MSc thesis handed in on Analysis of Airborne LiDAR Data for Deriving Terrain and Surface Models

MSc thesis handed in on Analysis of Airborne LiDAR Data for Deriving Terrain and Surface Models

May 9, 2016

A M.Sc thesis by Raja Ram Aryal  at the University of Applied Sciences Stuttgart was recently written  under the supervision of Dr. Hooman Latifi and Prof. Michael Hahn. The thesis focused on a comparative study on the variations of an adaptive TIN ground filtering algorithm  to extract DTM from discrete LiDAR point cloud captured in leaf-off and full wave LiDAR point cloud collected in leaf-on conditions. In addition Analysis of Variance (ANOVA) type II was used to assess the influential factors that are related to DTM random error.  The Accuracy assessment of extracted DTMs was done  at local and landscape levels in heterogeneous forest stands of Bavarian Forest National Park. The DTM generated using mirror points in leaf-off returned less RMSE (0.844 m) than in leaf-on (0.988 m) conditions. Furthermore RMSE values of 0.916 m (leaf-off) and 1.078 m (leaf-on) were observed the local level analysis when no mirror points were used. However, RMSE value of ca. 0.5 m was observed at the landscape level, with leaf-off DTM showing slightly higher error than leaf-on DTM. The DTM error increased with increasing slope. Deciduous habitat was found to significantly influence DTM error in both leaf-off and leaf-on conditions. Interaction effects were mainly observed between slope and forest habitat type.

DTMs Extracted using denser point cloud LiDAR data (leaf-on condition) using mirror points  (left side) and without using mirror (right side)

DTMs Extracted using denser point cloud LiDAR data (leaf-on condition) using mirror points (left side) and without using mirror (right side)

you may also like:

AgriSens DEMMIN 4.0 field work – mission completed

AgriSens DEMMIN 4.0 field work – mission completed

Last week some EAGLE students ventured out for a field campaign at the Durable Environmental Multidisciplinary Monitoring Information Network (DEMMIN) test site to support us in the field work for the AgriSens DEMMIN 4.0 project funded by the Federal Ministry of Food...

WASCAL-DE-COOP Workshop in 2022

WASCAL-DE-COOP Workshop in 2022

For the second year in a row, WASCAL graduate students from the diverse WASCAL Graduate Schools in West Africa joined the workshop “Intercultural Competence – Communications with the German Research Landscape”. This workshop was provided virtually by colleagues from...

most recent news:

Video contest on migration in West Africa

Video contest on migration in West Africa

Our partner in the MIGRAWARE project CoKnow Consulting asks people from Ghana or Nigeria to participate in a Video contest: It is my pleasure to invite you to the Best Migration Video Contest of the MIGRAWARE project:https://www.servemebest.com/c/s/aBe In the...

WASCAL Director of Research at the Department of Remote Sensing

WASCAL Director of Research at the Department of Remote Sensing

From 18th to 20th of June, the WASCAL Director of Research, Prof. Dr. Kehinde Ogunjobi, and the remote sensing expert at the WASCAL Competence Center (CoC), Dr. Kwame Hackman, paid a visit to the Department of Remote Sensing. The two days were efficiently used for...