PHOTOGRAMMETRIC AND FLUORESCENCE SOLUTIONS FOR MONITORING OF HABITAT FORMING ORGANISMS
Keywords: underwater photogrammetry, high-resolution 3D reconstruction, marine ecosystems, geometric monitoring, health status monitoring, fluorescence imagery
Abstract. The development and testing of innovative technologies and automated data analysis methodologies offer tools for the monitoring of complex marine ecosystems and the direct and indirect effects of climate change on natural heritage. Photogrammetric methods allow precise mapping of the underwater landscape as well as detailed three-dimensional (3D) reconstruction of marine structures, improving the study of complex marine ecosystems. Moreover, fluorescence analyses can provide critical information about the health status of marine organisms. Analysing the variations in their self-fluorescence, allow for early detect changes in their physiological state. These applications provide very useful data to evaluate the health state of biodiversity-rich 3D biogenic structures and make measurements of fine-scale changes, with greater precision than existing methodologies. This contribution shows a multidisciplinary approach to the design, development, and implementation of a technological solution based on the above-mentioned optical measuring systems. Such a system is characterized by a reflex camera, LED-based light sources, and filters to allow the analysis of the self-fluorescence signal. The proposed solution aspires to improve the standardization of monitoring plans through non-destructive fine-scale accurate data collection for image analysis and multi-temporal comparisons, providing challenging stepping-stones for habitat-forming anthozoan management and restoration activities. Initial results of tests carried out in controlled conditions are shown. The photogrammetric approach resulted in 3D reconstructions that allow the monitoring of deformations at millimetre scale. The fluorimetry methodology allowed to obtain high-resolution images with great repeatability, which enabled the identification of stressful status even in absence of geometric deformations. The proposed approaches and obtained results are discussed, together with potential issues related to their implementation in a real-world context adopting remotely operative vehicles.