Remote sensing technology continues to play a significant role in the understanding of our environment. It has evolved into an integral research tool for the natural sciences. Disciplines such as climatology, hydrology, and studies of the terrestrial biosphere have all developed a strong remote sensing analysis component. Moreover, remote sensing has facilitated our understanding of the environment and its many processes over a broad range of spatial and temporal scales. This is a highly important aspect of land surface research, especially in the management of land and water resources and for the detection of environmental change. 

Remote sensing applications have greatly enhanced our ability to monitor and manage our natural resources, especially in the areas of agriculture, ecosystems, and water resources. However, in spite of significant progress in recent years, there are still many areas where the potential of remote sensing has not been fully realized, and these are areas of active research. 

Of unique importance are those efforts that are focused on gaining a better understanding of what sensors are actually measuring as well as new applications and inverse modelling techniques. Contributions using visible, near- and thermal infrared, microwave and other wavebands are solicited, as well as applications using laser/LiDAR or hyperspectral imaging. The conference is especially interested in papers, which emphasize the use of data from satellite, nanosatellites, airborne and UAV platforms, describing recent research results in the hydrological, agricultural and ecosystems sciences. Contributions are sought for state-of-the-art research and operational applications, in particular related to water cycle research and climate change. Invited keynote speakers will present overviews of problems, progress and prospects in key areas. Supporting papers are requested that review the latest contributions of Earth Observations (EO) to water cycle and soil-vegetation-atmosphere sciences from global to basin to plot scales (e.g., precipitation, soil water content, water levels, surface water, groundwater, land and water mass and heat exchanges). Also assessing the advances and identify the needs in physical modeling, including uncertainties and consistency quantification and data assimilation of EO-based observations to improve our knowledge of water, vegetation and ecosystems processes and our ability to assess future changes in water cycle, extreme events and hydrological hazards. 

Understanding of small-scale complex environmental systems is still a challenging problem due to interface between global and regional data sets. This is driven by lack of in situ observations and the variety of downscaling techniques used to model the regional issues. These are the pre-requisites for addressing urban to regional problems such as agriculture health, water resource management, drought and food security. 

In recent years, opportunities for big data analysis in food and agricultural production are arising. Technological advancements in remote sensing coupled with advances in IT, mobile/cloud computing (smart phones, wearable devices), wide spread adoption of GPS, internet of things (everything gets connected in the internet), and all advanced digital technologies have created a unique opportunity for implementing smarter solutions for large and smallholder farmers globally, leading to increased productivity, reduced resource consumption, and improved food security. These techniques allow for the delivery of high-tech agricultural services and precision agriculture based on remote sensing. 

Also, distributed networks provide the opportunity for setting up integrated processing for near real-time regional or global monitoring products for hydrology; agriculture; and ecosystems: e.g., HF radar networks, ground stations, GPS networks, flux towers, etc. 

A joint session on Monitoring of Soil and Vegetation Water Content in Agricultural and Natural Ecosystems will be held with the sister Conference on “Active and Passive Microwave Remote Sensing for Environmental Monitoring”.