UCL -- Mapping the different types of forest of the Congo Basin by high resolution satellite remote sensing

Posted-Deadline 04/04/2018 -  20/04/2018
Type Job vacancy
Description The successful applicants will be in charge of the necessary satellite remote sensing developmentand of the production of national forest maps for the 10 countries of the Congo Basin (Central Africa). At the request of the COMIFAC countries, the Observatoire des Forêts d’Afrique Centrale (OFAC) delivers since 2008 on regular basis an internationally recognised report on “The State of the Forests in the Congo Basin”. This report as well as the on-line OFAC information system (http://www.observatoire-comifac.net/) help the COMIFAC countries to manage their forest resources in a more sustainable way.

In the context of the international REDD+ program and for their national forest plan, the COMIFAC countries recently requested detailed and up-to-date maps of the forest extent as well as the delineation of the different types of forests for their respective national territory. With the support of the European Union, a detailed forest typology, advanced remote sensing methods, and a collaborative mapping strategy will be developed by the project team using state-of-theart methods, the most recent technologies including the four Sentinel-1 and 2 satellites and some very high resolution imagery.

In close collaboration with the national experts from each country and the OFAC partners, the mapping activities at 10 m resolution will include experts training, regional workshops, cloud computing and field visits in several countries of the Congo Basin. In addition, on-line data analytics will be further developed to enhance the use of the OFAC website for decision makers. The remote sensing research, the data analytics as well as the map production will rely on the large experience of our lab team in the field of tropical forest remote sensing.

The applicant will be:
  • graduated as bioengineer or equivalent ;
  • trained in remote sensing and geomatics ;
  • fluent in French and English ;
  • motivated to work with international research teams and national experts;
  • ready to actively contribute to training activities in the region.

Additional experiences in tropical forest, advanced image processing and mapping activities are
most welcomed.
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Organisation UCL - Earth and Life Institute
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