In recent years, the availability of new sensing techniques, such as drones, and information sources provided by e.g. the Internet of Things and Big Data initiatives have changed the playing field of remote sensing. Very high resolution observations acquired by drones, airplane observations and also satellite missions open new possibilities for investigations into precision farming, hydrological process (including evapotranspiration and soil moisture mapping), and biodiversity studies.

In this context, new technologies should pave the way for enhancement in these applications.
“Management of water resources is a complex decision-making process (WMO)”. Global changes, such as the unprecedented rise in population, rising standards of living, climate variability and change and environmental issues, are affecting demand and supply for available water”, and have led to a decrease in biodiversity. In order to circumvent these issues there is an growing demand for increasing our knowledge of among others water resources in households, food and industrial production, and the ecosystem. In order to achieve this, new emerging sensing techniques need to be combined with modeling tools to facilitate these issues.

However, traditional modeling tools are not fully designed to estimate at the high resolutions of drones, or the high frequency of IOT devices. Another difficulty emerges from the fact that due to the novelty of such observation systems, no long-term information is available at the respective scales. Thus, Big Data tools capable of combing long-term (coarse resolution) data sets with these novel RS observations, such as data mining, data fusion and data-assimilation of remote sensing observations into hydrological models and monitoring networks, are becoming more important than ever. Such synergistic techniques provide the possibility to improve current hydrologically relevant land surface characterization practices and even create new hydrological products.

This session aims to discuss and exchange on innovative research that integrates high performance remote sensing techniques, products and models in their hydrological processing. As such we invite presentations that focus on:
- New technologies (including satellites/airplanes/drones) that map vegetation traits (leaf chlorophyll, water content) and/or hydrological parameters (soil moisture, precipitation).
High performance modeling using remote sensing information on specific processes (such as plant growth, evapotranspiration)
- Big data and Merging techniques (such as data-assimilation practices)
- Synergistic retrieval of hydrological parameters (soil moisture, evapotranspiration, irrigation, etc) using multiple remote sensing techniques