Coral reef habitat mapping in the Red Sea (Hurghada, Egypt) based on remote sensing

Remote sensing can give information about the configuration and composition of coral reefs, about the biophysical parameters of the seas and oceans in which they occur and about the changes over time of these elements. This paper deals with the classification of a Landsat7 ETM+ data set in order to identify the different bottom types (macro-algae, coral, sea grass and sand) occurring on the reefs offshore Hurghada, Egypt. Before classification, the radiance values received at sensor are corrected for atmospheric and water column effects. ‘Depth-invariant bottom indices’ are calculated and form the basis for classification. Besides the bottom type as an ecological classification, also a geomorphological classification is made. After contextual editing of the ecological classification, both results are combined into an open-ended hierarchical classification scheme. An in-depth accuracy assessment still needs to be undertaken but a mean accuracy between 47% and 83% is to be expected

A diver-operated hyperspectral imaging and topographic surveying system for automated mapping of benthic habitats

We developed a novel integrated technology for diver-operated surveying of shallow marine ecosystems. The HyperDiver system captures rich multifaceted data in each transect: hyperspectral and color imagery, topographic profiles, incident irradiance and water chemistry at a rate of 15-30 m(2) per minute. From surveys in a coral reef following standard diver protocols, we show how the rich optical detail can be leveraged to generate photopigment abundance and benthic composition maps. We applied machine learning techniques, with a minor annotation effort (<2% of pixels), to automatically generate cm-scale benthic habitat maps of high taxonomic resolution and accuracy (93-97%). The ability to efficiently map benthic composition, photopigment densities and rugosity at reef scales is a compelling contribution to modernize reef monitoring. Seafloor-level hyperspectral images can be used for automated mapping, avoiding operator bias in the analysis and deliver the degree of detail necessary for standardized environmental monitoring. The technique can deliver fast, objective and economic reef survey results, making it a valuable tool for coastal managers and reef ecologists. Underwater hyperspectral surveying shares the vantage point of the high spatial and taxonomic resolution restricted to field surveys, with analytical techniques of remote sensing and provides targeted validation for aerial monitoring

The role of integrated information acquisition and management in the analysis of coastal ecosystem change

This book chapter represents a synthesis of the work which started in my PhD and which has been the conceptual basis for all of my research since 1993. The chapter presents a method for scientists and managers to use for selecting the type of remotely sensed data to use to meet their information needs associated with a mapping, monitoring or modelling application. The work draws on results from several of my ARC projects, CRC Rainforest and Coastal projects and theses of P.Scarth , K.Joyce and C.Roelfsema

Coastal and Inland Aquatic Data Products for the Hyperspectral Infrared Imager (HyspIRI)

The HyspIRI Aquatic Studies Group (HASG) has developed a conceptual list of data products for the HyspIRI mission to support aquatic remote sensing of coastal and inland waters. These data products were based on mission capabilities, characteristics, and expected performance. The topic of coastal and inland water remote sensing is very broad. Thus, this report focuses on aquatic data products to keep the scope of this document manageable. The HyspIRI mission requirements already include the global production of surface reflectance and temperature. Atmospheric correction and surface temperature algorithms, which are critical to aquatic remote sensing, are covered in other mission documents. Hence, these algorithms and their products were not evaluated in this report. In addition, terrestrial products (e.g., land use land cover, dune vegetation, and beach replenishment) were not considered. It is recognized that coastal studies are inherently interdisciplinary across aquatic and terrestrial disciplines. However, products supporting the latter are expected to already be evaluated by other components of the mission. The coastal and inland water data products that were identified by the HASG, covered six major environmental and ecological areas for scientific research and applications: wetlands, shoreline processes, the water surface, the water column, bathymetry and benthic cover types. Accordingly, each candidate product was evaluated for feasibility based on the HyspIRI mission characteristics and whether it was unique and relevant to the HyspIRI science objectives

Enhancing the detection and classification of coral reef and associated benthic habitats: A hyperspectral remote sensing approach

Coral reefs and associated benthic habitats are heterogeneous in nature. A remote sensor designed to discriminate these environments requires a high number of narrow, properly placed bands which are not currently available in existing satellite sensors. Optical hyperspectral sensors mounted on aerial platforms seem to be appropriate for overcoming the lack of both high spectral and spatial resolution of satellite sensors. This research presents results of an innovative coral reef application by such a sensor. Using hyperspectral Airborne Imaging Spectroradiometer for Applications (AISA) Eagle data, the approach presented solves the confounding influence of water column attenuation on substrate reflectance on a per-pixel basis. The hyperspectral imagery was used in band ratio algorithms to derive water depth and water column optical properties (e.g., absorption and backscattering coefficients). The water column correction technique produced a bottom albedo image which revealed that the dark regions comprised of sea grasses and benthic algae had albedo values ≈15%, whereas sand- and coral-dominated areas had albedos \u3e30% and ≈15–35%, respectively. The retrieved bottom albedo image was then used to classify the benthos, generating a detailed map of benthic habitats, followed by accuracy assessment

Using RapidEye high spatial resolution imagery in mapping shallow coastal water benthic habitats

http://www.ester.ee/record=b448589