Drone thermal imaging and benthic time-series analysis show dynamic spatial and temporal delivery of submarine groundwater discharge on reef ecosystems

The Black Point (Oʻahu, Hawaiʻi) reef flat is a groundwater-impacted coastal ecosystem where submarine groundwater discharge (SGD) delivers low-salinity, nutrient-rich water that modulates nearshore biogeochemistry. To resolve fine-scale SGD delivery that is difficult to capture with conventional, labor-intensive in situ mapping alone, we combined a cost-effective small uncrewed aerial system with a thermal-infrared (sUAS-TIR) sensor and co-located benthic salinity/temperature time series. The approach enables rapid deployment, real-time visualization of surface mixing, and high-resolution orthomosaics that, together with benthic time series, reveal delayed transport, retention, and offshore dispersal of SGD across the reef.
This data project provides all primary data and code used in the manuscript submitted to PLOS ONE, enabling users to reproduce thermal-orthomosaic processing, integrate with in situ records, and apply analysis tools to detect temporal lags in time series and validate correspondence between sUAS-derived and in situ measurements.
The data project includes: 
- README — Inventory and metadata for all CSV and GeoTIFF files (units, CRS, timestamps, sensor IDs).  
- Thermal orthomosaics (GeoTIFF) — All mosaics used in the manuscript, exported as grayscale index GeoTIFFs (WGS84 / EPSG:4326) produced with PIX4Dmapper Desktop v4.9.  
- In situ validation data — YSI-derived salinity and temperature and inorganic nutrient measurements used in the manuscript’s statistical analyses.  
- Benthic time series — Raw benthic salinity and temperature records with timestamps and sensor IDs.  
- R code to: convert TIFFs to rasters, reproject to WGS84, and overlay thermal orthomosaics on Esri World Imagery (for on-screen visualization), validate drone-derived temperatures against in situ measurements, and detect temporal lags in benthic time series (cross-correlation) and groundwater retention (autocorrelation).