Bettina Knorr
Phone: +49 (0) 6221 54-5560
Fax: +49 (0) 6221 54-4529
Postal Address
Heidelberg University
Prof. Bernhard Höfle
Institute of Geography
Im Neuenheimer Feld 368
69210 Heidelberg

3D Geospatial Data Processing Group


3D Geospatial Data Processing (3DGeo) Research Group

3DGeo-Logo       IWR – Interdisciplinary Center for Scientific Computing       HCE – Heidelberg Center for the Environment

We investigate the extraction of geoinformation from 3D/4D geodata (predominantly point clouds), which were acquired with cutting-edge Earth observation technology (e.g. 3D laser scanning, photogrammetry and SAR). Emphasis is put on the exploitation of multitemporal geographic 3D data, which enables near real-time 3D/4D mapping and observation. A major focus lies on the development of computational methods for 3D/4D geospatial data processing and analysis by making use of the full sensor data streams (e.g. LiDAR backscatter). It is aimed at increasing the understanding of geographical phenomena. Our methods and tools are applied to multi- and interdisciplinary research questions in the broad field of Digital and Computational Environmental Sciences. This covers landscapes dominated by physical processes (e.g. geomorphology), man-made landscapes (e.g. renewable energies) and strong human-environmental interactions (e.g. agriculture, natural hazards, health and geoarchaeology). Our research sites are spread all over the world: we perform in-situ measurements, program in the lab and simulate Earth observation in virtual environments.

Please check our recent publications, latest talks and running research projects for further details. If you are interested in joining the 3DGeo Group as a student assistant, intern, PhD student or senior researcher, please check our latest job postings.

Latest News (RSS Feed)
13.07.2019 09:52
Multi‐temporal 3D point cloud‐based quantification and analysis of geomorphological activity at an alpine rock glacier using airborne and terrestrial LiDAR

Change analysis of rock glaciers is crucial to analyzing the adaptation of surface and subsurface processes to changing environmental conditions at different timescales because rock glaciers are considered as potentially unstable slopes and solid water reservoirs. To quantify surface change in complex surface topographies with varying surface orientation and roughness, [...]

03.07.2019 22:53
AGEO Award 2019 at AGIT in Salzburg: Third place for Lukas Winiwarter

3DGeo group member Lukas Winiwarter was awarded the third place of this year’s AGEO award at the AGIT2019 in Salzburg for his diploma thesis on “Classification of 3D Point Clouds using Deep Neural Networks”. It was carried out at TU Wien under the supervision of Dr. Gottfried Mandlburger and Prof. Dr. Norbert Pfeifer, and has [...]

26.06.2019 17:55
Colloquium on image processing for geomorphological and hydrological monitoring

We cordially invite everybody interested to our next open GIScience colloquium talk! The speaker is Dr. Anette Eltner TU Dresden, Institute of Photogrammetry und Remote Sensing When: Monday 01.07.2019, 2:15 pm Where: INF 348, room 015 (Institute of Geography, Heidelberg University) Image processing for geomorphological and hydrological monitoring The potential of images to answer research questions in geosciences is vast. Earth observation [...]

26.06.2019 12:20
Kick-off field campaign for AHK-4D project

From 22 - 25 June, the first field visit within the project AHK-4D - High-resolution and high-frequency monitoring of the rock glacier Äußeres Hochebenkar (AHK) in Austria took place in the Austrian Alps. The aim of this project is to develop a methodology to quantify the magnitudes and frequencies of individual surface change processes of a [...]

21.06.2019 21:32
ISSAR19 - Third Innsbruck Summer School of Alpine Research

Close-range sensing techniques in Alpine terrain have been taught in the frame of a bi-annual ISPRS summer school since 2015. This week, a group of 40 young researchers (mainly PhD students) is participating in the third edition of the summer school to learn about various sensors, processing techniques, and analysis methods for different topics in [...]

18.06.2019 10:29
Estimating tree height from TanDEM-X data at the northwestern Canadian treeline

A new paper on tree height estimation from TanDEM-X data has just been published in Remote Sensing of Environment. The article finds that tree height can be predicted using TanDEM-X metrics (backscatter, bistatic coherence, and interferometric height) in the sparse forest patches of the Arctic treeline zone at the transition from forest to tundra. Taking [...]

14.06.2019 09:56
3DGeo at the Geospatial Week 2019

This week, the 3DGeo participated in the ISPRS Geospatial Week 2019 with two presentations among the sessions of the Laser Scanning Workshop with many interesting talks and poster. Presentations were given by Ashutosh Kumar in the Machine Learning Session and Katharina Anders in the Change Detection Session. Highlight: The work by Ashutosh Kumar on feature relevance in [...]

05.06.2019 18:15
Comparison of Three Algorithms for the Evaluation of TanDEM-X Data for Gully Detection in Krumhuk Farm (Namibia)

Namibia is a dry and low populated country highly dependent on agriculture, with many areas experiencing land degradation accelerated by climate change. One of the most obvious and damaging manifestations of these degradation processes are gullies, which lead to great economic losses while accelerating desertification. The development of standardized methods to [...]

31.05.2019 16:14
Paper on High-Frequency 3D Geomorphic Observation using Hourly LiDAR Time Series

Can you imagine how much sand is being moved on the beach in the course of a week? Did you ever observe truckloads of sand being transported on the beach in the absence of storms and bulldozers? It is hardly possible to estimate to the naked eye, but can be quantified with permanent terrestrial laser [...]

31.05.2019 16:12
Paper on Analysis of Feature Relevance in Deep Learning for 3D Point Cloud Classification

A paper investigating the relevance of (pre-calculated) features for 3D point cloud classification using deep learning was just published in the ISPRS Annals of Photogrammetry and Remote Sensing. The study presents a non-end-to-end deep learning classifier for 3D point clouds using multiple sets of input features and compares it with an implementation of the state-of-the-art [...]

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