master thesis remote sensing

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Chair of Earth Observation and Remote Sensing

Master thesis.

General guidelines can be found here , while more information regarding citation etiquette can be found here .

Examples of recently-completed projects are listed below. A complete list is located at the bottom of this page.

Revealing the Recent Height Changes of the Great Altesch Glacier Using TanDEM-X DEM Series

Student:  Pierre-Louis Vlieghe Supervisor:  Prof. Dr. Irena Hajnsek, Shiyi Li Time period: 2023

Monitoring glacier mass balance is essential for understanding glacier-climate interactions and predicting water resources management. As the largest glacier in the Alps, the Great Aletsch Glacier plays a significent role in understanding the dynamics of glacier mass change in this region. The TanDEM-X satellite mission has selected the Great Aletsch Glacier as a super-testsite and has collected abundant single-pass bistatic Synthtetic Aperture Radar (SAR) data over the glacier since 2011. In this project, leveraging the TanDEM-X data, we generated 124 digital elevation models (DEMs) from the Coregistered Single-look Slant Range Complex (CoSSC) data product, calculated glacier elevation changes between 2011 and 2022, and quantified the temporal dynamics of the mass balance of the Great Aletsch Glacier.Our results revealed a consistent glacier-wide height loss of 1 meter per year on average between 2011 and 2022, corresponding to a cumulative volumetric ice loss of 79×106 cubic meter per year and mass loss of 68 Mt per year (assuming a mean ice density of 850 kg/m3. Notably, the Konkordiaplatz region, situated at elevations between 2600 and 2800 meters, exhibited an average elevation loss of 2.3 m a−1, whereas the Glacier tongue region, ranging in elevation between 1900 and 2100 meters, witnessed an average elevation loss of 5.2 m a−1. Our results have provided valuable insights into the dynamic changes of the Great Aletsch Glacier by analyzing the abundant TanDEM-X data. The detailed spatiotemporal of our work advanced our understanding of glacier recession in the Alps under the climate change.

Coral Reef Shapes and Benthic Mapping Capabilities of Sentinel-2 Bands and Spectral Indices

Student: Giulia Zobrist Supervisors: Prof. Irena Hajnsek Dr. Lanqing Huang Time period: 2022

Coral reefs are marine underwater ecosystems present in most of the tropical and shallow ocean water on the globe. Due to anthropogenic intervention and the consequent rise of ocean temperature the coral reefs have been experiencing drastic changes in the last years. Monitoring these changes is imperative not only for biodiversity purposes but also for the social impact on the coastal communities. Remote sensing (RS) offers great possibilities to monitor coral reefs on a global scale. This Master’s thesis explores the applications of remote sensing for coral reef studies and presents a pipeline for studying coral reef shapes and spectral features. Consecutively, a machine learning framework was applied for substrate classification. The study concludes that the most important Sentinel-2 bands for classifying underwater reef substrates are bands 1 to 5 and that the spectral water indices derived from Sentinel-2 bands are effective to separate the substrate rock from the others. It also concludes that there are some visible trends in the shape of coral reef regionally. Finally, this study provides a machine learning framework for benthic classification whose F1 score is higher than 60%.

Full list of MSc Theses

Pierre-Louis Vlieghe:   Revealing the Recent Height Changes of the Great Altesch Glacier Using TanDEM-X DEM Series

Giulia Zobrist:   Coral Reef Shapes and Benthic Mapping Capabilities of Sentinel-2 Bands and Spectral Indices

Clotilde Marmy:  Exploration of methodologies for landslide susceptibility mapping in Valais

Henry Holsten: Application of Sentinel-1 data to quantify Arctic Coastal Retreat

Xiaochen Zheng:   Rare Wildlife Recognition with Self-Supervised Representation Learning

Cédric Tompkin: The Role of Local Resolution Weighting in Automatic Avalanche Mapping with Sentinel-1

Simon Frasch: Parallelized Time-Domain Synthetic Aperture Radar Imaging on GPGPUs

Wicki Raphael : Detection feasibility of snow avalanches in TerraSAR-X datasets for rapid mapping

Round, Vanessa: Surge dynamics and lake outburst of Kyagar Glacier, Karakoram (Co-Supervision)

Liao, Juanwei: Assessment of the Ground Phase Line-fit Estimation Procedure over Agriculture from Polarimetric Interferometric SAR Data

Jing, Huo: The Application of Remote Sensing in PM10 Monitoring in Switzerland (Co-Supervision)

Weber, Melchior: Observing Seasonal Flooding in the Kafue-Flats (Zambia) with Tandem-X Data

Chesnokova, Olga: Analysis on the Relation between Statistical Similarity Measures and Agricultural Parameters: A Case Study

Master's Programme in Geomatics with Remote Sensing and GIS

• 120 credits cr.
• Gå till denna sida på svenska webben

This Master’s programme develops students’ skills in several fields, such as remote sensing, GIS, methods for modelling, explorative data analysis and visualisation with a focus on Earth and Environmental Sciences.

Landscape change, environmental monitoring and mapping, as well as environmental issues in general, feature significantly on the daily political agenda.

Teaching emphasizes both hands-on experience and the exploration of fundamental concepts and methods and is linked to research undertaken at the department. Outreach activities, internships and research collaborations ensure our students gain insights into real world problems and applications leading to enhanced opportunities when entering the job market.

Geographical information, also known as geodata, is central to many modern activities from parcel tracking to storm tracking and navigation to monitoring elephant behaviour. Satellite data is used in global activities such as the evaluation of progress towards sustainable development goals, estimations of carbon storage and emissions, mapping glacier dynamics and evaluating ecosystem health. Remote sensing systems from laser scanning and radar to hyperspectral imaging are introduced. Geographic information systems (GIS) make efficient management of such diverse data possible, facilitating many different types of analysis and modelling, in a future accelerating towards the exploitation of Big Data. Landscape change, environmental monitoring and mapping, as well as environmental issues in general, feature significantly on the daily political agenda. This situation is further enhanced by environmental agreements that demand the continuous reporting of the status of and changes in the environment at municipality to international scales. Geomatics is central to meeting these demands. Consequently, graduates mastering skills in data acquisition methods and analysis, as well as in visualisation and mapping, are in high demand in both the public and private sectors. 

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Programme overview

The two-year master’s programme consists of 120 credits:.

45 credits Mandatory advanced courses 15–45 credits Optional courses 30–60 credits Master thesis (mandatory)

Autumn term

Applied Remote Sensing, and GIS for Landscape Analysis, 15 credits (GE7088)

Geographic Analysis and Visualization in GIS, 15 credits (GE7089)

Spring term

Advanced Remote Sensing, 15 credits (GE7090)

Optional courses, 15 credits

The number of optional courses taken will be dependent on the period of time devoted to the Master thesis 30, 45 or 60 credits, which may extend over one or two terms:  Degree Project in Physical Geography and Quaternary Geology 30/45/60 credits (GE9009).

How to apply

All applications must be sent through www.universityadmissions.se. January 15 2024 – last date to apply for all applicants.

Required supporting documentation

In addition to the documents required by www.universityadmissions.se, the following documents must accompany all applications to this master’s programme:

• Personal letter/Letter of interest (maximum one page). Please indicate how you fulfill the specific requirements for the programme in the letter. Further information:  Frequently asked questions about admissions
• Brief summary of the grading system of your university (if other than ECTS).

If you are still studying for your Bachelor degree when making the admission application then please write in the personal letter which courses and credits are yet to be completed.

Meet our students

Meet robert salmijärvi.

A former student at the Master's Programme in Geomatics with Remote Sensing and GIS

Meet our teachers

Our researchers. your teachers..

Education and research are closely linked at Stockholm University. As a student, you will have direct contact with leading researchers in your field and access to the most recent scientific findings. Meet Gustaf Hugelius here.

Questions and Answers Ian Brown, Programme responsible about this Programme:

We have had very positive feedback from employers!

Who should apply to this programme?   Geographers, geoscientists, biology-Earth sciences who want to develop their knowledge and skills in geodata management and spatial analysis with GIS and remote sensing.     What is specific for this programme?  The programme focuses on the development of knowledge towards real everyday applications in geography and earth sciences.    Is there an opportunity for studies abroad and internships?  Yes. We have had students who have worked from the Arctic to Africa.    How do you think the students should consider when choosing optional (elective) courses within the programme?   Students can choose from a wide range of courses: modeling, statistics and programming have been chosen by former students e.g.    What skills do students acquire after graduation?   GIS and geodata skills.    What kind of jobs do the students usually get after their studies?  Consulting jobs in geodata, planning and jobs within municipalities, county administrative boards or authorities.    What is most fun with this education?  Group work, problem solving, the opportunity to explore socially important problems and new technologies (satellite data, drones, topics such as environmental health and climate).    How is it to teach on this programme?!  Fun, challenging. The student groups are very diverse with students from different backgrounds and countries.    Anything else you would like to tell us about the education?  We have had very positive feedback from employers!    What do you do when you're not researching/teaching?  Sleeping and running.    What is your research subject?  Snow, ice sheets, radar, ecosystems.    What education did you choose?   Geography and history, both interesting topics with societal relevance.    Your best tip for an aspiring student?   Follow your interests! 

We are several persons working with study administration and study counselling. Please contact the Student office for questions concerning course information, registration, schedule, literature lists and exams. If you have questions concerning credit transfer, admission, eligibility or need study advice please contact the Study counsellor .

Program responsible Ian Brown E-mail: [email protected]

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The faculty at a glance

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• Faculty of Physics and Earth System Sciences

work Institutsgebäude Linnéstraße 5 04103 Leipzig

Phone: work +49 341 97 - 32400

Dean of Studies Prof. Dr. Christoph Zielhofer

Vice-Dean for Research Prof. Dr. Frank Cichos

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Dean of Studies for Physics and Meteorology Prof. Dr. Michael Ziese

Deanery Dr. Annett Kaldich

Secretariat Susan Baeumler

Institutes & Facilities

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• Felix Bloch Institute for Solid State Physics
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Master Earth System Data Science and Remote Sensing

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.

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:

Additional Information on the Application

First university degree obtained in germany.

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.

First University Degree Obtained Abroad

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.

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.

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.

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.

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Remote Sensing, geoInformation and Visualization | Master

This English-language master’s degree program focuses on the gathering, processing, analysing, and presentation of geoscientific spatial data by using remote-sensing technologies and data-processing methods. The program uses models and theories to assess geoinformation, and then to prepare and communicate our findings with modern means of visualization.

• PROGRAM FLYER (PDF 269KB)
• FACULTY PAGES

Prof. Dr. Bodo Bookhagen,

„This new international degree program, established at one of Germany’s leading geoscientific research universities and research centers, combines geological remote sensing with geoinformation systems and visualization to clearly communicate scientific results.“

Program Content

In the Remote Sensing, geoInformation and Visualization master's degree program, you will develop an advanced understanding of remote sensing in theory and practice. The program begins by addressing fundamental principles in the recording and processing of spatial data as they are typically gathered by means of remote sensing methodologies. The program teaches advanced scientific principles of physics, chemistry, and biology to quantify environmental process, the recording of remote sensing data and their interaction with the environment, as well as practical skills in the application of modern data processing methods. The program will grant you an overview of the broad range of available remote sensing technologies and data-processing methodologies. You will learn how to apply these technologies and methods to specific problems in scientific and applied scenarios.

We use modern data visualization tools to prepare our data, for example in the generation of prognoses, scientific communication, and the comprehensible presentation of data to representatives from other disciplines as well as non-specialist decision-makers. The program thereby offers a comprehensive, interdisciplinary understanding of, as well as a critical perspective towards, the solution and evaluation of geoscientific questions.

Course Objective and Future Career Options

In addition to application-oriented specialist knowledge in the fields of remote sensing, geoinformation and visualization, a Master of Science degree in our field puts you in a position to define scientific problems, formulate suitable hypotheses, design research projects, to apply for funding, and to administer scientific projects.

Future fields of work include positions in public administration, such as in municipal, regional and land use planning; natural disaster management and response, as well as  environmental monitoring; research in the university and in institutions outside universities. Diverse employment opportunities are also possible in the IT industry, for example in software development in the field of digital mapping; in the insurance and real estate industry; the construction industry; the transportation industry; and in the leisure and tourism sectors.

Prerequisites for Admission to the Master’s Program

Admission to the Remote Sensing, geoInformation and Visualization master’s degree program requires a qualifying university degree in the field of the geosciences, geography, physics, mathematics, biology, environmental sciences, information science, or a similar program of study with a standard period of study of at least three years and a total share of at least 36 credit points (CP) in the geosciences, biology, physics, chemistry or information science. An additional 12 CP of mathematics coursework as well as 12 CP of geosciences coursework must also be documented. Moreover, your English language skills must correspond at least to the B2 level of the Common European Framework of Reference for Languages (CEFR). Applicants who are not a German citizen must demonstrate sufficient German language proficiency corresponding to the level A2 (CEFR).

You can read more about the subject-specific admission requirements in the respective Admission Regulations .

Program Structure

In the four-semester master’s program, you will earn a total of 120 credit points, consisting of the following modules and your master’s thesis: For additional information, please consult the subject-specific Degree Regulations or the Departmental Advisory Office .

Institute of Geosciences

Prof. Dr. Bodo Bookhagen | Departmental Student Advisor & Chair of Examination Board

•   +49 331 977-5779
•   rsiv u geo.uni-potsdam p de

Campus Golm Building 27, Room 1.39

Advantages at a Glance

The Remote Sensing, geoInformation and Visualization master's degree program at the University of Potsdam offers a diverse array of opportunities for specialization in the design of custom-made plans for study. Practical components of the program also offer you the opportunity to acquire professional and research-oriented competences, thereby facilitating a smoother entry into your future career. Our close cooperation with industry and research institutions both in Germany and abroad – such as the nearby Helmholtz Center Potsdam - Research Center for Geosciences ,  Potsdam Institute for Climate Impact Research , Institute for Advanced Sustainability Studies and the Alfred Wegener Institute of Potsdam – also contributes to this effort.

The University of Potsdam takes into account the actual living conditions of its students and has introduced the possibility of part-time study for many degree programs. This also pertains to the Remote Sensing, geoInformation and Visualization program. To learn more, and to find a list of subjects appropriate for part-time study, please see part-time study at the University of Potsdam.

• Application

Have you decided to study the English-language master’s degree in Remote Sensing, geoInformation and Visualization at the University of Potsdam? Then you should take the next step on the application pages to find out more about current application and enrollment procedures.

Important Links

• Departmental Student Advisor
• Study and Examination Regulations
• Admission Regulations

This description is based in part on information from the subject-specific regulations for a master’s degree in Remote Sensing, geoInformation and Visualizationat the University of Potsdam dated February 15, 2017 (AmBek No. 13/17, p. 562).

• Master Theses

Proposed Topics for Master Theses

The staff of the Chair of Remote Sensing are always open for indiviudal ideas. Just contact us.

If you are interested in a BSc thesis in the context of biodiversity, nature conservation and remote sensing, please contact Dr. Martin Wegmann .

Current Theses

Master's course "eagle", university of würzburg, master's course "global change ecology", university of bayreuth, completed theses.

• Zehner, M . (2021): Characterization of individual urban trees using combinations of VHR remote sensing and auxiliary data
• Groth, S . (2021): Deep multi-task learning for building characterization with street-level imagery
• Mast, J . (2021): Analysing the relationship between urban morphology and economic subcenters
• Sogno, P . (2021): Earth Observation for Exposome Mapping - Proof of Concept and Case Study in Augsburg, Germany
• Halbgewachs, M . (2021): Deforestation and forest fragmentation in Mato Grosso, Brazil
• Fisser, H . (2021): Erfassung von Verkehrsaktivitätenmustern zur Ableitung von Verkehrsdichte und Emsissionsfaktoren
• Lee, B. C . (2020): Development of a semi-analytical model for seagrass mapping using cloud-based computing and open sourced optical satellite-data
• Wang, M . (2020): Comparison of Surface Urban Heat Islands Using the World Settlement Footprint Imperviousness Layer
• Buchelt, S . (2020): Mapping High-Resolution Spatio-Temporal Patterns of Snowmelt using Orthorectified Photo Cameras & Sentinel-1 Time Series Data
• Adelware, O . (2020): Application of Remote Sensing Techniques to detect historical landslides for improving risk assessment in Antioquia, Colombia
• Soltani, S . (2020): Spatio-temporal Analysis of Urbanization caused by the New Silk Road
• Glasmann, F . (2020): Potential of the Firebird Mission for the Detection of Gas-flaring Activity
• Klein, R . (2020): The Water Use Efficiency Monitor in Central Asia (WUEMoCA) as a tool for supporting water management in the Aral Sea Basin
• Kluter, P . (2020): Deep Learning Approach to Ship Detection and Classification Using Synthetic Aperture Radar Data
• Gnann, N . (2020): Identification of anthropogenic debris assisted by unmanned aerial vehicles and deep learning
• Turulski, K . (2020): Ableitung hyperspektraler Indices zur Bewertung von Trockenstress unter Verwendung von HySpeX Daten
• Hasenbein, K . (2020): The potential of time-series data to improve fine scale mapping of land use in heterogeneous landscapes
• Abu, I.-O . (2020): Detection of Cocoa Plantages in complex forest landscapes Cocoa mapping in West Africa
• Ahmed, F . (unpublished Master thesis 2020): Agricultural landscape Configuration and Pattern Analysis with VHR Imagery in Bavaria Seite, 88.
• Steiner, S . (2020): Assessing the Potential of a Land Cover Dependent Snow Cover Detection Algorithm for the Global SnowPack
• Orthofer, A . (2020): Deriving Leaf Area Index and mowing dates for grasslands based on the radiative transfer model SLC and Sentinel 2 data
• Beck, L . (2020): Multi-Annual Flood Mapping using Multi-Sensor Satellite Data in the Iishana Sub-Basin (Namibia/Angola)
• Singh Dhillon, M . (unpublished Master thesis 2019): Comparing the performance of crop growth models using synthethic remote sensing data at DEMMIN, Germany
• Kurtenbach, M . (2019): Erfassung und Analyse der oberflächennahen Bodenfeuchte und deren Dynamik im agrarisch geprägten Süden Italiens mit fernerkundlichen Daten und Methodiken. (Master thesis), Julius-Maximilians-University Würzburg, Germany Seite, 120.
• Selbmann, A.-K . (unpublished Master thesis 2019): Spatial patterns of wildfire severity and vegetation in the Yokon-Kuskokwim-Delta, Alaska Seite, 65.
• Groll, M . (unpublished Master thesis 2019): Deep learning for Instance Segmentation of bomb craters on historical aerial images of the Second World War Seite, 96.
• Endara Pinillos, P . (unpublished Master thesis 2019): Flooding patterns and vegetation development in the Orinoco flooded savannas of Colombia Seite, 55.
• Reiter, M . (unpublished Master thesis 2019): Comparing Urban Green Spaces in German Cities Using Remote Sensing Data
• Roersch, S . (unpublished Master thesis 2019): Development of a semi-automated method to measure solar potential
• Roersch, S . (unpublished Master thesis 2019): Development of a semi-automated method to measure solar potential Seite, 70.
• Baur, M. J . (unpublished Master thesis 2019): Global Characterization of Vegetation Canopy Properties and Their Dynamics Using Microwave Radiometry. Seite, 40.
• Sauerbrey, J . (unpublished Master thesis 2018): Integration of SAR and Optical Satellite Imagery: Time-Series Analysis of Sentinel-1 and Sentinel-2 Imagery for Detection of Active Morphodynamics: A Case Study in the Atacama Desert, Chile. Seite, 96.
• Löw, J . (2019): Interferometric and polarimetric signatures of agricultural crops using multi-temporal dual-polarimetric Sentinel-1 imagery: a case study in north-eastern Germany Seite, 81.
• Salerno, C . (unpublished Master thesis 2019): Remote sensing assessment of projected sea level rise on land use and the urban coastal city of Cape Town, South Africa Seite, 21.
• Reiter, M . (unpublished Master thesis 2019): Comparing Urban Green Spaces in German Cities Using Remote Sensing Data Seite, 116.
• Wiertz, K . (unpublished Master thesis 2019): Development of a semi-automatic remote sensing approach for change detection of forest structures in Bialowieza Forest Seite, 51.
• Miah, J . (unpublished Master thesis 2019): Detecting and Assessing Ground Subsidence of Dhaka City, Bangladesh, Using Synthetic Aperture Radar Data of Sentinel-1 Seite, 70.
• Hendel, A.-L . (unpublished Master thesis 2018): Effects of rain-on-snow and basal ice on seasonal NDVI in High Arctic Svalbard: a multi-scale approach Seite, 50.
• Saadallah, A . (unpublished Master thesis 2019): The Potential of Earth Observation for Monitoring Agricultural Lands in Egypt (1984-2017) Seite, 53.
• Nolting, S . (unpublished Master thesis 2019): Risk Assessment for Flood Events based on Geo- and Socioeconomic Data - A Case Study for North-Rhine Westphalia, Germany Seite, 89.
• Philipp, M . (unpublished Master thesis 2018): Potential of harmonic analysis using remote sensing data for studying the effects of climate change induced weather extreme events on forest ecosystems Seite, 164.
• Schwalb-Willmann, J . (unpublished Master thesis 2018): A deep learning movement prediction framework for identifying anomalies in animal-environment interactions
• Stiller, D . (unpublished Master thesis 2018): Analysing Spatio-temporal Patterns of Coastal Aquaculture Based on Three Decades of Satellite Data
• Schulte to Bühne, H . (unpublished Master thesis 2017): Quantifying land cover change using remote sensing data in a transboundary protected area Seite, 63.
• Karg, S . (unpublished Master thesis 2017): Burn scar detection using polarimetric ALOS-2 time-series data
• Weiser, F . (unpublished Master thesis 2017): Assessing the forest response along treelines to an Epirrita autumnata outbreak in Abisko, using a combination of fieldwork and remote sensing
• Biber, M. F . (unpublished Master thesis 2017): Can animal movement and remote sensing data help to improve conservation efforts? - A case study on plains and Grevy’s zebras
• Maier, P. J. M . (unpublished Master thesis 2017): Modellierung von Erntemengen für Hopfensorten in der Hallertau mittels Deep Learning Algorithmen auf Basis von Klima- und Satellitendaten Seite, 114.
• Binnig, J . (unpublished Master thesis 2017): Entwicklung eines räumlich-dynamischen Ansatzes zur fernerkundungsbasierten Modellierung der tatsächlichen Evatranspiration von Bewässerungsregionen im Aralseebecken Seite, 87.
• Staab, J . (unpublished Master thesis 2017): Applying Computer Vision of Monitoring Visitor Numbers Seite, 65.
• Reinermann, S . (unpublished Master thesis 2017): Extreme Events in Europe between 2000 and 2017: Analysis of Vegetation Dynamics based on Earth Observation Times Series Seite, 49.
• von Uslar, J . (unpublished Master thesis 2017): Der Einfluss stratifizierter Sampling Mehtoden auf multi-temporale, objektbasierte Random-Forest Klassifikation Seite, 86.
• Premier, J. B . (unpublished Master thesis 2016): The Lynx Effect: Behaviour of Roe Deer in the Presence of Lynx in a European Forest Ecosystem
• Ulloa Torrealba, Y. Z . (unpublished Master thesis 2016): Land change in the Main catchment with an Object Based approach using eCognition
• Stephani, A . (unpublished Master thesis 2016): Impact of remote sensing characteristics for biodiversity monitoring - A case study of Southern Myanmar mangroves
• Kuhn, J . (unpublished Master thesis 2016): Using very high resolution remote sensing imagery to assess crop diversity in the Fergana Valley, Uzbekistan
• Bolkart, M . (unpublished Master thesis 2016): Mapping and Monitoring Locust Habitats in the Aral Sea Region based on Satellite Earth Observation Data
• Schumann, B . (unpublished Master thesis 2016): Ermittlung der Baumkronendichte des Ober- und Unterstandes in heterogenen Wäldern Hilfe von multitemporalen LiDAR- Daten
• Asja, B . (unpublished Master thesis 2015): Mind the Gap: A Global Analysis of Grassland Fragmentation using MODIS Land Cover Data
• Hill, S . (unpublished Master thesis 2015): Predicting the Forest Development after Natural Disturbance in the Bavarian Forest National Park using Airborne LiDAR
• Duguru, M . (unpublished Master thesis 2015): Trends in Indices for Extreme Precipitation in Western Africa
• Beroya-Eitner, M. A . (unpublished Master thesis 2015): Flood Vulnerability Index for Delta Socio-Economical Systems: Application to the Mekong River Delta, Vietnam
• Gnoyke, P . (unpublished Master thesis 2015): Large Land Acquisitions in East Africa. An examination of spatial dynamics through remote sensing
• Graf, W . (unpublished Master thesis 2015): Suitability of LiDAR and texture measures of aerial distribution of Glaucidium passerinum (pygmy owl) in Vercors, French Alps
• Sieg, T . (unpublished Master thesis 2015): The potential of interferometric and polarimetric SAR data to characterize urban areas at the example of Mumbai and Manila
• Hess, A . (unpublished Master thesis 2015): Deforestation in Myanmar – what can we say about causes?
• Broszeit, A . (unpublished Master thesis 2015): Assessing long-term inland water quality using satellite imagery: A feasibility and validation study of different lake types
• Rossi, M . (unpublished Master thesis 2015): Statistische Analyse von Standortfaktoren zur Erklärung phänologischer Zeitpunkte am Beispiel von Grünlandflächen im Alpenvorland
• Vollmuth, M . (unpublished Master thesis 2015): Zusammenhänge der Schneedynamik und des Abflussverhaltens im Einzugsgebiet des Naryn - Statistische Betrachtungen und physiogeographische Erklärungen
• Malec, S. S . (unpublished Master thesis 2015): Assessment of Soil erosion parameters in Costa Rica using reflectance hyperspectral and simulated EnMAP imagery
• Ziewers, K . (unpublished Master thesis 2014): Declining migratory avian species in the UK: a consequence of habitat quality alteration in western Africa?A case study using Remote Sensing Data
• Baron, D . (unpublished Master thesis 2014): Analysis of MODIS time series data for characterization of hydrometeorological factors in relation to landslide activity in Southern Kyrgyzstan
• Ortmann, A . (unpublished Master thesis 2014): Estimating land cover changes and current carbon stock in Tanzania in the context of REDD+
• Sokol, V . (unpublished Master thesis 2014): Interaction between white stork migration patterns and urban environment in Germany
• Braun, D . (unpublished Master thesis 2013): Estimating the current and future human impact in Tanzania for wildlife corridor management Seite, 77.
• Panah, S. S. A . (unpublished Master thesis 2013): Relationship Between Land Surface Temperature and the Ratio of Urban area und Urban Parks - An Appplication for the City of Munich (Germany)
• Wohlfart, C . (unpublished Master thesis 2013): Mapping tropical dry forest in South East Asia using a continuous cover approach Seite, 59.
• Dambroz, C. S . (unpublished Master thesis 2013): Analysing forest fragmentation characteristics among continuous vegetation gradients in South America Seite, 40.
• Reichmuth, A . (unpublished Master thesis 2013): Detection of forest parameters using imaging spectroscopy
• Kachelrieß, D . (unpublished Master thesis 2013): Analysis of the effectivity of Marine Protected Areas – a case study using Remote Sensing for the Chagos Archipelago Seite, 63.
• Bell, A . (unpublished Master thesis 2013): Moving Forward Application of behaviour change pont analysis and species distribution models in conservation
• Plum, C . (unpublished Master thesis 2012): The underuse of remote sensing in ecology and conservation: Quantifying technical and cultural constraints hindering a deeper rootage of remote sensing as a standard tool in biodiversity and conservation sciences Seite, 132.
• Reise, J . (unpublished Master thesis 2012): Impact of model algorithm selection and remote sensing data selection on the analysis of species-habitat associations and the prediction of species distribution: A case study using camera trap data of dhole and leopard in Cambodia Seite, 55.
• Früh, A . (unpublished Master thesis 2012): Historic changes in regional ecosystem service demand: The impact of settlement change on flood mitigation in the upper Main basin
• Simang, A . (unpublished Master thesis 2011): Influence of habitat and governance for landscape level conservation on Asian elephants Seite, 73.
• Edlinger, J . (unpublished Master thesis 2011): The Soviet heritage in the Aral Sea Basin: Monitoring the expansion and intensification of crop production in the Karshi irrigation district, Uzbekistan, between 1972 and 2009 using Landsat time series Seite, 55.
• Knauer, K . (unpublished Master thesis 2011): Monitoring ecosystem health of Fynbos remnant vegetation in the City of Cape Town using remote sensing
• Zeidler, J . (unpublished Master thesis 2009): Field-based agricultural land-use classi cation and analysis in Khorezm, Uzbekistan for the years 2004 to 2007 Seite, 30.

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Geographic Information Science with Remote Sensing, Master of Science

Department of geography planning & recreation, graduate coordinator.

A 30-unit program that integrates geospatial problem solving with state of the art geographic information systems (GIS) and remote sensing technologies. The program emphasizes geodatabase management, programming for GIS, geographic data analysis, geovisualization, web mapping, image analysis, and location intelligence. The graduate will be prepared to take leadership roles in geospatial data management and analysis in many fields and industries.

Degree Info Tab Open

Requirements tab open, overview tab closed, details tab closed, availability tab closed, requirements accordion open.

To receive a master’s degree at Northern Arizona University, you must complete a planned group of courses from one or more subject areas, consisting of at least 30 units of graduate-level courses. Many master’s degree programs require more than 30 units. You must additionally complete:

• All requirements for your specific academic plan(s). This may include a thesis.
• All graduate work with a cumulative grade point average of at least 3.0.
• All work toward the master's degree must be completed within six consecutive years. The six years begins with the semester and year of admission to the program.

Read the full policy here .

Overview Accordion Closed

In addition to University Requirements:

• Complete individual plan requirements.

Purpose Statement The MS in Geographic Information Science with Remote Sensing program prepares GIS professionals who will take leadership roles in geospatial data management and analysis in many fields and industries.  It integrates geospatial problem solving with state of the art geographic information systems (GIS) and remote sensing technologies. The program emphasizes geodatabase management, programming for GIS, geographic data analysis, geovisualization, web mapping, image analysis, location intelligence, and project management. It is designed for working professionals or new college graduates with a Bachelor's degree in any discipline who want to elevate their career or develop a new career in GIS and remote sensing. Upon completion of the program, students will be able to demonstrate abilities in effectively managing and analyzing geospatial data, working with remotely sensed images, producing high-quality maps, publishing interactive web maps, developing GIS tools and automating spatial data processing, as well as developing solutions for GIS problems and managing GIS projects. Graduates will be able to find opportunities and play leadership roles in fields and industries such as urban and regional planning, transportation planning, environment and resource management, energy development and management, and utility management, in either government or private sector. Student Learning Outcomes

• Explain map projection, datum, and coordinate systems.
• Define coordinate system to data and perform transformation between coordinate systems.
• Explain spatial data representation and data models and perform between different data formats.
• Explain how spatial and attribute information is stored in the computer.
• compile, create, and edit geospatial data
• work with personal, file, and enterprise geodatabase
• create and work with attribute domains, relationships, topology, and versions in enterprise geodatabase
• Develop spatial analysis procedures.
• Prepare and preprocess data for spatial analysis.
• Perform vector-based and raster-based analysis.
• Effectively find and use geoprocessing tools.
• Perform raster-based analysis using map algebra.
• Interpret analysis results.
• Identify problems, goals, and objectives of GIS applications.
• Source data that are in appropriate format and quality for the applications.
• Develop strategies and workflows for solving the problem.
• Develop cartographic models to implement the strategies and workflow.
• Implement the cartographic models using ArcGIS geoprocessing tools and ModelBuilder.
• Creating Python script to implement geoprocessing automation.
• Develop custom tools using Python scripts.
• Interpret model output.
• Describe the project.
• Identify problems, goals, and objectives of projects.
• Develop strategies, methodology, and procedures.
• Prepare data that meet demands of projects.
• Solve the problems by analyzing data.
• Interpret and discuss the analysis results.
• Provide management or policy recommendations.
• Develop project plan including resources and timeline.
• Create professional project reports.
• Explain the server-client model in web mapping.
• Explain web map service and web feature service protocol.
• Explain and use vector data formats GML and GeoJSON for web GIS.
• Publish maps on the web using ArcGIS online, StoryMaps, and leaflet.
• Client-side map customization using JavaScript and CSS.
• Explain basic concepts of remote sensing including platforms, sensors, properties electromagnetic radiation, etc.
• Effectively use popular and publicly available remotely sensed data sources.
• Perform imagery data processing and visualization.
• Perform supervised and unsupervised classifications.
• Interpret imagery data.
• Develop environment/resource monitoring applications

Details Accordion Closed

Graduate admission information.

The NAU graduate online application is required for all programs. Admission to many graduate programs is on a competitive basis, and programs may have higher standards than those established by the Graduate College. Admission requirements include the following:

• Transcripts.
• Undergraduate degree from a regionally accredited institution with a 3.0 GPA on a 4.0 scale ("A" = 4.0), or the equivalent.

Visit the NAU Graduate Admissions website for additional information about graduate school application deadlines, eligibility for study, and admissions policies. Ready to apply? Begin your application now.

International applicants have additional admission requirements. Please see the International Graduate Admissions Policy .

Additional Admission Requirements

Individual program admission requirements over and above admission to NAU are required.

• Three letters of recommendation
• Personal statement or essay

Master's Requirements

Take the following 30 units:

• GSP 520 , GSP 531 , GSP 535 , GSP 536 , GSP 538 , GSP 539 (24 units)
• Practicum: GSP 689 (6 units)

Students enrolled in this plan may not enroll in or pursue the following due to the number of overlapping units:

• Geographic Information Systems , Graduate Certificate
• Geography , MS

Additional Information

Be aware that some courses may have prerequisites that you must also successfully complete. For prerequisite information, click on the course or see your advisor.

Availability Accordion Closed

What is gis accordion closed.

• Federal and state governments use GIS to manage and plan public land and natural resources.
• Local governments and municipalities use GIS to maintain property data and tax records.
• City planners use GIS to access information, improve communication, and support decision making.
• Environmental agencies use GIS to monitor pollutant discharges and analyze environmental impacts.
• Transportation agencies use GIS to design transportation systems and optimize operations.
• Utility agencies use GIS to manage utility maintenance records and plan services.
• Public health agencies use GIS to monitor epidemic patterns and predict trends.
• Police use GIS to manage emergency dispatching and analyze urban crime patterns.
• Developers use GIS to design sustainable communities and produce maps for permissions.
• Retail businesses use GIS to analyze potential markets and help select new store locations.
• Biologists use GIS to analyze plant disease patterns and develop management strategies.
• Archeologists use GIS to analyze spatial patterns of cultural relics and predict historical sites.

What can I do with the degree? Accordion Closed

• Local government
• Urban and regional planning
• Environmental resource management
• Transportation planning
• Surveying and cartography
• Facilities management
• GIS Data Capture Specialist
• GIS Mapping Technician
• GIS Data Engineer
• GIS Database Administrator
• GIS Front End Developer
• GIS Business Analyst
• GIS Data Analyst
• GIS Manager, GIS Supervisor, GIS Tech Lead, Chief GIS Officer ...

What will I learn in the program? Accordion Closed

• understand and be able to integrate theory and empirical practice of remote sensing involving visible and non-visible forms of electromagnetic radiation using active and passive techniques.
• develop detailed and current knowledge of scientific and applied literature in a remote sensing subdiscipline of their choosing.
• demonstrate mastery at using remote sensing software (ArcGIS Pro, Google Earth Engine) for visualizing and analyzing remotely sensed data.
• apply scripting languages (Python, JavaScript) to automate geoprocessing tasks for remote sensing data analyses.
• complete an advanced remote sensing project that involves obtaining raw imagery, image analysis and visualization, and creation of professional-quality deliverables.
• apply multi-sensor fusion techniques in real-world remote sensing applications.

Why should I choose NAU? Accordion Closed

• We teach the cutting edge and practical GIS technology
• We have a long history of offering GIS courses
• We have a reputed Master in Geography program and GIS certificate program
• We have a strong team of faculty dedicated to the new MS in GIS/Remote Sensing Program
• We are affordable and cost effective

How much will I pay? Accordion Closed

• NAU tuition and expenses
• Graduate funding

How do I apply? Accordion Closed

• NAU graduate admission

Department of Geography, Planning and Recreation

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Remote Sensing and Geoinformatics Master of Science (M.Sc.)

Degree: Master of Science (M.Sc.)

Regular program length: 4 semester (full-time program)

Credit points (ECTS): 120 credit points

Language of instruction: English

Program details

Degree and duration.

Regular program length of 2 years leading to a "Master of Science (M.Sc.)" degree; 120 credit points (corresponding to the European Credit Transfer and Accumulation System - ECTS) must be completed. Individual prorgram length may differ from regular program length.

Program structure

The goal of this MSc program is to convey the ability to independently apply scientific knowledge and methods to evaluate and solve complex scientific and social problems. To this end, a mixture of basic skills and advanced methods and applications make up the program.

The credit points (CP) total is 120. They are distributed over the different courses as follows:

• Remote Sensing 21 CP
• Mathematics and Beyond 17 CP
• Profile Courses 20 CP
• Supplementary Modules 8 CP
• Lab Rotation 20 CP
• Key Competences 4 CP
• Master Thesis 30 CP

Profile courses

Students can choose from six profiles with each a combination of two of the following topic areas:

Computer Vision and Geoinformatics

Computer Vision and Remote Sensing of the Atmosphere

Computer Vision and Environmental Geodesy

Geoinformatics and Remote Sensing of the Atmosphere

Geoinformatics and Environmental Geodesy

Remote Sensing of the Atmosphere and Environmental Geodesy

Qualification profile of the graduate

Graduates of the English-language M.Sc. program "Remote Sensing and Geoinformatics" are qualified for scientific work (e.g. at universities and international research institutions), they can take up qualified employment related to the study program. Furthermore, they can contribute to the solution of civil society questions and continuously develop their own personality.

Students understand current methods and approaches of remote sensing, computer vision and geoinformatics as well as Earth observation. They assess the advantages and disadvantages of different approaches in relation to concrete problems. Furthermore, they select methods in a target-oriented manner and apply them adequately. In addition, they adapt existing methodologies and transfer approaches to new areas of application and research. Students interpret findings obtained from the application of the learned methodology scientifically and socially and correctly classify them. Students coordinate collaborative work and communicate gained knowledge competently.

Career prospects

Graduates of the degree program Remote Sensing and Geoinformatics can work in all areas where geodata is surveyed, collected, analyzed, visualized and interpreted by help of modern information technology and digital media: from automobile industry to development of appliances and electronics industry, software development, construction businesses, engineering offices, public administration and agencies to international air and space organisations. Not only is a direct start in a professional career possible, graduates with excellent accomplishments may also choose to do a doctorate which opens the possibility for a future career in research and teaching.

Characteristic features of the degree program

• future-oriented engineering program (specialization in mathematics and natural science)
• interdisciplinary focus, with a specific connection to computer science and geosciences
• study work in small, well supervised groups
• large percentage of practical experience (exercises, project work)
• research-oriented teaching through active involvement in research and engineering projects
• campus close to the city

Admission requirements

Admission requirements to the master's degree program in Remote Sensing and Geoinformatics are found in the current admission regulations. A rough overview:

• a completed bachelor’s or equivalent degree of at least 3 years duration and based on a minimum of 180 ECTS credit points in the fields of physical-natural sciences, engineering-information technology and especially geodesy or geoinformatics-affine or geoscientific fields
• mathematics, statistics, physics and / or mechanics of 25 credit points
• geoinformatics, image processing, remote sensing, photogrammetry, geosciences, geodesy and / or cartography of 30 credit points
• declaration that you have not lost your right to take any examinations in Remote Sensing and Geoinformatics or in a study program in a related field
• with an Abitur that states they have completed English for at least 5 years up until graduation and with a grade no less than 4
• who have completed their high school or university education in the USA, Canada, Great Britain, Ireland, Australia or New Zealand
• who have completed a degree program at a university in the European Economic Area or Switzerland with English as the sole language of instruction
• a letter of motivation in which the applicant states how the master's program in Remote Sensing and Geoinformatics ties in with their career history and how it will be useful for their future career. The letter must be written in English and no more than 1 DIN A4 page in length.

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Karlsruher Institut für Technologie (KIT) Zentrale Studienberatung (ZSB) Engelbert-Arnold-Str. 2 76131 Karlsruhe

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• Information about exchange programs and studying abroad
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04-15-2024 to 07-27-2024

10-21-2024 to 02-15-2025

04-22-2025 to 08-02-2025

10-27-2025 to 02-21-2026

04-20-2026 to 08-01-2026

10-26-2026 to 02-20-2027

04-19-2027 to 07-31-2027

10-25-2027 to 02-19-2028

04-18-2028 to 07-29-2028

Lectures will not take place:

• From 12-24 to 01-06
• the week after Pentecost
• on all public holidays in the state of Baden-Wuerttemberg

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Deutsches Geodätisches Forschungsinstitut (DGFI-TUM)

TUM School of Engineering and Design

Technische Universität München

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Opportunities for Master's Theses / Masterarbeiten

Currently the following opportunities for Master's Theses are open at DGFI-TUM. We also welcome your own suggestions! In case of interest please do not hesitate to contact us.

All theses can be written in English or German.

Reference Systems

• Simulations of extended SLR space and ground segments for the refined determination of global geodetic parameters
• Precise orbit determination based on xTRF20xx solutions
• Analysis and refined generation of SLR normal points from full-rate data
• Signatures of post-seismic relaxation in station motions of Terrestrial Reference Frames

Satellite Altimetry

• Time-variable river surface slopes from SWOT
• Studying the ocean dynamics of the Agulhas Plateau and its interaction with the Agulhas Current
• Data-driven derivation of wave period from radar altimetry
• Ocean tide modelling in coastal areas: Can we improve tidal predictions by using dedicated geophysical range corrections?
• Wet troposphere path delay corrections for inland altimetry applications

Atmosphere & Space Weather

• Space Weather impact on the thermosphere
• Operational method of the 3D ionosphere reconstruction
• Analysis and filtering of ionospheric and plasmaspheric measurements

Completed Master' and Bachelor' Theses

• Changes in tides from satellite altimetry in the North European Continental Shelf. TUM (M.Sc. ESPACE), Master Thesis
• Impact of refined geophysical models on orbits of altimetry satellites. TUM (M.Sc. ESPACE), Master Thesis
• Effect of coral reefs on wave height and wave energy. TUM (M.Sc. ESPACE), Master Thesis
• Correlation between tidal variations and El Nino Southern Oscillation. TUM (M.Sc. ESPACE), Master Thesis
• Feature extraction for ionospheric Space Weather forecasting with machine learning. TUM (M.Sc. Geodesy & Geoinformation), Master Thesis
• Detecting extreme sea states in satellite altimetry data. TUM (M.Sc. Geodäsie & Geoinformation), Master Thesis
• SLR long-term mean range biases for LEO satellites. TUM (M.Sc. Geodäsie & Geoinformation), Master Thesis
• Transformation of global thermospheric density grids from the NRLMSISE-00 model into a multi-dimensional B-spline representation. TUM (M.Sc. Geodäsie & Geoinformation), Master Thesis
• Estimation of electron density key parameters using the multi-layer Chapman Model considering inequality constraints from ionospheric radio occultation measurements. TUM (M.Sc. Geodäsie & Geoinformation), Master Thesis
• Inland water levels from Sentinel-6: How can SAR altimetry improve the height estimation of rivers and lakes?. TUM (M.Sc. ESPACE), Master Thesis
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MSc thesis topics: Sensing & measuring

MSc thesis topic: Alternative method to derive CLC2024

MSc thesis topic: Assessing patterns of tropical forest disturbances [using the RADD alerts]

MSc thesis topic: Can we detect small temporal differences in spring/fall phenology with high spatial and temporal resolution remote sensing data?

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MSc thesis topic: Combining Sentinel-1 Imagery and Environmental Variables for Deforestation Prediction in Tropical Forests Using Deep Learning

MSc thesis topic: Commodity crops recognition in satellite images using Fourier transform: A new look at signal to frequency domain for detecting commodity crops.

MSc thesis topic: Comparing spaceborne LiDAR data with Holdrige’s forest plots

MSc thesis topic: Deep Learning AI Models for Crop Type Mapping with Sentinel-2

MSc thesis topic: Decoding the optimal time for detecting commodity crops after deforestation.

MSc thesis topic: Detecting reindeer carrion in the Arctic tundra of Svalbard

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Extraction of coal mine surface collapse information and design of comprehensive management model based on multi-source remote sensing—taking zhaogu mining area as example, 1. introduction, 2. materials and methods, 2.1. overview of the study area, 2.2. data sources and preprocessing, 2.3. research methodology, 2.3.1. d-insar technology fundamentals, 2.3.2. spectral-spatial residual network modeling, 2.3.3. improvement of fuzzy comprehensive evaluation model of g1 method, 3.1. analysis of extraction results by d-insar, 3.1.1. verification of extraction accuracy of d-insar technology, 3.1.2. mining subsidence depth extraction results, 3.1.3. mining subsidence depth classification, 3.2. extraction of land use information on collapsed areas, 3.2.1. ssrn extraction accuracy verification, 3.2.2. results of land use information extraction in subsidence area, 3.3. results of the land damage assessment, 3.4. comprehensive management model for collapsed area, 3.4.1. design of comprehensive treatment scheme for subsidence area, 3.4.2. comprehensive management planning for collapsed areas, 4. discussion, 5. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, conflicts of interest.

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Peng, J.; Wang, S.; Wang, Z. Extraction of Coal Mine Surface Collapse Information and Design of Comprehensive Management Model Based on Multi-Source Remote Sensing—Taking Zhaogu Mining Area as Example. Appl. Sci. 2024 , 14 , 6055. https://doi.org/10.3390/app14146055

Peng J, Wang S, Wang Z. Extraction of Coal Mine Surface Collapse Information and Design of Comprehensive Management Model Based on Multi-Source Remote Sensing—Taking Zhaogu Mining Area as Example. Applied Sciences . 2024; 14(14):6055. https://doi.org/10.3390/app14146055

Peng, Jinyan, Shidong Wang, and Zichao Wang. 2024. "Extraction of Coal Mine Surface Collapse Information and Design of Comprehensive Management Model Based on Multi-Source Remote Sensing—Taking Zhaogu Mining Area as Example" Applied Sciences 14, no. 14: 6055. https://doi.org/10.3390/app14146055

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