SESAC

100 Critical Questions for Earth Observation and the Social Sciences

Earth Observation (EO) data provide a powerful way to observe, measure, and understand changes across the Earth’s surface, atmosphere, and human-environment systems. EO includes satellite-based remote sensing and can be complemented by airborne, ground-based, and in-situ observations. These data provide spatially extensive, repeatable, and regularly updated information that can support the analysis of environmental, social, and economic processes across multiple scales (Chuvieco, 2008; Zhao et al., 2022).

EO can help address these gaps by providing spatially detailed and comparable evidence. In data-rich settings, EO can also serve as a bridge between heterogeneous datasets, helping researchers integrate, validate, and explore information across surveys, registers, field observations, citizen science, and other spatial data sources.

While EO has long been central to environmental monitoring, climate science, land-use analysis, and disaster response, its potential contribution to the social sciences remains underdeveloped. Many societal challenges unfold unevenly across space and time: urbanisation, environmental degradation, land-use and land-cover change, vegetation and ecosystem dynamics, socio-economic inequalities, conflict, displacement, and human-environment interactions. These issues are often difficult to study using conventional social science methods alone, especially in data-scarce regions or in contexts where administrative data are incomplete, outdated, or spatially inconsistent (Kansakar & Hossain; Li et al., 2020).

Why is a horizon scan needed?

Despite growing technical capabilities, EO remains underused in many areas of social science compared with its established role in physical and environmental sciences. This gap reflects several challenges. EO analysis often requires technical expertise in remote sensing, geospatial analysis, coding, and data processing. It can also be difficult to translate satellite-observed physical signals, such as roofs, roads, vegetation, water, night-time lights, or land cover, into meaningful social indicators.

There are also important conceptual and ethical questions. Social conditions rarely have direct spectral signatures. They must usually be inferred through models, proxies, contextual knowledge, and validation data. This makes interpretation, uncertainty, bias, privacy, and responsible use central concerns. EO-based social analysis therefore requires interdisciplinary frameworks that combine technical methods with social theory, local knowledge, participatory approaches, and careful attention to the people and communities represented in the data (Fritz et al., 2017; Gevaert, 2022).

This initiative responds to that need through a Horizon Scanning approach. Horizon scanning is a systematic, forward-looking method used to identify emerging trends, critical uncertainties, and priority research questions. Similar approaches have been used in sustainability, development, and ecology to identify sets of 100 key questions for future research and action (Oldekop et al., 2016; Sutherland et al., 2013).

What are we trying to identify?

Through this Horizon Scan, we aim to identify 100 critical questions at the intersection of Earth Observation and the social sciences.

We are interested in questions that can help shape the future of the field, including questions about:

• How can EO support social science research and policy-relevant analysis?
• Which societal challenges can benefit most from EO-based evidence?
• How can EO be combined with surveys, registers, participatory data, citizen science, and local knowledge?
• How can artificial intelligence, machine learning, and explainable AI support responsible EO-based social analysis?
• Where is EO already making meaningful contributions?
• Where is its potential underexplored?
• What methodological, ethical, legal, and political risks need greater attention?
• How unequal access to data, infrastructure, expertise, and decision-making power shapes the global EO landscape.

The goal is not only to list technical research problems, but to build a shared agenda for a more integrated, inclusive, and socially relevant EO research community.

Who can contribute?

We invite contributions from researchers, practitioners, policymakers, civil-society organisations, public agencies, private-sector actors, students, and others working with, using, or critically engaging with Earth Observation and social science.

Participants may come from fields such as geography, sociology, political science, economics, urban studies, development studies, sustainability science, risk research, public health, remote sensing, data science, artificial intelligence, environmental science, or related areas.

How will the process work?

The Horizon Scan will use a collaborative process involving surveys, open workshops, discussion, refinement, and structured prioritisation. Submitted questions will be reviewed, grouped, discussed, and refined through participatory steps. The final outcome will be a prioritised set of 100 critical questions that reflect diverse perspectives across disciplines, sectors, and regions.

By contributing, participants will help take stock of the current state of EO-related social science research, identify emerging priorities, and highlight the opportunities and risks that should shape the field in the coming years.

Take part in the survey

Please use the survey form below to submit the questions you believe are most important for the future of Earth Observation and the social sciences.

We welcome broad, forward-looking, and critical questions. These may relate to methods, applications, theory, ethics, data access, governance, participation, artificial intelligence, policy uptake, or other issues that you believe deserve attention.

References

Chuvieco, E. (Ed.). (2008). Earth Observation of Global Change: The Role of Satellite Remote Sensing in Monitoring the Global Environment. Springer. https://doi.org/10.1007/978-1-4020-6358-9

Fritz, S., Fonte, C. C., & See, L. (2017). The role of citizen science in Earth Observation. Remote Sensing, 9(4), 357. https://doi.org/10.3390/rs9040357

Gevaert, C. M. (2022). Explainable AI for Earth Observation: A review including societal and regulatory perspectives. International Journal of Applied Earth Observation and Geoinformation, 112, 102869. https://doi.org/10.1016/j.jag.2022.102869

Kansakar, P., & Hossain, F. (2016). A review of applications of satellite Earth Observation data for global societal benefit and stewardship of planet Earth. Space Policy, 36, 46–54. https://doi.org/10.1016/j.spacepol.2016.05.005

Li, D., Guo, W., Chang, X., & Li, X. (2020). From Earth Observation to human observation: Geocomputation for social science. Journal of Geographical Sciences, 30, 233–250. https://doi.org/10.1007/s11442-020-1725-8

Oldekop, J. A., Fontana, L. B., Grugel, J., Roughton, N., Adu-Ampong, E. A., Bird, G. K., Dorgan, A., Vera Espinoza, M. A., Wallin, S., Hammett, D., Agbarakwe, E., Agrawal, A., Asylbekova, N., Azkoul, C., Bardsley, C., Bebbington, A. J., Carvalho, S., Chopra, D., Christopoulos, S., … Sutherland, W. J. (2016). 100 key research questions for the post-2015 development agenda. Development Policy Review, 34(1), 55–82. https://doi.org/10.1111/dpr.12147

Sutherland, W. J., Freckleton, R. P., Godfray, H. C. J., Beissinger, S. R., Benton, T. G., Cameron, D. D., Carmel, Y., Coomes, D. A., Coulson, T., Emmerson, M. C., Hails, R. S., Hays, G. C., Hodgson, D. J., Hutchings, M. J., Johnson, D., Jones, J. P. G., Keeling, M. J., Kokko, H., Kunin, W. E., … Wiegand, T. (2013). Identification of 100 fundamental ecological questions. Journal of Ecology, 101(1), 58–67. https://doi.org/10.1111/1365-2745.12025

Zhao, Q., Yu, L., Du, Z., Peng, D., Hao, P., Zhang, Y., & Gong, P. (2022). An overview of the applications of Earth Observation satellite data: Impacts and future trends. Remote Sensing, 14(8), 1863. https://doi.org/10.3390/rs14081863