Agriculture plays a key role in the Earth future, with strong ties to many United Nations Sustainable Development Goals (SDG). Earth observation (EO) is a key for achieving the SDGs and provides support to agricultural practices in several ways. It serves farmers, supporting precision farming of crops by monitoring phenology, plant health, water requirements, by predicting yield, detecting pest infections, mapping and quantifying natural hazards-related damages etc. It serves public administrations supporting controls (e.g EU CAP) and giving at-the-landscape level comprehensive overviews of ongoing agriculture-related phenomena like carbon sequestration, habitat quality and landscape degradation/planning/amelioration. Monitoring agricultural systems at different spatial and temporal scales is proving to give insights on positive and negative effects of agriculture management and to support near real time decisions from farmers along the entire crop growing season. In this framework, given the steadily increasing number of (i) Earth Observation platforms (satellite, aerial and drones), (ii) products/services (from various public and private players) and (iii) new algorithmic approaches to data processing (AI included) the research and academic communities are called invited to actively support a proper technology transfer. This workshop is specifically intended to bring together researchers, industry, data users and stakeholders using Earth Observation for agricultural applications to make a proper synthesis of all the involved key issues, longing for a focused SWOT analysis able to draft the guidelines and the requirements of a proper future scenario of EO science application. In this third edition of the EARSeL SIG Workshop on Remote Sensing for Agriculture we welcome contributions that address a broad range of challenges:
List of topics
- EO-based Services and Products for Agriculture
- support for risk modeling and management in agriculture
- evaluation of direct and indirect economic benefits of EO products and services in agriculture
- EO data integration with other services (e.g. agro-meteo networks, phenological networks etc…)
- mapping yield for crop monitoring and optimization
- mitigation of environmental impact in farming activities (e.g. monitoring gas emissions, reduction of impact from treatments, optimization of water usage etc….)
- damage assessment for multiple purposes – insurance, economic loss estimation, etc…
- definition of quality assurance/quality control (QA/QC) products specific for agricultural applications
- Regional/Continental/Global Applications of EO in Agriculture
- mapping and monitoring biodiversity in agricultural landscapes
- monitoring crop management practices (e.g. land use intensity, growing strategies s) in the context of climate change adaptation and mitigation
- advantages and pitfalls of deep/machine learning and AI-based approaches
- spatial and temporal capability of generalization of EO-based models, wide area mapping / historical land use mapping
- supporting Common Agricultural Policies (CAP)
- products and Services Officiality in the CAP framework
Scientific Committee of the Workshop
Marcel Schwieder, marcel.schwieder@thuenen.de, Thünen-Institut, GER
Patrick Hostert, patrick.hostert@geo.hu-berlin.de, Humboldt-Universität zu Berlin, GER
Enrico Corrado Borgogno Mondino, enrico.borgogno@unito.it, Università di Torino, IT
Francesco Pirotti, francesco.pirotti@unipd.it, Università degli Studi di Padova, IT
Mirco Boschetti, boschetti.m@irea.cnr.it, CNR-IREA, IT
Dr. Gohar Ghazaryan, Gohar.Ghazaryan@zalf.de, Leibniz Centre for Agricultural Landscape Research (ZALF), GER
Organizers
Prof. Enrico Corrado Borgogno Mondino
Università di Torino, IT
enrico.borgogno@unito.it
Dr. Mirco Boschetti
CNR-IREA, IT
boschetti.m@irea.cnr.it
Marcel Schwieder
Thünen-Institut, GER
marcel.schwieder@thuenen.de
Dr. Gohar Ghazaryan
Leibniz Centre for Agricultural Landscape Research (ZALF), GER
Gohar.Ghazaryan@zalf.de