Toward Real-Time Earth System Intelligence Through Advancements in Onboard AI Processing: A review

Domenico Barretta; Luca Marini; Francesca Razzano; Giorgia Guerrisi; Sanna Sandberg; Roberto Del Prete; Valentina Zancan; Jian Guo; Gabriele Meoni; More Authors

doi:10.1109/MGRS.2026.3665978

Toward Real-Time Earth System Intelligence Through Advancements in Onboard AI Processing: A review

Domenico Barretta^*, Luca Marini, Francesca Razzano, Giorgia Guerrisi, Sanna Sandberg, Roberto Del Prete, Valentina Zancan, Jian Guo, Gabriele Meoni, More Authors

^*Corresponding author for this work

Space Systems Engineering

Research output: Contribution to journal › Review article › peer-review

Abstract

The Earth Observation (EO) sector is rapidly evolving into Earth Action (EA), with onboard Artificial Intelligence (AI) processing emerging as a key enabler. This technology offers strategic advantages through 1) enabling autonomous and low-latency EO missions with adaptive data processing capabilities that overcome the limitations of ground-based post-processing in handling the vast data volumes produced by growing satellite constellations and 2) supporting the evolution toward AI-driven and distributed EO mission architectures. This review explores the key technological advancements, mission architectures, and emerging paradigms that are shaping the next-generation EO systems. Pioneering EO missions are presented to showcase current capabilities, while the commercial, technical, and operational implications are analyzed alongside key challenges and ongoing research efforts (January 2020 to March 2025) aimed at enabling Real-Time (RT) Earth system intelligence.

Original language	English
Pages (from-to)	392-441
Number of pages	50
Journal	IEEE Geoscience and Remote Sensing Magazine
Volume	14
Issue number	3
DOIs	https://doi.org/10.1109/MGRS.2026.3665978
Publication status	Published - 2026

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title = "Toward Real-Time Earth System Intelligence Through Advancements in Onboard AI Processing: A review",

abstract = "The Earth Observation (EO) sector is rapidly evolving into Earth Action (EA), with onboard Artificial Intelligence (AI) processing emerging as a key enabler. This technology offers strategic advantages through 1) enabling autonomous and low-latency EO missions with adaptive data processing capabilities that overcome the limitations of ground-based post-processing in handling the vast data volumes produced by growing satellite constellations and 2) supporting the evolution toward AI-driven and distributed EO mission architectures. This review explores the key technological advancements, mission architectures, and emerging paradigms that are shaping the next-generation EO systems. Pioneering EO missions are presented to showcase current capabilities, while the commercial, technical, and operational implications are analyzed alongside key challenges and ongoing research efforts (January 2020 to March 2025) aimed at enabling Real-Time (RT) Earth system intelligence.",

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T2 - A review

AU - Barretta, Domenico

AU - Marini, Luca

AU - Razzano, Francesca

AU - Guerrisi, Giorgia

AU - Sandberg, Sanna

AU - Del Prete, Roberto

AU - Zancan, Valentina

AU - Guo, Jian

AU - Meoni, Gabriele

AU - More Authors,

PY - 2026

Y1 - 2026

N2 - The Earth Observation (EO) sector is rapidly evolving into Earth Action (EA), with onboard Artificial Intelligence (AI) processing emerging as a key enabler. This technology offers strategic advantages through 1) enabling autonomous and low-latency EO missions with adaptive data processing capabilities that overcome the limitations of ground-based post-processing in handling the vast data volumes produced by growing satellite constellations and 2) supporting the evolution toward AI-driven and distributed EO mission architectures. This review explores the key technological advancements, mission architectures, and emerging paradigms that are shaping the next-generation EO systems. Pioneering EO missions are presented to showcase current capabilities, while the commercial, technical, and operational implications are analyzed alongside key challenges and ongoing research efforts (January 2020 to March 2025) aimed at enabling Real-Time (RT) Earth system intelligence.

AB - The Earth Observation (EO) sector is rapidly evolving into Earth Action (EA), with onboard Artificial Intelligence (AI) processing emerging as a key enabler. This technology offers strategic advantages through 1) enabling autonomous and low-latency EO missions with adaptive data processing capabilities that overcome the limitations of ground-based post-processing in handling the vast data volumes produced by growing satellite constellations and 2) supporting the evolution toward AI-driven and distributed EO mission architectures. This review explores the key technological advancements, mission architectures, and emerging paradigms that are shaping the next-generation EO systems. Pioneering EO missions are presented to showcase current capabilities, while the commercial, technical, and operational implications are analyzed alongside key challenges and ongoing research efforts (January 2020 to March 2025) aimed at enabling Real-Time (RT) Earth system intelligence.

UR - https://www.scopus.com/pages/publications/105035019187

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JO - IEEE Geoscience and Remote Sensing Magazine

JF - IEEE Geoscience and Remote Sensing Magazine

IS - 3

ER -

Toward Real-Time Earth System Intelligence Through Advancements in Onboard AI Processing: A review

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