# A systematic map of methods for assessing societal benefits of Earth science information

**Authors:** Casey C. O’Hara, Mabel Baez-Schon, Rebecca Chaplin-Kramer, Samantha H. Cheng, Alejandra Echeverri, Gillian L. Galford, Rachelle K. Gould, Cristina L. Mancilla, Maura C. Muldoon, Gerald G. Singh, Priscilla Baltezar, Yusuke Kuwayama, Stephen Polasky, Amanda D. Rodewald, Richard P. Sharp, Elizabeth J. Tennant, Jiaying Zhao, Benjamin S. Halpern

PMC · DOI: 10.1073/pnas.2524370123 · 2026-02-06

## TL;DR

This paper maps methods used to assess how Earth science information benefits society, highlighting diverse approaches and the need for better quantification of these benefits.

## Contribution

A systematic mapping of valuation methods for Earth science information's societal benefits, revealing methodological diversity and gaps.

## Key findings

- Most studies use decision analysis methods to assess quantitative instrumental values like profit and crop yield.
- Fewer studies capture qualitative and relational values like empowerment and justice through preference elicitation.
- Many studies focus on agriculture, and there is a need for more systematic valuation approaches to align science with societal goals.

## Abstract

Earth science information (ESI) from satellites and other remote sensing technologies is critical for managing climate, agriculture, disasters, and more. Yet the societal value of ESI, how it improves real-world decisions and outcomes, remains poorly understood. We systematically map studies that quantify this value, revealing how different methods capture diverse benefits, from economic efficiency and lives saved to empowerment and justice. Our findings demonstrate that a rich array of methods exists to assess societal benefits of ESI across many decision contexts, identifying benefits in terms of instrumental and relational values. This synthesis expands the evidence base for why ESI matters and how it can help guide future investments, promote public support, and align Earth science with societal goals.

Remotely sensed Earth science information (ESI) has become increasingly central to addressing global challenges, yet its societal value, i.e., the difference ESI makes in real-world decisions and outcomes, is rarely quantified. In this study, we systematically map peer-reviewed literature that explicitly assesses the societal value of ESI across instrumental, intrinsic, and relational value types, and the diversity of approaches used to assess those values. Drawing from 13,823 publications across Scopus, Web of Science, and a curated library of ESI valuation studies, we identify 171 studies that applied ESI in a decision context and used a valuation method to compare outcomes with and without ESI. The majority of these studies employed decision analysis methods (e.g., Value of Information, Cost–Benefit Analysis), focusing primarily on quantitative instrumental values (e.g., profit, crop yield, lives saved), particularly in agricultural contexts. A smaller set of studies applied preference elicitation methods (e.g., stated preference, surveys, interviews, focus groups) to capture qualitative benefits and relational values including quality of life improvements, empowerment, and procedural justice. Many excluded studies demonstrated scientific value of ESI but did not explicitly translate that into societal value, revealing the need for a more systematic approach to ESI valuation. By promoting a more inclusive, interdisciplinary, and flexible portfolio of valuation methods, we aim to expand our understanding of the societal benefits of ESI to help guide investment in future missions, enhance public support, and ensure that science and policy goals are well aligned.

## Full-text entities

- **Diseases:** drought (MESH:C536747), polio (MESH:D011051)
- **Chemicals:** PNAS (MESH:D020135)
- **Species:** Helianthus annuus (common sunflower, species) [taxon 4232], Homo sapiens (human, species) [taxon 9606], Balaenoptera musculus (blue whale, species) [taxon 9771], Cetacea (cetaceans, infraorder) [taxon 9721]

## Figures

5 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12890935/full.md

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Source: https://tomesphere.com/paper/PMC12890935