Postdoc of Dynamic Forest Carbon Mapping from High Resolution Satellite Data

The Department of geosciences and natural resource management offers a two-year Postdoctoral position in the field of Remote Sensing of forest resources, with a specific focus on tree cover in European countries using very high resolution satellite imagery and novel machine learning techniques.

Carbon in forests is very important to mitigate climate change and to supply wood resources worldwide. Yet, forest carbon stocks are spatially highly heterogeneous across forest types, and are strongly impacted by trees demography, management, and natural disturbances such as fires, insect outbreaks and droughts causing mortality. Currently no suitable tool exists for a rapid assessment of forest carbon change down to tree level, to better understand regrowth and mortality. Such a tool is crucial to inform smart management of carbon sequestration from a myriad of projects with highly diverse forestry practices. New very-high-resolution satellites open a window to track carbon sequestration or losses at a detailed spatial scale. Near-daily coverage of images from PlanetScope allows for the first time to take the pulse of carbon in forests in almost near real time. Other imagers offer an even higher spatial resolution.

The aim of the Postdoctoral position is to develop ground-breaking methods to quantify forest resources and changes using very high resolution satellite imagery and artificial intelligence. High spatial and temporal resolution PlanetScope satellite data will be used to produce annual forest and carbon stock maps for selected regions in Europe. These data will be combined with plot-scale data from inventories and other satellite information such as forest height measurements using space-borne Lidars. A science breakthrough is expected on forest carbon dynamics and remote sensing image analysis to provide the first very high-resolution maps of forest carbon in several European countries, including tree density, species types and carbon change rates.

The position will be an integral part of a 2 year project (C-TREES) financed by H2020 Eurostar programme promoting international collaboration to support research-performing small and medium enterprises, which develop innovative products, processes and services, to gain competitive advantage. The C-TREES project, and the position will be a close collaboration between IGN and two French partners The Laboratoire des Sciences du Climat et de l’Environnement (LSCE) and Kayrros (a Paris based EO startup). A complementary position to this Postdoc will be announced by our French partners and the tw post docs are expected to work closely together.

Eligible candidates:

• The applicants should hold a PhD degree in remote sensing, geoinformatics, computer vision, AI or related fields.
• Candidates with a solid understanding of satellite images, spatial analyses, machine learning and deep learning. Candidates with knowledge on remote sensing of forestry is considered an advantage.
• Candidates with strong programming skills (preferably Python) as well as having proven experience with handling, processing and analyzing large image datasets.
• Experienced in multidisciplinary team-based activities with the ability to effectively communicate with colleagues and with staff from the partners of a project. Prior experience with SME (small and medium-sized enterprises) work is considered an advantage.
• Proficiency in spoken/written English, including skills in academic writing and publishing in peer-reviewed journals are essential. It is considered an advantage if candidates have proven records of innovative remote sensing-based work.

Work environment

Your work place will be the Department of Geosciences and Natural Resource Management (IGN), which conducts research and education on the past, present and future physical, chemical and biological environments of the Earth and their interactions with societal and human systems to provide graduates and research in support of sustainable future solutions for society. The department has strong experience in interdisciplinary collaboration within and beyond the department.

Further information on the Department can be found at https://ign.ku.dk/english/.

Inquiries about the position can be made to Professor Rasmus Fensholt (e-mail: rf@ign.ku.dk) or Assistant Professor Martin Brandt (mabr@ign.ku.dk).

The position is open from 1 April 2021 or as soon as possible thereafter.

The University wishes our staff to reflect the diversity of society and thus welcomes applications from all qualified candidates regardless of personal background.

Terms of employment

The position is covered by the Memorandum on Job Structure for Academic Staff.

Terms of appointment and payment accord to the agreement between the Ministry of Finance and The Danish Confederation of Professional Associations on Academics in the State.

The starting salary is currently up to DKK 436.730 including annual supplement (+ pension up to DKK 74.681). Negotiation for salary supplement is possible.

The application, in English, must be submitted electronically by clicking APPLY NOW below.

Please include

• Curriculum vitae
• Diplomas (Master and PhD degree or equivalent)
• Research plan – description of current and future research plans
• Complete publication list
• Separate reprints of 3 particularly relevant papers

The deadline for applications is 14 March 2021, 23:59 GMT +1

After the expiry of the deadline for applications, the authorized recruitment manager selects applicants for assessment on the advice of the Interview Committee.

You can read about the recruitment process at http://employment.ku.dk/faculty/recruitment-process/.

Part of the International Alliance of Research Universities (IARU), and among Europe’s top-ranking universities, the University of Copenhagen promotes research and teaching of the highest international standard. Rich in tradition and modern in outlook, the University gives students and staff the opportunity to cultivate their talent in an ambitious and informal environment. An effective organisation – with good working conditions and a collaborative work culture – creates the ideal framework for a successful academic career.