Remote Sensing for mapping and assessing the impact of invasive alien species

Scope and topics

Invasive alien plants (IAP) establish and spread when introduced to a new
region by increasing their distribution and spread without direct human
intervention. Invasive alien species are currently 1 of the 5 drivers of
biodiversity loss, counting to an estimated 12 billion euros loss per year in
Europe and Worldwide. The European Strategy for Biodiversity 2030 calls for a
50% reduction in the number of Red List species (regulation 1143/2014,
European Union (EU) – list of IAP of EU concern) and highlights the need for
active monitoring. Hence, member countries need more support in monitoring
and in evaluating past and future trends of key IAP.
Remote sensing systems have long been used to map IAP. Using different
satellite systems, covering larger areas and with decreased resolution, through
airborne hyperspectral data to unmanned aerial vehicle covering local areas
with high resolution data. New data and algorithms encourage optimizations of
existing methods, especially since IAP create heterogeneous spectral
compositions. However, there is little information about most of the AIP
spread in European countries, where there is no data focusing on the issue
from, for example, the Copernicus programme. Hence, more work is needed
with regards to satellite remote sensing of AIP. On a more local scale, the
multispectral UAV systems are starting be an established system within
researchers.
The public availability of decameter resolution satellite data and the
accessibility to MS UAV systems open the possibility for a spatially and
temporally continous monitoring of AIP. In parallel, the environmental impact
of such AIP spread can also take advantage of remote sensing to assess such
impact from local to transnational studies.

List of topics:

  • New Image processing algorithms and classification methods.
  • Detection of invasive alien plants (AIP) from remote sensing systems:
  • Geographical and temporal transferability of AIP detection algorithms.
  • Multi-, hyperspectral separation of AIP from other vegetation coversconsidering different landscapes, ecosystems and seasons.
  • Combination of ancillary datasets to generate reference data.
  • AIP and big data and cloud computing.
  • AIP digital twins.
  • Environmental impacts of IAP spread combining remote sensing, field
  • surveys and other sets of ancillary datasets.
  • Assessing biocontrol agents with remote sensing.

Organizers

Diogo Duarte – NESC Coimbra, University of Coimbra – diogovad@inescc.pt


Bogdan Zagajewski
– University of Warsaw – bogdan@uw.edu.pl