision of Dr. Hooman Latifi and Prof. Christopher Conrad that focused on a LiDAR-based approach to combine structural metrics and forest habitat informaiton for causal and predictive models of understory canopy cover. The data base used consisted of a bi-temporal LiDAR dataset as well as two field datasets and two habitat maps. The entire data were initially edited, revealing that a bi-temporal treatment is only possible for understory layers. The statistical models used for modelling canopy cover density included random forest, logistic models and zero-and-one inflated beta regression.

The results revealed the most relevant LiDAR metrics which contribute to explain the canopy cover density. Furthermore it indicates that the habitat types have a significant influence on canopy cover density. In addition, it was shown that with the use of a denser point cloud a higher performance can be achieved in almost every vertical stand layer.

Wall-to-wall predictions of understory canopy cover usign high density point cloud, habitat types and a logistic model

Wall-to-wall predictions of understory canopy cover usign high density point cloud, habitat types and a logistic model

you may also like:

What it takes to record a forest for an entire year: Insights into one out of many days flying drones in the University Forest

What it takes to record a forest for an entire year: Insights into one out of many days flying drones in the University Forest

This week, EOR Cluster staff carried out a routine flight mission in the University Forest: As every second week, the entire 200 ha were imaged with a multispectral sensor on a Wingtra fixed wing aircraft. Additionally, the mission was augmented by LIDAR on an M300 multicopter (as every month). Initially delayed by rainy weather, the crew managed to acquire high quality data, which helps monitoring the ecosystem.

Msc Defense by Katrin Wernicke

Msc Defense by Katrin Wernicke

On Tuesday, July 18 at 10 a.m. Katrin Wernicke will present her MSc Thesis "Deep Learning for Refugee Camps – Mapping Settlement Extents with Sentinel-2 Imagery and Semantic Segmentation" From the abstract: The number of people forced to flee their homes has...

MSc Defense by Tobias Gutzmann

MSc Defense by Tobias Gutzmann

On Friday, June 30 at 10 a.m. Tobias Gutzmann will present his MSc Thesis “Estimation of Above-ground Biomass of Trees in Würzburg using Object-based Interpretation of Airborne Imagery” From the abstract: With increasing recognition of the importance of urban forests,...