High-Resolution Remote Sensing Data as a Boundary Object to Facilitate Interdisciplinary Collaboration
Contribution to Books
Native forest regrowth in degraded tropical landscapes is critical for biodiversity conservation, carbon sequestration, and human livelihoods. However, social and ecological drivers of reforestation have primarily been studied in separate disciplinary frameworks and at different spatial scales. In southwestern Panama, we found that scale mismatches between satellite data used to study land cover change, forest inventory plots used to study ecological dynamics, and household survey data used to study farmer behavior were a major impediment to our research goals. We overcame the challenges posed by scale mismatches by applying high-resolution remote sensing data to facilitate interdisciplinary research. We describe how our data sources enabled us to scale up ecological field data, present our research to stakeholders, and resolve discrepancies between data at different scales. High-resolution imagery can thus facilitate boundary crossing via cross-scale research on coupled natural-human systems.
Caughlin, T. Trevor; Graves, Sarah J.; Asner, Gregory P.; Tarbox, Bryan C.; and Bohlman, Stephanie A. (2019). "High-Resolution Remote Sensing Data as a Boundary Object to Facilitate Interdisciplinary Collaboration". In S.G. Perz (Ed.), Collaboration Across Boundaries for Social-Ecological Systems Science: Experiences Around the World (pp. 295-326). Springer. https://doi.org/10.1007/978-3-030-13827-1_9