Scaling up benthic primary productivity estimates in a large intertidal estuary using remote sensing.

As two main primary producers in temperate intertidal regions, seagrass and microphytobenthos (MPB) support estuarine ecosystem functions in multiple ways including stabilizing food webs and regulating sediment resuspension among others. Monitoring estuary productivity at large scales can inform ecosystem scale responses to environmental stressors (climate change, pollution and habitat degradation). Here we use a case study to show how Sentinel-2 data can be used to estimate estuary-wide emerged and submerged gross primary productivity (GPP) on intertidal flats by coupling a new machine learning model to map seagrass and unvegetated habitats with literature-derived photosynthesis-irradiance (P - I) relationships.

Growth conditions impact particulate absorption and pigment concentrations in two common bloom forming cyanobacterial species.

Remote sensing using satellite imagery has been promoted as a method to broaden the scale and frequency of cyanobacterial monitoring. This relies on the ability to establish relationships between the reflectance spectra of water bodies and the abundance of cyanobacteria. A challenge to achieving this comes from a limited understanding of the extent to which the optical properties of cyanobacteria vary according to their physiological state and growth environment.

GLORIA - A globally representative hyperspectral in situ dataset for optical sensing of water quality.

The development of algorithms for remote sensing of water quality (RSWQ) requires a large amount of in situ data to account for the bio-geo-optical diversity of inland and coastal waters. The GLObal Reflectance community dataset for Imaging and optical sensing of Aquatic environments (GLORIA) includes 7,572 curated hyperspectral remote sensing reflectance measurements at 1 nm intervals within the 350 to 900 nm wavelength range. In addition, at least one co-located water quality measurement of chlorophyll a, total suspended solids, absorption by dissolved substances, and Secchi depth, is provided.

Dataset of five years of and satellite derived chlorophyll concentrations and its spatiotemporal variability in the Rotorua Te Arawa Lakes, New Zealand.

Horizontal patchiness of water quality attributes in lakes substantially influences the ability to accurately determine an average condition of a lake from traditional in situ sampling. Monitoring programmes for lake water quality often rely on water samples from one or few locations but the assumption of representativeness is seldomly tested. Satellite observations can support environmental monitoring by detecting horizontal variability of water quality attributes over entire lakes.