Groundwater Dependent Ecosystem (GDE) protection is increasingly being recognized as essential for the sustainable management and allocation of water resources. GDE services are crucial for human well-being and for a variety of flora and fauna. However, the conservation of GDEs is only possible if knowledge about their location and extent is available. Several studies have focused on the identification of GDEs at specific locations using ground-based measurements. However, recent progress in remote sensing technologies and their integration with Geographic Information Systems (GIS) has provided alternative ways to map GDEs at a much larger spatial extent. This paper presents a review of the geospatial methods that have been used to map and delineate GDEs at spatial different extents. Additionally, a summary of the satellite sensors useful for identification of GDEs and the integration of remote sensing data with ground-based measurements in the process of mapping GDEs is presented.

Coral reefs are among the most biologically diverse ecosystems on Earth. In the last few decades, a combination of stressors has produced significant declines in reef expanse, with declining reef health attributed largely to thermal stresses. We investigated the correspondence between time-series satellite remote sensing-based sea surface temperature (SST) datasets and ocean temperature monitored in situ at depth in coral reefs near La Parguera, Puerto Rico. In situ temperature data were collected for Cayo Enrique and Cayo Mario, San Cristobal, and Margarita Reef. The three satellite-based SST datasets evaluated were NOAA’s Coral Reef Watch (CoralTemp), the UK Meteorological Office’s Operational SST and Sea Ice Analysis (OSTIA), and NASA’s Jet Propulsion Laboratory (G1SST). All three satellite-based SST datasets assessed displayed a strong positive correlation (>0.91) with the in situ temperature measurements. However, all SST datasets underestimated the temperature, compared with the in situ measurements. A linear regression model using the SST datasets as the predictor for the in situ measurements produced an overall offset of ~1 °C for all three SST datasets. These results support the use of all three SST datasets, after offset correction, to represent the temperature regime at the depth of the corals in La Parguera, Puerto Rico.

The use of passive satellite sensor data in shallow waters is complicated by the combined atmospheric, water, and bottom signals. Accurate determination of water depth is important for monitoring underwater topography and detection of moved sediments and in support of navigation. A Worldview 2 (WV2) image was used to develop high-resolution bathymetric maps (four meters) that were validated using bathymetry from an active sensor Light Detection and Ranging (LiDAR). The influence of atmospheric corrections in depth retrievals was evaluated using the Dark Substract, Fast Line-of-Sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) and the Cloud Shadow Approach (CSA) atmospheric corrections. The CSA combined with a simple band ratio (Band2/Band3) provided the best performance, where it explained 82% of model values. The WV2 depth model was validated at another site within the image, where it successfully retrieved depth values with a coefficient of determination (r²) of 0.90 for all the depth values sampled, and an r² of 0.70, for a depth range to 20 m. The WV2 bands in the visible region were useful for testing different band combinations to derive bathymetry that, when combined with a robust atmospheric correction, provided depth retrievals even in areas with variable bottom composition and near the limits of detection.

The coloration of tropical reef corals is mainly due to their association with photosynthetic dinoflagellates commonly known as zooxanthellae. Combining High Performance Liquid Chromatography (HPLC), spectroscopy and derivative analysis we provide a novel approach to discriminate between the Caribbean shallow-water corals Acropora cervicornis and Porites porites based on their associated pigments. To the best of our knowledge, this is the first time that the total array of pigments found within the coral holobiont is reported. A total of 20 different pigments were identified including chlorophylls, carotenes and xanthophylls. Of these, eleven pigments were common to both species, eight were present only in A. cervicornis, and three were present only in P. porites. Given that these corals are living in similar physical conditions, we hypothesize that this pigment composition difference is likely a consequence of harboring different zooxanthellae clades with a possible influence of endolithic green or brown algae. We tested the effect of this difference in pigments on the reflectance spectra of both species. An important outcome was the correlation of total pigment concentration with coral reflectance spectra up to a 97% confidence level. Derivative analysis of the reflectance curves showed particular differences between species at wavelengths where several chlorophylls, carotenes and xanthophylls absorb. Within species variability of spectral features was not significant while interspecies variability was highly significant. We recognize that the detection of such differences with actual airborne or satellite remote sensors is extremely difficult. Nonetheless, based on our results, the combination of these techniques (HPLC, spectroscopy and derivative analysis) can be used as a robust approach for the development of a site specific spectral library for the identification of shallow-water coral species. Studies (Torres-Pérez, NASA Postdoctoral Program) are currently underway to further apply this approach to other Caribbean benthic coral reef features. The data will be used with planned and future airborne and satellite studies of the site and for algorithm development to advance the use of future airborne and satellite instrument capabilities (NASA PRISM and HyspIRI) for discrimination of coral reef benthic composition.