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2023•Unpublished venueOpen access

Exploring the Potential of Compressive Sensing Payloads for Earth Observation from Geostationary Platforms: An Instrumental Concept for Fire Monitoring

Donato Borrelli, Massimo Baldi, Dirk Berndt, Lucas Bertoncini, Tiziano Bianchi, Lionel Bischof, Guzmán Borque Gallego, Roberto Carlà, Peter Coppo, Chiara Corti, Francesco Corti, Marco Corti, N. L. J. Cox, Ulrike Dauderstädt, Peter Dürr, Enrico Franci, Sara Francés González, Andrea Gonnelli, I. Guerri, Donatella Guzzi, Stéphane Humbert, Demetrio Labate, Nicolas Lamquin, Cinzia Lastri, Enrico Magli, Emiliano Marzi, Andrea Migliorati, Vanni Nardino, Christophe Pache, Lorenzo Palombi, Alice Maria Piccirillo, Giuseppe Pilato, Enrico Suetta, Dario Taddei, Diego Valsesia, Michael Wagner, Valentina Raimondi

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Abstract

Earth observation (EO) payload performances in the infrared spectral region from geostationary platforms are often limited by spatial resolution. In this paper, we investigate an instrumental concept leveraging a compressive sensing paradigm and super-resolution architecture to implement an EO payload from a geostationary platform aimed at the monitoring of wildfires with a nominal spatial sampling distance of 500 m. The core device of the instrument is a European-technology-based micromirror array under study for space applications. Besides payload specifications and working principles, the main critical aspects and the expected impact on EO applications are discussed.

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Earth observation (EO) payload performances in the infrared spectral region from geostationary platforms are often limited by spatial resolution. In this paper, we investigate an instrumental concept leveraging a compressive sensing paradigm and super-resolution architecture to implement an EO payload from a geostationary platform aimed at the monitoring of wildfires with a nominal spatial sampling distance of 500 m. The core device of the instrument is a European-technology-based micromirror array under study for space applications. Besides payload specifications and working principles, the main critical aspects and the expected impact on EO applications are discussed.

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Available abstract

Earth observation (EO) payload performances in the infrared spectral region from geostationary platforms are often limited by spatial resolution. In this paper, we investigate an instrumental concept leveraging a compressive sensing paradigm and super-resolution architecture to implement an EO payload from a geostationary platform aimed at the monitoring of wildfires with a nominal spatial sampling distance of 500 m. The core device of the instrument is a European-technology-based micromirror array under study for space applications. Besides payload specifications and working principles, the main critical aspects and the expected impact on EO applications are discussed.

Key concepts: Geostationary orbit, Payload (computing), Remote sensing, Earth observation, Computer science, Compressed sensing, Sampling (signal processing), Image resolution

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