Session Outline
| Atmospheric and Hydrospheric Sciences (A) | ||||
|---|---|---|---|---|
| Session Sub-category | Technology &Techniques (TT) | |||
| Session ID | A-TT50 | |||
| Title | Soil and Water Monitoring through Innovative Sensing Technologies under Climate Change | |||
| Short Title | Soil Water Monitoring | |||
| Main Convener | Name | Wendi Wang | ||
| Affiliation | Department of Land, Environment, Agriculture and Forestry, University of Padova, | |||
| Co-Convener 1 | Name | Eugenio Straffelini | ||
| Affiliation | Department of Land, Environment, Agriculture and Forestry, University of Padova, 35020 Legnaro, PD, Italy | |||
| Co-Convener 2 | Name | Fangxin Chen | ||
| Affiliation | ||||
| Co-Convener 3 | Name | Sara Cucchiaro | ||
| Affiliation | University of Udine, Department of Agricultural, Food, Environmental and Animal Sciences | |||
| Co-Convener 4 | Name | Manel Llena | ||
| Affiliation | University of Lleida | |||
| Co-Convener 5 | Name | Paolo Tarolli | ||
| Affiliation | University of Padova | |||
| Session Language | E | |||
| Scope |
Climate extremes and unsustainable land use are disrupting soil and water systems, accelerating degradation, and threatening food and water security, addressing these issues requires continuous monitoring and integration of multi scale data, advances in sensing technologies, artificial intelligence AI, and data analytics offer new ways to observe Earth surface processes, improve predictions, and understand soil water interactions.
This session invites studies developing or applying innovative sensing and monitoring approaches for soil and soil water dynamics across spatial and temporal scales, contributions using in situ sensors, UAVs, airborne platforms, or satellite data are welcome, as well as studies integrating multiple geospatial datasets such as LiDAR, photogrammetry, and remote sensing for modelling and scenario analysis under changing environmental conditions.
Topics include but not limited :
Proximal and remote sensing for soil and water monitoring
Multi source data fusion and integration
AI and machine learning in soil water studies
Linking sensing data with models
Decision support tools based on sensing and modelling.
Interdisciplinary and early career contributions are encouraged.
|
|||
| Session Format | Orals and Posters session | |||