Masterarbeiten – Geodätisches Institut Hannover

Abschlussarbeit im Bereich Flächen- und Immobilienmanagement

Wir bieten viele spannende Themen aus den Themenfeldern Stadt- und Regionalplanung, ländliche und städtische Neuordnung sowie Immobilienbewertung und Untersuchungen im Grundstücks- und Immobilienmarkt, welche im Rahmen von Bachelor-/ Masterarbeiten bearbeitet werden können. Sprechen Sie uns an!

Betreuung: Dr.-Ing. Jörn Bannert

Jahr: 2025

Qualitätsgesicherter Validierungsansatz für laserscanner-basierte Multisensorsysteme

Im Rahmen dieser Masterarbeit soll die Möglichkeit der Validierung von laserscanner-basierte Multisensorsystemen (MSS) durch einen Vergleich zu einer Referenzpunktwolke der Umgebung untersucht werden. Dabei sollen Aussagen zur Qualität der Positionierung und Datenerfassung des MSS abgeleitet werden.

Betreuung: Dominik Ernst, M. Sc.

Jahr: 2025

Integrating Measurement Uncertainty for Enhanced Reliability in Digital Bathymetric Models

Nowadays mapping of underwater topography has been greatly facilitated by high-resolution systems such as multibeam echosounders (MBES). Nevertheless, the extensive data collected by these instruments are often contaminated with varying degrees of errors. This calls for caution in constructing Digital Bathymetric Models (DBMs), particularly for critical applications like waterway navigation. This master thesis aims to explore and enhance the quality of DBMs by incorporating measurement uncertainties systematically into the modeling process.

Betreuung: PD Dr.-Ing. Hamza Alkhatib, Bahareh Mohammadivojdan, M. Sc.

Jahr: 2025

Bayesian Deep Learning for Distribution Prediction of TLS Uncertainties

In modern geodetic applications, Terrestrial Laser Scanning (TLS) is a key technology for the acquisition of detailed 3D information. While TLS has demonstrated remarkable capabilities, the need for robust uncertainty modelling is becoming increasingly apparent in critical applications such as deformation analysis. An accurate understanding and quantification of systematic deviations in TLS measurements is essential to ensure the reliability of 3D data. This research seeks to address this aspect by investigating the uncertainties within TLS data, in particular the systematic deviation in distance measurement.

Betreuung: PD Dr.-Ing. Hamza Alkhatib, Jan Hartmann, M. Sc.

Jahr: 2025

Bewertung von Grundstücken unter Einbeziehung von Expertenwissen: Eine Bayes'sche Inferenz für die Wertermittlung in kaufpreisarmen Lagen

Auf Grundstückswerte wirken in Abhängigkeit von räumlichen und sachlichen Teilmärkten verschiedene wertrelevante Parameter mit unterschiedlich starken Einflüssen ein. In räumlichen und sachlichen Teilmärkten mit einem guten Kauffallgeschehen können die Bodenwert-beeinflussenden Parameter durch statistische Auswertemethoden bestimmt werden.

Betreuung: PD Dr.-Ing. Hamza Alkhatib, Dr.-Ing. Jörn Bannert

Jahr: 2025

Advanced Particle Filter-Based V2V Collaborative Localisation in Urban Environments

This master thesis aims to develop and integrate a reliable Vehicle-to-Vehicle (V2V) collaboration approach into an existing Particle Filter framework. By incorporating the uncertainty information of leading vehicles, the method seeks to accurately quantify the filtered ego-vehicle's pose. The primary objective is to minimize longitudinal deviations, particularly in feature-poor environments, where current methods experience significant pose disturbances. Ultimately, this module aims to enhance localization robustness and accuracy in challenging urban scenarios.

Betreuung: PD Dr.-Ing. Hamza Alkhatib, Marvin Scherff, M. Sc.

Jahr: 2025

Advanced Particle Filtering for Quadruped Robot Navigation

The aim of this master thesis is to adapt and evaluate an existing particle filter framework for quadruped robots. Originally developed for autonomous cars, the framework must be assessed and potentially modified to account for the differences in sensor configurations and the distinct characteristics of quadruped robots. Necessary improvements should be identified and implemented as needed.

Betreuung: Dr.-Ing. Rozhin Moftizadeh, Christian Hartberger, M. Sc.

Jahr: 2025

Real World Operational State Estimator for Autonomous Vehicles Based on LoD2 Maps

The objective of this Master’s thesis is to incorporate real sensor data to further develop an existing simulation-based state estimation scheme. The main aims are: Investigate the limitations of the previously developed algorithm when paired with real data, Develop pre-processing algorithms that alleviate these limitations, Suggest necessary additions or modifications to the existing Multi Sensor System (MSS), and Assess the real-time capabilities of the newly developed scheme.

Betreuung: PD Dr.-Ing Hamza Alkhatib, Mohamad Wahbah, M.Sc

Jahr: 2025

Spatio-temporal Change Point detection in InSAR Persistent Scatterer Time Series

The goal of this master's thesis is to utilize deep learning models to detect significant changes in trends and steps of PS time series in a spatio-temporal manner. This approach could help identify areas exhibiting significant land deformation in Germany.

Betreuung: Dr.-Ing Mohammad Omidalizarandi, Kourosh Shahryarinia , M. Sc.

Jahr: 2025

Robust Recursive State Estimation: Application in UAV Pose Determination

This master's thesis initially focuses on investigating and studying various recursive parameter estimators that integrate blunder detection and mitigate their influence. Secondly, it focuses on decision-making and integrating a suitable outlier detector to specific recursive estimators that use fused sensor data to determine the pose of a UAV.

Betreuung: Arman Khami, M. Sc.

Jahr: 2025

ML and Modelling Underwater 3D Point Clouds

Modeling detailed DGMs of waterways using AutoML

Betreuung: Bahareh Mohammadivojdan, Hamza Alkhatib

Jahr: 2022

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