ESRA 2027 sessions by theme
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Integrating Remote Sensing and Survey Data: Methodological Innovations, Practical Challenges, and Substantive Applications |
| Coordinator 1 | Dr Susanne de Vogel (Data Science Center, University of Bremen) |
| Coordinator 2 | Dr Rajini Nagrani (Leibniz Institute for Prevention Research and Epidemiology (BIPS)) |
| Coordinator 3 | Dr Annika Nolte (Data Science Center, University of Bremen) |
| Coordinator 4 | Ms Alexandra Nozik (Leibniz Centre for Tropical Marine Research (ZMT)) |
Session Details
Remote sensing data—from satellite imagery and aerial observations to derived geospatial indicators—offer growing opportunities to enrich survey research with spatially detailed and temporally dynamic information about the environments in which people live. Linking such data to surveys can extend substantive analyses, improve contextual measurement, support sampling and estimation, and open new avenues for studying social and environmental processes. At the same time, bringing survey and remote sensing data together raises methodological, computational, and other practical challenges that require closer exchange between survey specialists, statisticians, researchers from the social, behavioural and health sciences, and remote sensing experts.
This session invites contributions on the integration of survey and remote sensing data across the research process. We welcome methodological work on data linkage and integration, spatial and temporal alignment, measurement and representation, sampling, weighting, small-area estimation, uncertainty, and validation. This may also include the use of machine learning or other computational methods to derive, combine, or validate information from remote sensing and survey data. We further encourage contributions addressing practical challenges, including geocoding, data access and processing, computational workflows, reproducibility, privacy and disclosure risks, and interdisciplinary collaboration. Finally, we explicitly invite substantive applications that demonstrate how these combined data sources can advance research questions across the social, behavioural, health, and economic sciences, including research on environmental and public health, health and social inequalities, mobility, urban and rural characteristics, political and economic behaviour, or other spatially embedded phenomena.
By bringing together methodological contributions, practical experiences, and substantive research applications, the session aims to identify both the potential and the limits of remote sensing as a complementary data source for survey research and to foster exchange across disciplinary boundaries.
