Drylands, covering more than 40% of the Earth's land surface, are water-limited regions where evaporation exceeds precipitation. They serve as the main reservoirs of carbon regulating global trends and variability in atmospheric CO2, represent a key source to the global dust cycle, and host diverse endemic plants and animals. Moreover, drylands’ extent is projected to expand, as climate change intensifies aridity, triggering abrupt ecosystem changes which could affect services supporting more than two billion people. Consequently, developing integrated tools for assessing and monitoring of dryland ecosystems represents a high research priority. Advances in Earth observation —including high resolution UAV and satellite imagery and deep learning —have enabled unprecedented spatial, temporal and spectral resolution facilitating breath-taking progress in this field of research. However, dryland remote sensing is particularly challenging due to the complex landscapes, sparse vegetation, and high proportions of open areas with background effect. Moreover, biological soil crusts, representing soil surface communities of cyanobacteria, algae, lichens, and bryophytes, also affects the spectral signal of dryland soils. Owing to the various vegetation types that shows different timing responses to water pulses, their spectral response to the infrequent rainfall to be strongly heterogeneous and hampers the application of remote sensing methodologies for the monitoring of ecosystem state and processes in drylands.
This session invites novel remote sensing approaches and applications for drylands, focusing on surface component mapping and monitoring. A special focus is also on the new generation of hyperspectral satellite missions like Environmental Mapping and Analysis Program (EnMAP) and their integration with other data sources, such as multispectral and hyper spatial resolution UAV imagery. All contributions of combining remote sensing and field data to identify ecosystem patterns, processes, and functional traits are also welcome.