THE PROMISE OF HYPERSPATIAL REMOTE SENSING FOR UNDERSTANDING AEOLIAN PROCESSES: AN EXAMPLE USING PLANETSCOPE AT “THE DUSTIEST PLACE ON EARTH”

For more than three decades, a range of Earth observation data and techniques have been used to assemble a catalogue that has allowed researchers to improve our understanding of aeolian processes, especially the global dust cycle. Initial studies, using TOMS- the Total Ozone Mapping Spectrometer- achieved the first global geospatial assessments of dust emission and transport. This step paved the way for extensive use of remote sensing data, such as from MODIS- the Moderate Resolution Imaging Spectroradiometer- to further our understanding of how geomorphology and climate control terrestrial sources of dust aerosols. However, ability to record components of the aeolian dust cycle at the fine spatial scale at which field measurements are collected has been limited to date. Here, we demonstrate the potential of hyperspatial remote sensing to investigate dust source behaviour. Recent advancements in microsatellite and sensor ‘constellation’ technology now provide the capability to examine dust sources and monitor active dust emission processes at an unprecedented level of precision. Planet Lab’s constellation of Dove satellites equipped with the PlanetScope sensor allows a spatial resolution of ~2-5 m and time scales of ~1 day, with <24 h turnover between data capture and its readiness for download and processing. We provide a preliminary illustration of its potential by applying PlanetScope imagery to two dust emission cases in the dustiest place on Earth, the Bodélé Depression of North Africa, to show its ability to query aeolian processes at high detail. In this example, our data allow visualisation of the interaction between saltation flux and the erodible diatomite surface that drives the extreme dustiness of the Bodélé Depression. We demonstrate the potential of these data to inform modelling of dust uplift from the surface- the first, crucial stage of the global dust cycle. In broader terms, this case study illustrates how demands for improved spatial and temporal resolution deemed necessary for process observations across the geosciences can be met via recent advances in Earth observation science.