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Catapult Home / Digital Library / An Earth Observation Framework for the Lithium Exploration
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An Earth Observation Framework for the Lithium Exploration

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Catapult Co-Authors: Cristian Rossi, Maral Bayaraa, Stephen Spittle, Anoop Pandey, Niki Henry

This paper presents an overview of a large research project involving collaboration from the government, academia and industry on lithium (Li) exploration in South-West Cornwall, UK. Scope of the study is to assess the utility of remote sensing technologies in the mining sector, with a particular focus on lithium. A wide range of datasets (including multispectral and Synthetic Aperture Radar (SAR)) are used to delineate the various steps of the project. The ultimate aims are the generation of a map with the probability of lithium occurrence and a complementary environmental baseline study. For the first aim, geological and vegetation anomalies maps indicating proxies for the presence of lithium, derived from multi- and hyperspectral data, and fault lines, derived from SAR imagery, are integrated with in-situ data and a ground-based campaign. The second aim involves the generation of a high-resolution land cover classification and a historical time series analysis to provide an environmental baseline study for the assessment of the impact of mining activities.

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Cristian Rossi
Principal Earth Observation Specialist
+44 (0)1235 567999
Cristian Rossi received the B.
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Sc and M Sc degrees in telecommunication engineering from the Polytechnic of Milan, Italy, and the Ph D degree in remote sensing technology from the Technical University of Munich, Germany Before joining Catapult, he was a Research Scientist with the German Aerospace Center (DLR), where he was involved in the development of the integrated TanDEM-X processor and in the definition of novel algorithms for synthetic aperture radar missions Since 2017, he has been the Principal Earth Observation Specialist at the Catapult, where he is technically leading several national and international projects focused on the exploitation of remote sensing data for land applications

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