● Internship agreement (tripartite convention)
● Location: Brussels, open to remote work (Europe)
● Schedule: to be agreed upon availability of the candidate
● Duration: 2 months between March and June
● Starting date: as soon as possible
CONTEXT
WeForest is an international non-profit association headquartered in Belgium with the mission to conserve
and restore the ecological integrity of forests and landscapes, engaging communities to implement and deliver
lasting solutions for climate, nature and people. We promote science and best practices in a culture of sharing
and inclusion, so that others can replicate and augment what we do.
As an integral part of a large mangrove restoration project, over 7000ha of drone imagery was captured and
analysed on the West Coast in Senegal. This imagery will be used for identifying saplings to understand their
survival rates across the project areas. This data feeds into WeForest carbon projects. Hence, accuracy is
crucial and we require support to quality control and assure the imagery and its derived products. As the
imagery was taken in remote areas GPS coverage is variable and as a result the automated georectification
process as well. The candidate will support the project by quantifying the overall geolocation error and identify
large outliers to correct these ones using open-source tools such as QGIS and Very-High-Resolution imagery
available via Google Earth and others.
OBJECTIVE
The objective of this assignment is two-fold:
- Quantify geolocation error of drone images taken over mangrove sites;
- Select and correct images with errors greater 5-10m by georectification tools in QGIS;
DELIVERABLES
● Technical report on georeferencing accuracy and error statistics;
● Corrected and georeferenced drone imagery in GeoTIFF format;
● Vector dataset of Ground Control Points (GCPs).
REQUIRED SKILLS & QUALIFICATIONS
Currently enrolled in a postgraduate program in a relevant field (science, engineering, environmental
studies, geospatial sciences, or equivalent), or holding a professional certification in geography, GIS,
or remote sensing;
● Strong skills in Geographic Information Systems (GIS);
● Experience with remote sensing data processing and forest or landscape monitoring applications;
● Familiarity with qualitative research methods (e.g., documentation, interpretation of spatial data
quality, reporting findings);
● Excellent written and verbal communication skills in English;
● Strong analytical mindset, attention to detail, and willingness to learn.
