Remote Sensing Field Validation of Water Quality in Conway Lake

In June 2024, Spectral Evolution joined local researchers from the University of New Hampshire and citizen scientists to collect water quality data on Conway Lake in New Hampshire. This fieldwork provided an opportunity to gather validation data in support of a simultaneous Landsat-8 satellite flyover. Our goal is to

demonstrate the value of field collected reflectance data while contributing to critical local water monitoring efforts. For this kind of analysis targeting vegetation and algae we sent the PSR-1100f which is a hyperspectral spectroradiometer covering the range of 320 to 1100nm. Measurements were taken at nadir with an 8-degree lens off the side of a small boat using a boom and the pistol grip fiber holder.

Satellite remote sensing is an essential tool for monitoring water quality. It enables researchers to assess broad areas, offering valuable information for communities that rely on water for public health, environmental protection, fishing, and tourism. Satellite data comes with limitations most systems are constrained in spectral, spatial, and temporal resolution. This is where ground-based validation becomes crucial. To compare the data pixel extraction was performed at each sample site for comparison with simultaneous water sampling and reflectance spectra collection.

Field reflectance measurements allow scientists to verify what satellites observe by providing hyperspectral high-resolution data directly from the field site. While laboratory analysis of water samples gives excellent insights, it is often costly and slow limiting the number of samples. Field reflectance enhances the

ability to interpret satellite imagery and increases confidence in broader-scale remote sensing analyses.

In this study, we analyzed a Landsat-8 image alongside field-collected chlorophyll concentration data and water reflectance measurements. We calculated a Normalized Difference Chlorophyll Index (NDCI) for the satellite imagery, as well as NDVI using the narrowband index method described by Gitelson and Merzlyak (1994). The satellite imagery provided an estimate of algae presence in Conway Lake.

When comparing all datasets, we observed strong agreement across the different resolutions. Field reflectance data correlated closely with chlorophyll concentrations collected on the ground with an R2= .912, indicating high accuracy at those locations.

This correlation was notably stronger than between the satellite-derived values and chlorophyll counts, which showed less agreement at R2=.873.

This brief analysis supports confidence in the satellite imagery, suggesting that Conway Lake currently has relatively low algal biomass, with most growth concentrated in the central areas. The northern inflow appears to have lower chlorophyll content, indicating clearer water in that region.

In summary, Spectral Evolution provides high-quality UV-VIS-NIR spectroradiometers that play a critical role in field validation and support meaningful advancements in water quality research. We encourage the use of similar methodologies in future studies as well as incorporating algae spectral library comparison for speciation of microbiology. Consider Spectral Evolution instruments for your water quality remote sensing needs.