Topics

EARSeL is a scientific network of European remote sensing laboratories, coming from both academia and the commercial/industrial sector, which covers all fields of geoinformation and earth observation through remote sensing. All persons involved or interested in the field of the remote sensing and geoinformatics are strongly encouraged to present contributions according to the following topics:

  • Applications of remote sensing,
  • Forestry and forest fires,
  • Land use and land cover, degradation and desertification,
  • Urban Remote Sensing,
  • Developing countries: mapping, monitoring and change analysis,
  • 3D remote sensing,
  • New instruments and methods, including ground truth,
  • Unmanned Aircraft Systems (UAS) from theory to application,
  • Novel techniques of image processing, classification and change detection,
  • Thematic sessions proposed by EARSeL members:

Augmented and Virtual Realitychairs: Claudia Lindner, e-mail: Claudia.Lindner(at)ruhr-uni-bochum.de; Andreas Rienow, e-mail: andreas.rienow@ruhr-uni-bochum.de
Augmented and virtual reality applications using Earth Observation data and their products. This includes applications for research, commerce, education, and public outreach. Discussion of advantages, limitations, chances, and drawbacks.

Citizen Science – new challenges and opportunitieschairs: Marta Samulowska, e-mail: m.samulowska(at)uw.edu.pl; Anca Dabija, e-mail: anca.dabija(at)uw.edu.pl
The citizens engaged in scientific research projects become citizen scientists, who, in contrast with typical respondents, are interested in the whole research process and expect to see the results of their research contribution effects. Depending on the level of citizen engagement, they contribute to the project by collecting and analyzing data, but can also be involved in defining research questions or even interpreting results. CS provides a solution to research problems and also educates citizens.
The goal of the session is an integration of persons who are interested in the development of the CS research methods; crowdsourcing, quality assurance system building and implementations. All participants of CS projects are cordially invited to share experiences and to promote outcomes.

Earth Observation Proxies to Predict Urban Deprivation, Socio-Economic and Environmental Inequalitieschair: Monika Kuffer, e-mail: m.kuffer(at)utwente.nl
Recent rapid urbanization, in particular, in low- and middle-income countries (LMICs) has both boosted economic growth, as well as proliferated inequalities in access to basic infrastructure, access to essential services, and environmental conditions having severe impacts on living conditions and health outcomes. UN-Habitat estimates that a billion people currently live in slums, informal settlements, and inadequate housing, and this number is expected to double by 2050. Three significant knowledge gaps undermine the efforts to monitor progress towards the corresponding Sustainable Development Goal (SDG 11 — Sustainable Cities and Communities). First, the data available about deprivation in cities worldwide is patchy and insufficient to analyse socio-economic and environmental conditions. Second, existing approaches to deprivation mapping are mostly siloed, and lack transferability or scalability. Third, ethic and privacy standards are not well developed to guide the publishing of data on the geography and attribute information of deprived areas (e.g., socio-economic characteristics). The thematic session will allow researchers to exchange on state-of-the-art EO methods to analyse variations in socio-economic and environmental conditions and health outcomes, with the aim to understanding multiple deprivations (e.g., degree of pollution, environmental risk, informality, and health outcomes) to enable targeting of programmes and policies. As technologies, available data, and computing power rapidly evolve, new opportunities are emerging to co-create and integrate data. We must ensure that these approaches are inclusive, result in benefits to all stakeholders, and that we have mitigated unintended consequences, such as locating already vulnerable populations.

EO Education chairs: Agata Hościło, e-mail: Agata.Hoscilo(at)igik.edu.pl; Andreas Rienow, andreas.rienow(at)ruhr-uni-bochum.de
Increasing number of Earth Observation (EO) and in-situ data sources, requires evermore new skills and knowledge for data collection, processing and analysis. Technological changes driven by big Earth data induce a paradigm shift in learning and knowledge transfer which need to be considered for the creation of future EO curricula and training actions at different educational levels.
This thematic session will inform about current EO educational activities in Europe, e.g. EO4GEO an Erasmus+ Sector Skills Alliance, EO College, Remote Sensing in Schools FIS, and will stimulate discussion on its future needs. 
Within this session a GeoInformation and Earth Observation EO4GEO Body of Knowledge for the purpose of curriculum and job profiles development will be presented and discussed including hands-on activities.

Remote sensing for Natura 2000 habitats monitoring – chairs: Łukasz Sławik, e-mail: lslawik(at)mggpaero.com; Dominik Kopeć, e-mail: dkopec(at)mggpaero.com
The aim of the session is to exchange experiences in using remote sensing to monitoring Natura 2000 habitats. Especially valuable will be all presentations which describe experiences of people using different datasets and methods of analysis.

Remote Sensing for Precision Farmingchair: Katarzyna Dabrowska-Zielinska, e-mail: katarzyna.dabrowska-zielinska(at)igik.edu.pl
The Session will consist of various aspects of precision  farming for the Decision System  at the farm level applying the information from satellites, drones, gyrocopters and aerial pictures.
The early prediction of drought gives possibilities for proper agriculture management, what is crucial for obtaining better crop yield. The recognition of pests, needs for irrigation  give information for decisions how to improve the farm management. Information using remote sensing data  in visible, infrared and microwave  supports modern agriculture.