PhD Position Mapping and classifying landslides by exploiting EO Big Data
Mapping and classifying landslides by exploiting EO Big Data
The Chair of Engineering Geology at ETH Zurich invites applications for a PhD position in the area of slope stability analysis. The successful candidate must have a MSc in Earth Sciences, Environmental Engineering or related field and be strongly interested in research. Knowledge and experience in remote sensing and machine learning algorithms are of prime importance. Good technical and writing skills are desired. The duration of the position is about 3-4 years.
The position is funded for 3 years by the EU-H2020 project “BETTER”. The main objective of BETTER is to implement an Earth Observation (EO) Big Data intermediate service layer devoted to harnessing the potential of the Copernicus and Sentinel European EO data directly from the needs of the users. BETTER developments will be driven by a large number of Big Data challenges to be set forward by the users deeply involved in addressing the key societal challenges. ETH Zurich is responsible for the Big Data challenges related to GeoHazards, and the PhD student will be directly involved in these activities, in particular for the analysis of slope instability processes.
High topography, steep slopes, as well as geological and geomorphological conditions are primary predisposing factors for slope instabilities. One of the open issues in landslide research is the generation of reliable inventory maps and the detection of hazardous slope instabilities. These tasks are in most cases addressed with visual and subjective interpretation of EO imagery performed by experienced operators. This action is time consuming and produces a final inventory and slope classification, which might be biased by subjective interpretation and lead to heterogeneous results. The aim of the PhD project is to challenge new techniques to generate inventory and hazard maps of large landslides with automatic methods by exploiting multiple sources of EO data available, including SAR data (e.g. ERS-1/2, Envisat ASAR, Sentinel-1), optical imagery (e.g. Landsat, Sentinel-2), and DEMs (SRTM, Aster). Available catalogues of landslide phenomena will be considered to train machine learning algorithms, which will be then used to generate landslide inventory and hazard maps by relying on supervised and unsupervised classification schemes.
The Engineering Geology group consists of approximately 25 multidisciplinary scientists involved in a leading research and teaching program in quantitative engineering geology and hydrogeology. Detailed information about the Earth Science Department and the Chair of Engineering Geology is available on the web at www.engineering-geology.ethz.ch.
For further information regarding the advertised position please contact Prof. Simon Löw, Engineering Geology, ETH Zurich (e-mail: email@example.com) or Dr. Andrea Manconi, Engineering Geology, ETH Zurich (e-mail: firstname.lastname@example.org). Complete applications should be sent until August 15th by regular mail or e-mail to Dr. Andrea Manconi, Engineering Geology, ETH Zürich, Sonneggstrasse 5, 8092 Zürich, Switzerland, and must include the following: 1) Cover letter; 2) Curriculum vitae which describes your complete personal details and career history; 3) Complete course grades and transcripts; 4) Digital copies of both BSc and MSc theses.