The English-language master’s course of study Earth System Data Science and Remote Sensing is primarily research and method-oriented. You will get to know technologies and methods of environment-related data science and remote sensing comprehensively and can choose from different application areas for specialisation. The course of study aims to train a new generation of earth system scientists who are prepared from the start for the challenges of a data-rich world.

The course of study is subject to local admission restrictions (NCU). Please note the application deadlines and documents to be submitted.

enlarge the image: Visualised time series of vegetation index values from the Landsat 8 satellite from the Sacramento Valley in California (USA)
Visualised time series of vegetation index values from the Landsat 8 satellite from the Sacramento Valley in California (USA), Photo: Prof. Dr. Hannes Feilhauer, Leipzig University, with data from NASA, USGS

In our commitment to diversity, we welcome people of all backgrounds and cultures. We are particularly proud of the fact that more than 1500 students from 38 countries are currently studying in our German and international courses. For an international faculty like ours, diversity and inclusion are important resources for incorporating multifaceted approaches and ways of thinking into innovative teaching and research. We are therefore committed to cosmopolitan coexistence, where everyone is welcome regardless of origin, gender and religion.

Information on the Course of Study

Find out more about the requirements, contents and application for the course of study as well as the career prospects after the study here:

Master Earth System Data Science and Remote Sensing

Additional Information on the Application

If you obtained your first university degree in Germany and meet the following criteria:

  • at least 35 credit points from one or more of the following fields: Geography, Earth System Science, Geosciences, Environmental Science, Life Science, Data Science, Environmental Informatics, Remote Sensing, GIS,
  • prior knowledge of statistics equivalent to at least five credit points,
  • prior knowledge of a scripting language for scientific computing or a higher-level programming language (for example Python, R, Julia, ...), which is usually demonstrated by successful completion of appropriate courses or certificates obtained elsewhere,

please apply via AlmaWeb by 31 May for a start in the winter semester of the same year.

Please upload the following documents as PDF files in AlmaWeb:

  • Curriculum vitae in tabular form
  • Convincing letter of motivation in which you explain your interest in the master's course of study and list your study goals
  • Transcript of records showing all credits earned at the time of application (at least 140 credits must be obtained)
  • If applicable, proof of knowledge of a scientific programming language, if this is not evident from the transcript of records
  • If applicable, a certified certificate of a first professional degree in a geoscientific, natural scientific, environmental scientific or computer science and data science related course of study
  • If applicable, evidence of course-specific vocational training, voluntary internships or similar activities related to your studies
  • Proof of knowledge of the English language at the level B2 of the Common European Framework of Reference

The master's admissions committee uses these documents to check whether you meet the requirements for the admission to the master's course of study. You will receive a written notification about this, which you should submit to the Studierendensekretariat with the other documents for your enrolment.

A start for this course of study is only possible in the winter semester. From the winter semester 2023/24 onwards, admission to the course of study is restricted.

You obtained your first university degree abroad? In this case, please apply directly via uni-assist e.V. by 31 May for a start in the winter semester of the same year.

Structure of the Course of Study

The master's course of study Earth System Data Science and Remote Sensing has set itself the goal of equally covering the areas of technical skills, remote sensing and domain knowledge. You receive in-depth methodological training and set an individual specialisation in an area of Earth System Science for an improved understanding of processes as the core of this course of study. Our lecturers bring in their own research so that the methods are learned in a research-oriented and up-to-date manner. You acquire interdisciplinary skills in the areas of data management and scientific writing.

1st Sem.

Elective Area 1

Remote Sensing Products for Earth System Research Research Data Management and Social Responsibility Free Elective Area
2nd Sem. Introduction to Advanced Data Analytics Spatio-temporal Data Ground Truthing Scientific Writing Free Elective Area or Internship
3rd Sem. Applied Data Analysis of Earth-Surface Processes Data Analysis in Hyperspectral Remote Sensing Imaging and Non-imaging Reflectance Spectroscopy – Techniques and Data Analysis Elective Area 2

Internship or Free Elective Area

4th Sem. Master's Thesis

The information on the module numbers and credit points can be found in the detailed overview

Elective Areas

Elective Area 1 (Alignment)

In elective area 1 (alignment) you complete two modules totalling ten CP depending on your prior knowledge, so that existing gaps are closed. In this way, we create a common knowledge base for our students with different Bachelor degrees.

Sem. Module No. Module Title CP
1 12-GEO-M-AG01 Introduction to Data Science 5
1 12-GEO-M-AG02 Earth System Components 5
1 12-GEO-M-AG03 Introduction to Environmental Remote Sensing 5

Elective Area 2 (Further Methods)

In the elective area 2, you choose a module with five CPs. Through this selection, you complement your in-depth methods training.

Sem. Module No. Module Title CP
3 12-111-1036 E2 – Ground-based Radar and Microwave Remote Sensing 5
3 12-111-1038 E4 – Active Remote Sensing with Lidar 5
3 12-GEO-M-RS03 Introduction to Microwave and Lidar Remote Sensing 5

Free Elective Area (Applications)

In the free elective area, you select modules totalling 20 CP on the basis of subject cooperation agreements. You can choose from numerous modules from related courses of study and thus set an application focus. You can also select modules here that you have not taken in the elective area 2.

Upon application, other modules for the free elective area can be approved by the examination board in justified individual cases, provided that the person responsible for the module and the offering institute accept students from the course of study MSc Earth System Data Science and Remote Sensing.

Sem. Module No. Module Title CP
1/2 12-GEO-M-SP01 Applied Topics in Earth System Science 5
1 12-GEO-MSC-01 Sediments and Environment 10
1/2 12-GEO-MSC-07 Geology of the Cenozoic Era 10
Sem. Module No. Module Title CP
1 12-111-1001 Dynamics and Synoptics 6
1 12-111-1019 Atmospheric Radiation 5
2 12-111-1021 Dynamics of the Global Climate System 6
2 12-111-1043 A4 – Polar Climate 5
1 12-111-0001 P1 – Introduction to Meteorology 5
2 12-111-0033 Introduction to Climatology 10
Sem. Module No. Module Title CP
1 12-GGR-M-PG01M Environmental Change and Natural Risks 10
1 12-GGR-M-PG02M Environmental Geophysical Site Assessment 5
2 12-GGR-M-PG04 Laboratory Methods in Physical Geography 10
1 12-GGR-M-AG11 Urban Areas: Theories and Current Research Perspectives 10
1 12-GGR-M-AG12 Advanced Methods in Regional Studies 10
Sem. Module No. Module Title CP
2 11-BIO-109 Plant Physiology 10
1 11-BIO-115 Molecular Plant Physiology 10
2 11-BIO-124 Ecology of Vegetation and Plant Geography 10
2 11-BIO-L03 Ecology (Teaching Degree Programme) 10
2 11-BIO-206 Macroecology and Macroevolution under Global Change 10
2 11-BIO-208 Biogeography and Tropical Botany 10
2 11-BIO-209 Biodiversity and Ecosystem Functioning 10
2 31-BIO-221 Essentials of Conservation Biology and Ecological Modeling 10