PRR Project

Summary

Tasks:The Researcher will be required to develop remote sensing-based research, in some of the diverse areas of CEF and TERRA where the technology has been applied, namely burned area mapping, fuel mapping, and fire danger assessment; forest inventory; monitoring productivity and health status of forests and woodlands; characterization of structure and species composition of riparian vegetation; land cover and land cover change mapping. With the forthcoming acquisition of an unmanned aerial vehicle (UAV) and respective sensors, the Researcher will be tasked with taking a leading role in using and promoting the use of this equipment at CEF, ISA, and in collaboration with the TERRA Associate Laboratory’s broader research community. The Researcher will be required to collaborate in teaching remote sensing courses, namely Remote Sensing and Image Analysis , and Vegetation Monitoring with UAV and LiDaR . This will include the development and supervision of new practical exercises for field data acquisition and analysis, exploring the exceptional opportunities afforded by the 90 ha Tapada da Ajuda campus and Living Lab, integrated in the European Network of Living Labs. The Researcher shall also undertake responsibility for the creation and curation of remotely sensed datasets, following the principles of Findability, Accessibility, Interoperability, and Reusability (FAIR) data management. The Researcher will collaborate in supervising the use of all remote sensing equipment, including specialized computer hardware and software, UAV and UAV-based optical multispectral and LiDaR sensors, and terrestrial LiDaR, to be acquired. The Researcher will be asked to participate in the development and teaching of short courses on satellite-based remote sensing, UAV-based remote sensing, and terrestrial LiDaR applied to vegetation monitoring. The courses may include domains of interest for the TERRA Associate Lab partner research units, such as precision agriculture, landscape architecture, ecology and land use planning.Scientific profile:The Researcher will need to have demonstrated competence in remote sensing science and data analysis, including formal academic training, publications in peer-reviewed journals, and participation in relevant research projects. The Researcher will be required to have competence in optical and LiDaR remote sensing, with preference given to those who are also skilled with remote sensing in the thermal domain. The substantive domain of expertise of the Researcher in the application of remote sensing should be the analysis and monitoring of vegetation quantity, structure, condition and dynamics, namely for forests, woodlands, shrublands, and riparian vegetation. The tasks to be developed by the Researcher will require good data analytic skills, including proficiency in statistical and machine learning techniques, image processing, and change detection. The Researcher will also need good programming skills in languages such as Python and R, as well as proficiency with the Google Earth Engine (GEE).Rationale for hiring this profile:There is a fast expanding demand for the use of remotely sensed data over a variety of applied research areas at CEF and also within the TERRA Associate Lab community. While the use of remote sensing at CEF started in the early 1990s in research related to fire monitoring and fuel mapping, the domain of application gradually expanded to other topics, such as land cover mapping, monitoring tropical deforestation and regeneration, and mapping riparian vegetation. Subsequent technological progress, namely in unmanned aerial vehicles (UAV) as platforms for the acquisition of data at very high spatial resolution, and in LiDaR scanners, which allow for detailed characterization of the 3-dimensional structure of vegetation, further increased the demand for remotely sensed data. Starting in the mid-2010s, CEF researchers have been deploying such technologies to new topics such as forest inventorying, assessment of vegetation C stocks, and forest pest monitoring. Thus, CEF needs to strengthen its capability to respond this trend and increase our competitiveness with the recruitment of a talented young Researcher, also capable of collaborating in the new M.Sc.-level course on Vegetation Monitoring with UAV and LiDaR . CEF has elected Focal Themes for its next funding cycle (Fire, People, and Landscape; Oak Woodlands and Cork; Sustainable Use of Tropical Land), all of which have previously relied on remotely-sensed data and will greatly benefit from additional R&D capacity at the Centre. Last, but not least, the CEF member responsible for the course on Remote Sensing and Image Analysis will retire during the next funding cycle (2025-29), opening a possibility for progression in the career for the Researcher to be hired.