When only local participation in fieldwork is possible, how effectively can remote collaborations be executed in the field sciences, when so much diverse expertise is required?

Foremost is a comprehensive investment in the creation of digital archives at different scales. Various government agencies and developer-led fieldwork as well as excavations in extreme locations have been using such methods and techniques for years14. However, practice is neither standardized nor mainstreamed across comparable research projects, and in the context of COVID-19 there are many reasons to push for such goals.

First, the creation of high-resolution photographic databases for photogrammetry is relatively easy to teach remotely, and is inexpensive, although post-processing time is substantial and requires investment in technicians. These techniques can record and visualize spatial relationships, stratigraphic sequences and, depending on the use of different light, may permit assessments that can even be superior to traditional by-eye illustrations14. Specialists can clearly mark sampling locations on the models for those on site, enabling group assessments. Second, the creation of three-dimensional (3D) geological and sedimentary archives also enables re-assessment of sequences in future. Third, the creation and sharing of both the archives and their interpretations will precipitate the much-needed standardization of sampling and analytical procedures. Within an open data framework, this working model will ensure that novice researchers and non-specialists learn from experts through collaborative, team-based inferences, rather than stitching together the results of individual specialists in a top-down approach.

Our existing international field season schedules also require change — a long-overdue adjustment in the face of increasing anthropogenically induced climate change. Fieldwork will be based locally and projects will require many short and closely spaced field seasons. Those who can access our field sites within a few hours can conduct short-distance trips, focused on discrete steps in the process of assessment, excavation, sampling and inference. For example, a short initial season would focus on building a high-resolution digital model of the field site that can be shared with remote collaborators to develop excavation strategies. A later season could focus solely on sampling, following remote collaborative assessment of digital archives. Such approaches also in part mitigate the problems faced by less-accessible field sites, where frequent online meetings and the exchange of information are impossible. Effective remote collaboration will require very clear scheduling among remote experts at each phase of the process to minimize the burden on local researchers.

At a landscape scale, the situation becomes more challenging. 3D models from unmanned aerial vehicles (UAVs), remote-sensing data15 and LiDAR16 are already widely used in prospection and analysis, and may facilitate effective collaboration between remote specialists and local participants. Remotely generated landscape-scale hypotheses and geomorphological maps can be tested at a later stage by specialists on the ground, whenever longer-distance travel becomes an appropriate option. The creation of 3D data using UAVs does not represent a considerable remote training challenge. A major new research focus should address the extent to which these methods and predictive models in geomorphology are able to replicate, complement and validate assessments of landscape-scale processes made in the field.

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