Hernández-López, William J.

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    Benthic habitat mapping and bio-optical characterization La Parguera Marine Reserve using passive and active remote sensing data
    (2015) Hernández-López, William J.; Armstrong, Roy A.; College of Arts and Sciences - Sciences; Gilbes Santaella, Fernando; García Sais, Jorge; Clemente-Colón, Pablo; Otero, Ernesto; Department of Marine Sciences; Grove, Kurt A.
    Remote sensing techniques are widely useful in the field of oceanography and provide a better understanding of the dynamics of ocean circulation, in monitoring climate change, for navigation and fisheries management, and also help to improve models for weather and climate predictions. Also, information from satellites and airborne sensors can be used to evaluate constituents of natural waters, their optical properties, bottom depth and type, and classification of benthic features in shallow coastal environments. This study addressed the combined used of imagery from passive and active sensors, and field optical data, in an algorithm development for bio-optical characterization and benthic habitat mapping in La Parguera Marine Reserve. High-resolution bathymetry from passive sensors was obtained from a Worldview 2 (WV2) image at a significant spatial resolution (4 meters) and was validated using bathymetric data from an active sensor (LiDAR). An additional analysis was done that evaluated the influence of atmospheric corrections in depth retrievals. The Cloud Shadow Approach (CSA), using a simple band ratio (Band2/Band3) provided the best atmospheric correction with a second order polynomial equation (r2 = 0.82). This WV2 depth model was evaluated at another site within the image where it successfully retrieved depth values (r2 = 0.90) proving that high-resolution bathymetry can be obtained when combined with a robust atmospheric correction, even in areas with variable bottom composition. The Airborne Visible Infrared Image Spectrometer (AVIRIS) and WorldView-2 (WV2) sensors were used to derive water optical properties, combined with water depth from LiDAR data to perform a water column correction using Lee’s semi-analytical algorithm, and to determine the optical bottom albedo. The values of image-derived absorption (p=0.05, r2=0.90) and Kd (p=0.05, r2=0.96) exhibited a strong correlation when compared with in situ values. A strong inverse relationship was found between distance from shore to increasing values of absorption (p=0.07, r2=0.71) and this factor explained about 71% of the variation in absorption values for the time-series. For the AVIRIS image, bottom albedo values for sand, seagrass, and coral-gorgonians were in good agreement with in situ values for these substrates in both spectral shape and intensity, spectral absorption and reflectance features were only present after the water column correction. LiDAR reflectivity was highly correlated to bottom albedo images from AVIRIS (r2 = 0.79) and WV2 (r2 = 0.79), and this correlation was further improved by removing the depth influence from the LiDAR reflectivity (AVIRIS, r2 = 0.95; WV2, (r2 = 0.94). High-resolution benthic habitat maps were created from AVIRIS and WV2 modeled bottom albedo products from pre-processed imagery (atmospheric and water column corrected) for La Parguera Reserve. An ISODATA classification was performed and the segmented images were classified as coral reefs, seagrass, hardbottom, mixed sand/hardbottom/coral, mud, sand, and sand with benthic algae. The overall accuracy (AVIRIS = 63.55%, WV2 = 64.81%), kappa coefficient (AVIRIS = 55 %, WV2 = 57%), and the tau coefficient (AVIRIS = 59%, WV2 = 60%) were evaluated. No major class differences were found between the AVIRIS and WV2 classification totals, except for coral reefs and sand, where the reduction in coral reefs class totals could be attributed to temporal differences in the images depicting changes in the coral reefs distribution within the reserve. A major contribution of this study was the creation of the first benthic habitat map for La Parguera Reserve that: 1) provided multi/hyperspectral information at this spatial scale (4 square meters), 2) covered the extent of the reserve, and 3) provided a baseline for future development of benthic habitat studies using an objective classification scheme.