Application of Hyperspectral Imaging to Underwater Habitat Mapping, Southern Adriatic Sea

Quantifying pigment content in crustose coralline algae using hyperspectral imaging: A case study with Tethysphytum antarcticum (Ross Sea, Antarctica)

Crustose coralline algae (CCA) are a highly diverse group of habitat-forming, calcifying red macroalgae (Rhodophyta) with unique adaptations to diverse irradiance regimes. A distinctive CCA phenotype adaptation, which allows them to maximize photosynthetic performance in low light, is their content of a specific group of light-harvesting pigments called phycobilins. In this study, we assessed the potential of noninvasive hyperspectral imaging (HSI) in the visible spectrum (400-800 nm) to describe the phenotypic variability in phycobilin content of an Antarctic coralline, Tethysphytum antarcticum (Hapalidiales), from two distinct locations. We validated our measurements with pigment extractions and spectrophotometry analysis, in addition to DNA barcoding using the psbA marker. Targeted spectral indices were developed and correlated with phycobilin content using linear mixed models (R2 = 0.64-0.7). Once applied to the HSI, the models revealed the distinct phycoerythrin spatial distribution in the two site-specific CCA phenotypes, with thin and thick crusts, respectively. This study advances the capabilities of hyperspectral imaging as a tool to quantitatively study CCA pigmentation in relation to their phenotypic plasticity, which can be applied in laboratory studies and potentially in situ surveys using underwater hyperspectral imaging systems.

Pixelwise immersion factor calibration for underwater hyperspectral imaging instruments

In situ spectral reflectance initially captured at high spatial resolution with underwater hyperspectral imaging (UHI) is effective for classification and quantification in oceanic biogeochemical studies; however, the measured spectral radiance is rarely used as an absolute quantity due to challenges in calibration of UHI instruments. In this paper, a commercial UHI instrument was calibrated for radiometric flat field response and pixelwise immersion effect to support in situ measurement of absolute spectral radiance. The radiometric and immersion factor calibrations of the UHI instrument were evaluated quantitatively through comparative experiments with a spectroradiometer and a spectrometer. Results show that the immersion factor of the center pixel of the tested UHI instrument was 1.763 in pure water at 600 nm, and the averaged difference in immersion factor between the center and edge pixel of the UHI instrument in the visible light band was only 1∼3% across its half angle field of view of 35° in air. The new calibration coefficients were further used to calculate the spectral radiance of transmitted sunlight through ice algae clusters in sea ice measured by the UHI instrument during an Arctic under-ice bio-optical survey.

Chitons from Deep-Water Mollusk-Rich Deposits in the Southwestern Adriatic Sea (Mollusca, Polyplacophora)

Sea-bottom sampling at bathyal depths off the Apulian margin (southwestern Adriatic Sea) recovered shelly biogenic sediments rich in mollusk remains. Noteworthy is the occurrence in such taphocoenoses of loose chiton valves, rarely reported in these environments. We identified four species of Polyplacophora, Leptochiton asellus (Gmelin, 1791), Belknapchiton alveolus (M. Sars MS, Lovén, 1846), Hanleya hanleyi (Bean in Thorpe, 1844), and the new species Leptochiton antondohrni. L. asellus (Gmelin, 1791) and B. alveolus are primarily of North Atlantic (boreo-celtic) affinity and thus considered to belong to last Pleistocene glacial assemblages, whose presence in the study area has long been ascertained. The same could be true for the valves of H. hanleyi and, possibly, Leptochiton antondohrni n. sp. Finally, we updated the list of mollusks found thus far in the deep-sea taphocoenoses of this area, including new records of North Atlantic-type taxa considered at present extinct in the Mediterranean basin.

A Tunable Hyperspectral Imager for Detection and Quantification of Marine Biofouling on Coated Surfaces

Fouling control coatings (FCCs) are used to prevent the accumulation of marine biofouling on, e.g., ship hulls, which causes increased fuel consumption and the global spread of non-indigenous species. The standards for performance evaluations of FCCs rely on visual inspections, which induce a degree of subjectivity. The use of RGB images for objective evaluations has already received interest from several authors, but the limited acquired information restricts detailed analyses class-wise. This study demonstrates that hyperspectral imaging (HSI) expands the specificity of biofouling assessments of FCCs by capturing distinguishing spectral features. We developed a staring-type hyperspectral imager using a liquid crystal tunable filter as the wavelength selective element. A novel light-emitting diode illumination system with high and uniform irradiance was designed to compensate for the low-filter transmittance. A spectral library was created from reflectance-calibrated optical signatures of representative biofouling species and coated panels. We trained a neural network on the annotated library to assign a class to each pixel. The model was evaluated on an artificially generated target, and global accuracy of 95% was estimated. The classifier was tested on coated panels (exposed at the CoaST Maritime Test Centre) with visible intergrown biofouling. The segmentation results were used to determine the coverage percentage per class. Although a detailed taxonomic description might be complex due to spectral similarities among groups, these results demonstrate the feasibility of HSI for repeatable and quantifiable biofouling detection on coated surfaces.

Exploring time series of hyperspectral images for cold water coral stress response analysis

Hyperspectral imaging (HSI) is a promising technology for environmental monitoring with a lot of undeveloped potential due to the high dimensionality and complexity of the data. If temporal effects are studied, such as in a monitoring context, the analysis becomes more challenging as time is added to the dimensions of space (image coordinates) and wavelengths. We conducted a series of laboratory experiments to investigate the impact of different stressor exposure patterns on the spectrum of the cold water coral Desmophyllum pertusum. 65 coral samples were divided into 12 groups, each group being exposed to different types and levels of particles. Hyperspectral images of the coral samples were collected at four time points from prior to exposure to 6 weeks after exposure. To investigate the relationships between the corals’ spectral signatures and controlled experimental parameters, a new software tool for interactive visual exploration was developed and applied, the HypIX (Hyperspectral Image eXplorer) web tool. HypIX combines principles from exploratory data analysis, information visualization and machine learning-based dimension reduction. This combination enables users to select regions of interest (ROI) in all dimensions (2D space, time point and spectrum) for a flexible integrated inspection. We propose two HypIX workflows to find relationships in time series of hyperspectral datasets, namely morphology-based filtering workflow and embedded driven response analysis workflow. With these HypIX workflows three users identified different temporal and spatial patterns in the spectrum of corals exposed to different particle stressor conditions. Corals exposed to particles tended to have a larger change rate than control corals, which was evident as a shifted spectrum. The responses, however, were not uniform for coral samples undergoing the same exposure treatments, indicating individual tolerance levels. We also observed a good inter-observer agreement between the three HyPIX users, indicating that the proposed workflow can be applied to obtain reproducible HSI analysis results.

Assessment of agricultural prospects in relation to land use change and population pressure on a spatiotemporal framework

The urbanisation process moves quickly in emerging nations like India and Bangladesh, transforming natural landscapes into unsustainable landscapes. Consequently, growing development has had a significant impact on agricultural land as a natural environment. Moreover, there is a scarcity of research on fragmentation probability modelling in the extant literature. Thus, by combining random forest (RF) and bagging with the datasets which are multi-temporal in a GIS framework, the probability of fragmentation of LULC at Jangipur subdivision in India and Bangladesh can be modelled. Parallelepiped, Mohalnobis distance, support vector machines (SVM), spectral angle mapper (SAM), and artificial neural networks (ANN) classifiers were used for LULC classification, where SVM (Kappa coefficient: 0.87) surpassed other classifiers. The LULC maps for 1990, 2000, 2010, and 2020 were created using the best classifier (SVM). During this time, the built-up area grew from 23.769 to 158.125 km². Then, using an ANN-based cellular automata model, the future LULC map for 2030 was predicted (CA-ANN). In 2030, the built-up area would be 201.58 km². Then the matrices of class and landscape were taken out of the LULC maps utilising FRAGSTAT software and included the patch number (NP), largest patch index (LPI), edge density (ED), contagion index (percentage) (CONTAG), perimeter and area (P/A), aggregation index (AI), landscape percentage (PLAND), the area of class (CA), patch density (PD), edge in total (TE), total core area (TCA), and largest shape index (LSI). The validation results revealed that bagging (0.915 = AUC) and RF (0.874 = AUC) are capable of assessing fragmentation probability, with the bagging model having the greatest precision level of the two. Almost 20% of the total LULC was in a high and very high zone of fragmentation vulnerability, necessitating the use of direct measures to safeguard it. As a result, adequate LULC management is required.

Underwater hyperspectral imaging system with dual-scanning mode

As a kind of underwater detecting technology, hyperspectral imaging technology has been well applied in many areas. But the systems usually have a large volume, and it is hard to mount them on different platforms because the external scanning mechanisms are needed for scanning imaging. To overcome these disadvantages, an underwater hyperspectral imaging system that achieves scanning imaging through moving the objective lens is designed. The design of the optical system and internal scanning and focusing structure were completed. According to the design result, the system is assembled and tested. The imaging quality of the whole system is good, and the obtained spectrum of different targets can be distinguished. The system has a good underwater detection capability, which can provide a new feasible technical scheme for underwater detection.

Are the seafloors of marine protected areas sinks for marine litter? Composition and spatial distribution in Cabrera National Park

The seafloors of oceans and seas are becoming major sinks for marine litter (ML) at a global scale and especially within the Mediterranean Sea. Within global oceans and seas, Marine Protected Areas (MPAs) have been established to protect and conserve marine habitats and increase marine biodiversity. In this study, extensive coastal shallow scuba diving surveys were conducted in 2019 and 2020 to identify the distribution of ML in the MPA of Cabrera Marine-Terrestrial National Park (Cabrera MPA) in the Balearic Islands. Approximately 900 items weighing 70.1 kg were collected throughout the MPA during the underwater surveys. Glass bottles, including pieces (25-30%) and glass or ceramic fragments >2.5 cm (8-19%) were the most common identified items followed by plastic food containers and plastic bags (~8%). Overall, 75% of the abundance of collected ML was observed during the first year. In terms of the protection status of the different locations, similar abundances of ML were found in public access areas and no-take areas. Additionally, no significant differences were identified according to location indicating that ML on the seafloor was homogeneous within the studied shallow coastal areas. Overall, the results indicate that Cabrera MPA is a hotspot for ML and mitigation actions and measures, such as annual cleaning efforts, can help to prevent and minimize ML accumulation on the seafloor.

Preliminary Classification of Selected Farmland Habitats in Ireland Using Deep Neural Networks

Ireland has a wide variety of farmlands that includes arable fields, grassland, hedgerows, streams, lakes, rivers, and native woodlands. Traditional methods of habitat identification rely on field surveys, which are resource intensive, therefore there is a strong need for digital methods to improve the speed and efficiency of identification and differentiation of farmland habitats. This is challenging because of the large number of subcategories having nearly indistinguishable features within the habitat classes. Heterogeneity among sites within the same habitat class is another problem. Therefore, this research work presents a preliminary technique for accurate farmland classification using stacked ensemble deep convolutional neural networks (DNNs). The proposed approach has been validated on a high-resolution dataset collected using drones. The image samples were manually labelled by the experts in the area before providing them to the DNNs for training purposes. Three pre-trained DNNs customized using the transfer learning approach are used as the base learners. The predicted features derived from the base learners were then used to train a DNN based meta-learner to achieve high classification rates. We analyse the obtained results in terms of convergence rate, confusion matrices, and ROC curves. This is a preliminary work and further research is needed to establish a standard technique.

Technical Non-Invasive Study of an 18th Century Novo-Hispanic Panel Painting

Purísima Concepción, a large-format and unusual panel painting attributed to the 18th century, based on style and the common aspect of the visual tradition of the Virgin Mary found in the Viceroyalty of New Spain, is sheltered at the Museo Ex-convento San Agustín Acolman-INAH, México, an institution opened in late 1920, and one of the oldest museums in México. In this work, we present the material characterization of the surface layer of the painting by means of a non-invasive methodology, resulting from the combination of imaging and spectroscopic techniques. Analysis of hyperspectral images employing methods such as spectral angle mapper and principal component analysis allowed us to describe spatial distribution of the pigments and manufacturing methods, while XRF and FORS allowed us to record the complex and diverse color palette employed to achieve effects such as brightness, hue, saturation, and even the covering power of this painting.

Underwater Hyperspectral Imaging (UHI): A Review of Systems and Applications for Proximal Seafloor Ecosystem Studies

Marine ecosystem monitoring requires observations of its attributes at different spatial and temporal scales that traditional sampling methods (e.g., RGB imaging, sediment cores) struggle to efficiently provide. Proximal optical sensing methods can fill this observational gap by providing observations of, and tracking changes in, the functional features of marine ecosystems non-invasively. Underwater hyperspectral imaging (UHI) employed in proximity to the seafloor has shown a further potential to monitor pigmentation in benthic and sympagic phototrophic organisms at small spatial scales (mm–cm) and for the identification of minerals and taxa through their finely resolved spectral signatures. Despite the increasing number of studies applying UHI, a review of its applications, capabilities, and challenges for seafloor ecosystem research is overdue. In this review, we first detail how the limited band availability inherent to standard underwater cameras has led to a data analysis “bottleneck” in seafloor ecosystem research, in part due to the widespread implementation of underwater imaging platforms (e.g., remotely operated vehicles, time-lapse stations, towed cameras) that can acquire large image datasets. We discuss how hyperspectral technology brings unique opportunities to address the known limitations of RGB cameras for surveying marine environments. The review concludes by comparing how different studies harness the capacities of hyperspectral imaging, the types of methods required to validate observations, and the current challenges for accurate and replicable UHI research.

A Perspective for Best Governance of the Bari Canyon Deep-Sea Ecosystems

There is growing awareness of the impact of fishery activities on fragile and vulnerable deep-sea ecosystems, stimulating actions devoted to their protection and best management by national and international organizations. The Bari Canyon in the Adriatic Sea represents a good case study of this, since it hosts vulnerable ecosystems, threatened species, as well as valuable commercial species, but virtually lacks substantial management plans for the sustainable use of resources. This study documents the high level of biodiversity of the Bari Canyon and the impact of human activities by analyzing remotely operated vehicle surveys and benthic lander deployments. An integrated socio-economic study provides information on fishing pressure in the Bari Canyon and in the surrounding areas. Finally, measures of conservation, protection, and management are discussed and suggested for this remarkable site in the context of the deep Mediterranean Sea.

Size/Age Models for Monitoring of the Pink Sea Fan Eunicella verrucosa (Cnidaria: Alcyonacea) and a Case Study Application

The pink sea fan Eunicella verrucosa is a habitat-forming octocoral living in the East Atlantic and in the Mediterranean Sea where, under proper circumstances, it can form large populations known as coral forests. Although these coral forests represent vulnerable marine ecosystems of great importance, these habitats are still poorly known, and their monitoring is almost non-existent to date. For this reason, we compared two different models to infer the age of E. verrucosa based on nondestructive measurements of the colonies’ size, in order to highlight strengths and weaknesses of the existing tools for a potential application in long-term monitoring. We also applied the two models on a case-study population recently found in the northwest Mediterranean Sea. Our results showed which model was more reliable from a biological point of view, considering both its structure and the results obtained on the case study. However, this model uses solely the height of the colonies as proxy to infer the age, while the total branch fan surface area could represent a more appropriate biometric parameter to monitor the size and the growth of E. verrucosa.

Underwater Hyperspectral Imaging Technology and Its Applications for Detecting and Mapping the Seafloor: A Review

Common methods of ocean remote sensing and seafloor surveying are mainly carried out by airborne and spaceborne hyperspectral imagers. However, the water column hinders the propagation of sunlight to deeper areas, thus limiting the scope of observation. As an emerging technology, underwater hyperspectral imaging (UHI) is an extension of hyperspectral imaging technology in air conditions, and is undergoing rapid development for applications in shallow and deep-sea environments. It is a close-range, high-resolution approach for detecting and mapping the seafloor. In this paper, we focus on the concepts of UHI technology, covering imaging systems and the correction methods of eliminating the water column’s influence. The current applications of UHI, such as deep-sea mineral exploration, benthic habitat mapping, and underwater archaeology, are highlighted to show the potential of this technology. This review can provide an introduction and overview for those working in the field and offer a reference for those searching for literature on UHI technology.

Seven Good Reasons for Integrating Terrestrial and Marine Spatial Datasets in Changing Environments

A comprehensive understanding of environmental changes taking place in coastal regions relies on accurate integration of both terrestrial and submerged geo-environmental datasets. However, this practice is hardly implemented because of the high (or even prohibitive) survey costs required for submerged areas and the frequent low accessibility of shallow areas. In addition, geoscientists are used to working on land or at sea independently, making the integration even more challenging. Undoubtedly new methods and techniques of offshore investigation adopted over the last 50 years and the latest advances in computer vision have played a crucial role in allowing a seamless combination of terrestrial and marine data. Although efforts towards an innovative integration of geo-environmental data from above to underwater are still in their infancy, we have identified seven topics for which this integration could be of tremendous benefit for environmental research: (1) geomorphological mapping; (2) Late-Quaternary changes of coastal landscapes; (3) geoarchaeology; (4) geoheritage and geodiversity; (5) geohazards; (6) marine and landscape ecology; and (7) coastal planning and management. Our review indicates that the realization of seamless DTMs appears to be the basic condition to operate a comprehensive integration of marine and terrestrial data sets, so far exhaustively achieved in very few case studies. Technology and interdisciplinarity will be therefore critical for the development of a holistic approach to understand our changing environments and design appropriate management measures accordingly.

Seabed Mapping: A Brief History from Meaningful Words

Over the last few centuries, mapping the ocean seabed has been a major challenge for marine geoscientists. Knowledge of seabed bathymetry and morphology has significantly impacted our understanding of our planet dynamics. The history and scientific trends of seabed mapping can be assessed by data mining prior studies. Here, we have mined the scientific literature using the keyword “seabed mapping” to investigate and provide the evolution of mapping methods and emphasize the main trends and challenges over the last 90 years. An increase in related scientific production was observed in the beginning of the 1970s, together with an increased interest in new mapping technologies. The last two decades have revealed major shift in ocean mapping. Besides the range of applications for seabed mapping, terms like habitat mapping and concepts of seabed classification and backscatter began to appear. This follows the trend of investments in research, science, and technology but is mainly related to national and international demands regarding defining that country’s exclusive economic zone, the interest in marine mineral and renewable energy resources, the need for spatial planning, and the scientific challenge of understanding climate variability. The future of seabed mapping brings high expectations, considering that this is one of the main research and development themes for the United Nations Decade of the Oceans. We may expect a new higher resolution ocean seafloor map that might be as influential as The Floor of the Oceans map.

Offshore Neopycnodonte Oyster Reefs in the Mediterranean Sea

Oysters are important ecosystem engineers best known to produce large bioconstructions at shallow depth, whilst offshore deep-subtidal oyster reefs are less widely known. Oyster reefs engineered by Neopycnodonte cochlear (family Gryphaeidae) occur at various sites in the Mediterranean Sea, between 40 and 130 m water depths. Remotely Operated Vehicle surveys provide new insights on this rather neglected reef types with respect to their shape, dimensions and associated biodiversity. We suggest that these little contemplated reefs should be taken in due consideration for protection.

An Under-Ice Hyperspectral and RGB Imaging System to Capture Fine-Scale Biophysical Properties of Sea Ice

Sea-ice biophysical properties are characterized by high spatio-temporal variability ranging from the meso- to the millimeter scale. Ice coring is a common yet coarse point sampling technique that struggles to capture such variability in a non-invasive manner. This hinders quantification and understanding of ice algae biomass patchiness and its complex interaction with some of its sea ice physical drivers. In response to these limitations, a novel under-ice sled system was designed to capture proxies of biomass together with 3D models of bottom topography of land-fast sea-ice. This system couples a pushbroom hyperspectral imaging (HI) sensor with a standard digital RGB camera and was trialed at Cape Evans, Antarctica. HI aims to quantify per-pixel chlorophyll-a content and other ice algae biological properties at the ice-water interface based on light transmitted through the ice. RGB imagery processed with digital photogrammetry aims to capture under-ice structure and topography. Results from a 20 m transect capturing a 0.61 m wide swath at sub-mm spatial resolution are presented. We outline the technical and logistical approach taken and provide recommendations for future deployments and developments of similar systems. A preliminary transect subsample was processed using both established and novel under-ice bio-optical indices (e.g., normalized difference indexes and the area normalized by the maximal band depth) and explorative analyses (e.g., principal component analyses) to establish proxies of algal biomass. This first deployment of HI and digital photogrammetry under-ice provides a proof-of-concept of a novel methodology capable of delivering non-invasive and highly resolved estimates of ice algal biomass in-situ, together with some of its environmental drivers. Nonetheless, various challenges and limitations remain before our method can be adopted across a range of sea-ice conditions. Our work concludes with suggested solutions to these challenges and proposes further method and system developments for future research.