Smart systems are expected to revolutionize many – if not all – sectors of human activities during the Anthropocene. These systems are highly driven by information in the large sense of the term. Information is manipulated in a variety of forms (data cubes, NoSQL, Hadoop…). It is analyzed using advanced analytics (machine learning, deep learning… ). In this presentation, Dr. Al Bitar will aboard the question of the place of remote sensing from space in smart systems. Naturally, remote sensing by satellite is not strange to this revolution. Current Earth Observation (EO) missions like the Copernicus programme from the European Commission are delivering huge amounts of data covering a large spectrum of applications. In parallel, low-cost nanosatellite constellations are becoming common such that they are considered as the “new space industry”. The two-way benefit will be discussed. First, how the information from the satellite is currently used to enhance the predictability of the urban and agronomical system needs. Two concrete examples will be shown: on urban environment and on crop modeling of agronomical systems. The question of potential benefits of these data to a smart system will be open for discussion. The second section will put in perspective how the advanced analytics and distributed sensors in smart systems benefit the EO missions. A discussion will follow the presentation.
About the speaker
Ahmad Al Bitar received his PhD in Numerical Modelling in Earth Sciences from the Institut National Polythechnique de Toulouse in 2007. Since 2008, he was involved in the SMOS mission from commissioning to production. Currently he is in charge of highly added-value products for the SMOS mission. His research interest concerns the integration of remote sensing data in dynamic modelling of the water and energy cycles. He was PI, Co-PI and WP lead in H2020, ANR, TOSCA and ESA ITT projects. He is member of the Science Definition Team of the SWOT mission (NASA, CNES) and member of the Expert Scientific Lab for SMOS mission (ESA, CNES). He is co-receiver of the IEEE TGRS award for most highly cited paper in 2017. He is co-author of 72 papers in peer reviewed journals with a h-index of 24 and an i-10 index of 41.