Lucien Hoffmann (LIST): “One of the important challenges is to manage, analyze and process this big geospatial data effectively”

Earth observation (EO) is acknowledged as a field that has revolutionized our understanding of our planet and its complex systems. With advancements in satellite technology, remote sensing, and data analytics, EO has become an essential tool for monitoring changes in our environment, from tracking the effects of climate change to managing natural resources and predicting natural disasters.

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Publication date : 04/11/2023


Farvest Space encountered Lucien Hoffmann, ERIN Department Director at LIST, to bring wealth of knowledge and experience to the table, and to dive deeper into this fascinating subject.

How has Earth observation technology evolved over the past few decades, and which has been the biggest advancement?

After more than 60 years of development, Earth observation (EO) satellites have flourished. The significant advances in the spatial, spectral, and temporal resolution of EO data brought about by improvements in remote sensing technology have dramatically changed how we observe the Earth. Multi-spectral and hyper-spectral technologies, microwave radiometer, spaceborne radar, and synthetic aperture radar on EO satellites now satisfy the needs of many downstream applications. Additionally, as the costs of instruments and launching satellites have fallen, EO data have become more widely available. In addition to large multi-sensor platforms, the number of small satellites and unmanned aerial vehicles has exploded.

How has space observation contributed to our understanding of the Earth, and which were the most exciting discoveries made possible by this technology?

In recent decades, we have experienced rapid growth in Earth Observation (EO) satellites, which has allowed us to gather plenty of information about planet Earth’s physical, chemical and biological systems. Satellite imagery provided the first large-scale maps of land cover, weather patterns, vegetation health, atmospheric pollutants, soil moisture and rock types, among others. Be it land, sea or air, EO is today the most robust technology to monitor and assess the status of, and changes of our environment. The information obtained by EO satellites is widely used in various applications, especially in relation to the environment, where the measurements made by EO satellites are indispensable in such domains as forestry, agriculture, geology, disease and public health, as well as in the monitoring of land degradation, oceans and coastal areas, biomass and carbon, urban areas, natural disasters, land use and land cover, the atmosphere, biodiversity and water resources. 

Of particular relevance are also the contributions of EO data to assess greenhouse gas emissions, making EO pivotal in ensuring consistent, long-term environmental assessments in face of unpredictable climate change. Another important use case is disaster management in which the Environmental Research and Innovation department of the Luxembourg Institute of Science and Technology (LIST) and its spin-off Wasdi have gained international recognition. Thus the algorithms developed by the LIST researchers implemented on the multi-cloud platform of Wasdi are used worldwide for flood monitoring, e.g very recently in Pakistan and Indonesia.

What are some of the key challenges in Earth observation today, and how are they being addressed?

Over the last decades, the number of satellite instruments and the quality and scope of the information collected by satellites have constantly been improving, which lead to substantial and ever-increasing data volumes. One of the important challenges today is to manage, analyze and process this big geospatial data effectively. This will entail e.g. (1) increasing the number of initiatives and infrastructures to allow a fast access to the data, such as the Copernicus Open Access Hub or the dedicated collaborative ground segment, e.g. the Luxembourg Space Agency (LSA) Data Center, which aims to accelerate the development of the downstream sector of related value-adding applications; (2) the development of the next generation state-of-art data processing approaches that rely on rigorous forward modeling and numerical inversion methodologies, and use artificial intelligence techniques, such as deep learning and neural networks; (3) the adoption of a new computing paradigm that consists in moving away from a local processing of large amounts of data on desktop PCs towards massive processing using cloud-based services. 

An important challenge is also to achieve continuity in consistent satellite observations and long-term data sets by assuring sufficient compatibility and agreement of past, present and future data sets that are required for example for climate change-related issues.

How are Earth observation technologies likely to evolve over the next decade or two, and which kinds of new capabilities might we see?

Increasing information content of observations by deploying the satellite instruments with enhanced capabilities and exploring synergies of complementary observations, combining satellite observations with terrestrial in situ observations, and assimilating the data in environmental models. Moreover, the provision of these large quantities of data to the end users has no operational value per se. Thus, the goal will be to rapidly transform the raw EO data to generate intuitive, understandable and quantitative measurements, enabling evidence-based decision-making in different areas that are relevant for society.

How important is collaboration among scientists and organizations/institutions in Earth observation research?

Developing downstream applications is a truly interdisciplinary effort, bringing together image processing specialists, data scientists, modellers, and the different user communities. Beyond that it is of paramount importance to have for many applications EO data that are available in near-real time, respectively large datasets that are archived. There is thus also an important need for efficient IT infrastructures guaranteeing the availability of the EO data.



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