The Greenland Drone Explorer: A WebGIS for browser-based visualization and spatial browsing of published UAS raster imagery

Abstract:

Small uncrewed aerial systems (sUAS, or drones) have become standard tools across many scientific fields by enabling affordable, on-demand aerial surveys. A single sUAS survey can generate hundreds to thousands of overlapping images that, once processed, produce large raster products (orthomosaics and digital surface models) that are often many gigabytes in size, making adherence to the FAIR data principles difficult. Re- positories such as Zenodo and PANGAEA satisfy the findability requirement through appropriate metadata and persistent identifiers, but they do not provide visualization or spatial browsing of geospatial raster imagery. Assessing whether an archived dataset is fit for reuse therefore requires downloading large files and importing them into specialized GIS software before any visual inspection is possible. The friction introduced by these additional steps may limit reuse. Limited reuse is especially wasteful in remote regions such as Greenland, where sUAS surveys are expensive and logistically demanding to conduct and where features of interest from multiple disciplines are concentrated within the same small coastal footprints, giving each survey high cross-disciplinary reuse potential. To illustrate the value of visualization and spatial browsing for published sUAS datasets, we present the Greenland Drone Explorer (GDE), a WebGIS that aggregates dispersed, already-published Greenland sUAS datasets and enables 2D and 2.5D preview of orthomosaics without download or GIS software. As a vendor-neutral alternative to the proprietary platform on which GDE is built, we pair it with an open-source Jupyter notebook that reproduces the same capability by retrieving data from Zenodo, generating cloud-optimized GeoTIFFs, and displaying them in a browser-based map. Thus, GDE augments the baseline findability pro-vided by repositories with spatial, visual discovery that may lower the barrier to reuse of dispersed sUAS raster imagery.

https://doi.org/10.1016/j.geomat.2026.100123