Human-driven environmental changes — from accelerating land-use change and biodiversity loss to more frequent climate extremes — demand new ways of observing and understanding the Earth. This MSc brings together modern data science and remote sensing to address those challenges. You will learn to work with global data streams and multiple types of Earth observation (optical, LiDAR, radar, spectroscopy) while drawing on strong domain expertise available at the host institution in areas such as geoecology, biodiversity research, meteorology, eco‑hydrology and related fields. The university’s Remote Sensing Centre and active data‑science initiatives provide the technical and academic infrastructure for hands‑on, interdisciplinary training.
The programme aims to produce Earth system scientists who combine subject‑specific knowledge with coding and quantitative methods, with particular emphasis on state‑of‑the‑art remote sensing technologies. Teaching mixes in‑depth methodological training with opportunities to specialise in a particular Earth system domain so that graduates become method experts in their chosen application area. Instruction is in English and the course is geared to international students who want to work at the interface of environmental science, computing and observation technologies.
The degree is completed over two years (120 ECTS) and includes practical elements such as a national or international research internship and a master’s thesis, alongside courses that build scientific writing and research data management skills.
Program structure (120 ECTS total, two years)
The programme is structured as a set of independent modules, each covering a clearly defined topic or cluster of related topics. Modules may combine different teaching formats — lectures (L), seminars (S) and practical, hands-on training (P) — and are each completed with a final examination. Credit points (ECTS) indicate the expected student workload for each module; one ECTS equals about 30 hours of work.
Most modules in the MSc carry a workload of 5 ECTS, and together they are designed to build both theoretical understanding and practical skills in Earth system data science and remote sensing. You will take foundational “basic introduction” modules (classified as WP), select methodological and soft-skills modules (mandatory practical components) to develop analytical and professional competencies, and choose from application-focused modules (W) to tailor the degree toward particular areas of interest. Overall learning outcomes include the ability to master core subject knowledge, apply quantitative and practical methods to Earth system and remote-sensing data, and communicate results effectively in applied contexts.
Modules are independent in organisation and are assessed individually by the module’s concluding exam. The programme balances compulsory elements (method modules and soft-skill practicals) with elective options (basic-introduction selections and application-oriented modules), allowing you to shape your course of study while ensuring key methodological and professional skills are acquired.
Requirements (concise)
To be admitted you must hold a first professionally recognised bachelor’s degree (or a degree from a state or state-recognised university of cooperative education — German "Berufsakademie"). Any additional certificates or qualifications must be formally acknowledged by the programme’s responsible administration. If you studied outside Germany, the university offers a service to check whether your international degree qualifies you for study and to advise on any country-specific entry rules.
The programme requires a subject-relevant background and specific academic preparations. It is admission-restricted (places are limited), so you must submit a complete application package that includes proof of your academic record and documents demonstrating relevant skills and motivation.
Winter Semester (International)
31 May 2026
Winter Semester (EU/EEA)
31 May 2026
Graduates will be prepared for roles that require the integration of remote sensing and data-science expertise with domain knowledge in Earth and environmental sciences. Typical career paths include positions in environmental and earth-system research institutes, governmental and international agencies (climate and natural-resource monitoring), environmental consultancies, NGOs, and geospatial or Earth-observation companies.
The programme’s strong methodological focus also equips graduates for further research (PhD) or technical roles involving geospatial data pipelines, machine-learning model development for environmental applications, and the design and interpretation of monitoring systems using satellite and airborne sensors.