Skip to main content

PhD Position Historical Changes of Antarctic Glaciers from Photogrammetry TU Delft






PhD Position Historical Changes of Antarctic Glaciers from Photogrammetry TU Delft


Job description
The Antarctic Peninsula is one of the fastest changing regions on our planet, and experienced a warming unparalleled anywhere else in the Southern Hemisphere in the late-20th century. Several ice shelves along its margins have retreated or disintegrated, leading to rapid changes of the glaciers on its mainland. Due to its relatively small scale and complex topography, a detailed picture of the mass balance of the region was missing until the recent advent of high-resolution satellite observations. While these data revealed that the Peninsula is losing ice rapidly, a long-term perspective of the changes is still lacking.
In this project, you will unlock the potential of a vast archive of aerial photographs, obtained by the U.S. Navy since the 1940s, along ten thousands of kilometers spanning the Antarctic continent. Using the overlap between consecutive acquisitions in a Structure from Motion photogrammetry approach - combined with recent developments in high performance computing and image pattern recognition - you will derive digital elevation models of the Antarctic Peninsula, dating back more than five decades. These models will be compared to present-day elevation data, for example from satellite photogrammetry and LiDAR altimetry (ICESat-2), to obtain a detailed picture of elevation and mass changes over the past 50 years. Furthermore, regional climate models will be used to put the observed changes in a broader climatological perspective.
Your work will provide a unique insight into the long-term impact of changing climate conditions on Antarctica's glaciers, and their dynamical response to ice shelf weakening and disintegration. Your results will provide essential validation data for ice modelling efforts, thereby contributing to reducing the uncertainties in future sea level rise scenarios.
We aim to start the project early 20201, but no later than March, 1, 2021. During the project you will be supervised by Bert Wouters and Roderik Lindenbergh at TU Delft and you will collaborate with researchers at Utrecht University and in Norway, France and USA. If the situation allows, your project will include a research visit to one of our international collaborators.
Department
The position is located within the department of Geoscience and Remote Sensing (GRS). We seek to advance the understanding of dynamic processes on—and human interaction with—Earth, with a focus on atmospheric sciences and geodesy. The approach is based on the development of observation technology as well as the modelling of processes. Our ambition is to create an interdisciplinary research environment in which scientific staff and students explore, learn, and teach. GRS (with about 110 staff members of which 25 faculty staff) conducts a research programme in the disciplines of geodesy, remote sensing, data science, earth-oriented space research, and climate and atmospheric sciences. It focuses on the interrelation between new observational techniques and applications in engineering and geosciences, including the development of space-borne, airborne, and ground-based methods and models. The department has an internationally leading role in research related to 2D and 3D surveying, geodesy, satellite remote sensing, natural hazards, geodynamics and climate studies. Please check the website here.
Requirements
need-to-haves:
MSc in Geodesy, Photogrammetry, Aerospace Engineering, Computer Vision or related fields;
Strong programming skills;
Experience in development of data processing algorithms;
Good reporting and presentation skills;
Excellent level of written and spoken English (for non-native English speakers: TOEFL-score > 100 or IELTS > 7);
Ability to work independently and to critically assess own results;
nice-to-haves:
Affinity with photogrammetry and/or remote sensing of ice sheets and glaciers;
A solid backgroud and interest in glaciology
Experience in machine learning, image pattern recognition and handling large data sets and parallel computing, high performance computing or cloud computing;
Conditions of employment
TU Delft offers PhD-candidates a 4-year contract, with an official go/no go progress assessment after one year. Salary and benefits are in accordance with the Collective Labour Agreement for Dutch Universities, increasing from € 2395 per month in the first year to € 3061 in the fourth year. As a PhD candidate you will be enrolled in the TU Delft Graduate School. The TU Delft Graduate School provides an inspiring research environment with an excellent team of supervisors, academic staff and a mentor. The Doctoral Education Programme is aimed at developing your transferable, discipline-related and research skills.
The TU Delft offers a customisable compensation package, discounts on health insurance and sport memberships, and a monthly work costs contribution. Flexible work schedules can be arranged. For international applicants we offer the Coming to Delft Service and Partner Career Advice to assist you with your relocation.
TU Delft (Delft University of Technology)
Delft University of Technology is built on strong foundations. As creators of the world-famous Dutch waterworks and pioneers in biotech, TU Delft is a top international university combining science, engineering and design. It delivers world class results in education, research and innovation to address challenges in the areas of energy, climate, mobility, health and digital society. For generations, our engineers have proven to be entrepreneurial problem-solvers, both in business and in a social context. At TU Delft we embrace diversity and aim to be as inclusive as possible (see our Code of Conduct). Together, we imagine, invent and create solutions using technology to have a positive impact on a global scale.
Challenge. Change. Impact!
Faculty Civil Engineering & Geosciences
The Faculty of Civil Engineering & Geosciences (CEG) is committed to outstanding international research and education in the field of civil engineering, applied earth sciences, traffic and transport, water technology, and delta technology. Our research feeds into our educational programmes and covers societal challenges such as climate change, energy transition, resource depletion, urbanisation and the availability of clean water, conducted in close cooperation with a wide range of research institutions. CEG is convinced that Open Science helps to achieve our goals and supports its scientists in integrating Open Science in their research practice. The Faculty of CEG comprises 28 research groups in the following seven departments: Materials Mechanics Management & Design, Engineering Structures, Geoscience and Engineering, Geoscience and Remote Sensing, Transport & Planning, Hydraulic Engineering and Water Management.
Click here to go to the website of the Faculty of Civil Engineering & Geosciences.
Additional information
For more information about this vacancy, please contact Dr.ir. Bert Wouters, Assistant Professor and PI for this project, email: bert.wouters@tudelft.nl.
Application procedure
To apply, please e-mail a single pdf file named 'TUD00509_YourLastName.pdf' with your:
letter of motivation
detailed CV
list of grades/transcripts
contact information of 2 references
The abstract of your master thesis
Please compile all this information into a single pdf file named 'TUD00509_YourLastName.pdf' by November 15, 2020 to Dr. Bert Wouters via recruitment-citg@tudelft.nl. Please note that applications will not be processed if all documents required are not compiled into a single pdf document
The position remains open until filled. Your application will be given full consideration if you apply before November 15, 2020.
A pre-employment screening can be part of the application procedure.







Vineesh V
Assistant Professor of Geography,
Directorate of Education,
Government of Kerala.
https://www.facebook.com/Applied.Geography
http://geogisgeo.blogspot.com

Comments

Popular posts from this blog

Geometric Correction

When satellite or aerial images are captured, they often contain distortions (errors in shape, scale, or position) caused by many factors — like Earth's curvature, satellite motion, terrain height (relief), or the Earth's rotation . These distortions make the image not properly aligned with real-world coordinates (latitude and longitude). 👉 Geometric correction is the process of removing these distortions so that every pixel in the image correctly represents its location on the Earth's surface. After geometric correction, the image becomes geographically referenced and can be used with maps and GIS data. Types  1. Systematic Correction Systematic errors are predictable and can be modeled mathematically. They occur due to the geometry and movement of the satellite sensor or the Earth. Common systematic distortions: Scan skew – due to the motion of the sensor as it scans the Earth. Mirror velocity variation – scanning mirror moves at a va...

RADIOMETRIC CORRECTION

  Radiometric correction is the process of removing sensor and environmental errors from satellite images so that the measured brightness values (Digital Numbers or DNs) truly represent the Earth's surface reflectance or radiance. In other words, it corrects for sensor defects, illumination differences, and atmospheric effects. 1. Detector Response Calibration Satellite sensors use multiple detectors to scan the Earth's surface. Sometimes, each detector responds slightly differently, causing distortions in the image. Calibration adjusts all detectors to respond uniformly. This includes: (a) De-Striping Problem: Sometimes images show light and dark vertical or horizontal stripes (banding). Caused by one or more detectors drifting away from their normal calibration — they record higher or lower values than others. Common in early Landsat MSS data. Effect: Every few lines (e.g., every 6th line) appear consistently brighter or darker. Soluti...

Atmospheric Correction

It is the process of removing the influence of the atmosphere from remotely sensed images so that the data accurately represent the true reflectance of Earth's surface . When a satellite sensor captures an image, the radiation reaching the sensor is affected by gases, water vapor, aerosols, and dust in the atmosphere. These factors scatter and absorb light, changing the brightness and color of the features seen in the image. Although these atmospheric effects are part of the recorded signal, they can distort surface reflectance values , especially when images are compared across different dates or sensors . Therefore, corrections are necessary to make data consistent and physically meaningful. 🔹 Why Do We Need Atmospheric Correction? To retrieve true surface reflectance – It separates the surface signal from atmospheric influence. To ensure comparability – Enables comparing images from different times, seasons, or sensors. To improve visual quality – Remo...

Supervised Classification

In the context of Remote Sensing (RS) and Digital Image Processing (DIP) , supervised classification is the process where an analyst defines "training sites" (Areas of Interest or ROIs) representing known land cover classes (e.g., Water, Forest, Urban). The computer then uses these training samples to teach an algorithm how to classify the rest of the image pixels. The algorithms used to classify these pixels are generally divided into two broad categories: Parametric and Nonparametric decision rules. Parametric Decision Rules These algorithms assume that the pixel values in the training data follow a specific statistical distribution—almost always the Gaussian (Normal) distribution (the "Bell Curve"). Key Concept: They model the data using statistical parameters: the Mean vector ( $\mu$ ) and the Covariance matrix ( $\Sigma$ ) . Analogy: Imagine trying to fit a smooth hill over your data points. If a new point lands high up on the hill, it belongs to that cl...

Pre During and Post Disaster

Disaster management is a structured approach aimed at reducing risks, responding effectively, and ensuring a swift recovery from disasters. It consists of three main phases: Pre-Disaster (Mitigation & Preparedness), During Disaster (Response), and Post-Disaster (Recovery). These phases involve various strategies, policies, and actions to protect lives, property, and the environment. Below is a breakdown of each phase with key concepts, terminologies, and examples. 1. Pre-Disaster Phase (Mitigation and Preparedness) Mitigation: This phase focuses on reducing the severity of a disaster by minimizing risks and vulnerabilities. It involves structural and non-structural measures. Hazard Identification: Recognizing potential natural and human-made hazards (e.g., earthquakes, floods, industrial accidents). Risk Assessment: Evaluating the probability and consequences of disasters using GIS, remote sensing, and historical data. Vulnerability Analysis: Identifying areas and p...