• NEANIAS Underwater Research Community

A short sequence (5 sec) of underwater images in the wake of a clear water scour. The images show the bottom movements behind a pier on a single grain level. Hence, each moving grain is visible. The bed material consists of sand dm=1.x

The evolution of underwater photogrammetry allows to realize 3D models of submerged object and structures throughout the use of rapid and efficient procedures either in terms of data acquisition and data processing. These procedures are based on solutions that are applied using natural control points, signalized markers and tie points; the most common algorithms are based on Structure from Motion (SfM) approach. The limit of these applications is sometimes due to the final accuracy, especially when the goal is a centimeter level of accuracy. This accuracy should be necessary when dealing with a survey devoted to deformation control purposes. An example is the underwater photogrammetry for the determination of coral growth; it is effectively a movement or a deformation detection issue where the geometric change is almost at centimeter or few centimeters accuracy level. When dealing with deformation control applications, a geodetic network is essential to realize a stable and unambiguous reference frame through the accurate and permanent installation of Ground Control Points (GCPs). Such a network, indeed, permits a robust reference frame for the georeferencing of images blocks in the different époques of data acquisition. Therefore, the comparison among subsequent photogrammetric restitutions is based on homogeneous 3D models that have been oriented in the same absolute reference system. The photogrammetric survey is based on a methodological approach especially adapted to underwater biometry (like coral growth determination) and to underwater archaeology. The approach is suitable both for modeling objects of relatively reduced dimensions and for structures with a length of ten meters or more, such as coral barriers, wrecks and long walls. The paper describes underwater photogrammetric surveys on sites at different extensions, the geodetic GCPs reference network installation and measurements (distance and elevation difference observations) as well as preliminary results of the network adjustment. A brief description of image acquisition at a different scales and the resulting 3D model of first campaign are also shown.

Underwater 3D reconstruction techniques such as underwater photogrammetry are the latest trend in low cost survey techniques. Allowing for high resolution models to be fabricated using off-the-shelf digital cameras and editing software, this method in shallow water environments provide a welcome alternative to costly methods such as Lidar & Sonar. We discuss the method of using current low cost ROV’s as platforms forming the basis of underwater photogrammetry surveyance, providing speed and stability over the traditional use of divers. New technologies now available in the low cost market give the abilities for underwater vehicles to be tracked and positioned in real time using acoustic transponders in a network with known surface GPS. Such advances will enable photogrammetric models to be georeferenced which is of great aid to areas of research not limited to archaeological heritage and coral reefs studies.

Regular monitoring activities are important for assessing the influence of unfavourable factors on corals and tracking subsequent recovery or decline. Deep learning-based underwater photogrammetry provides a comprehensive solution for automatic large-scale and precise monitoring. It can quickly acquire a large range of underwater coral reef images, and extract information from these coral images through advanced image processing technology and deep learning methods. This procedure has three major components: (a) Generation of 3D models, (b) understanding of relevant corals in the images, and (c) tracking of those models over time and spatial change analysis. This paper focusses on issue (b), it applies five state-of-the-art neural networks to the semantic segmentation of coral images, compares their performance, and proposes a new coral semantic segmentation method. Finally, in order to quantitatively evaluate the performance of neural networks for semantic segmentation in these experiments, this paper uses mean class-wise Intersection over Union (mIoU), the most commonly used accuracy measure in semantic segmentation, as the standard metric. Meanwhile, considering that the coral boundary is very irregular and the evaluation index of IoU is not accurate enough, a new segmentation evaluation index based on boundary quality, Boundary IoU, is also used to evaluate the segmentation effect. The proposed trained network can accurately distinguish living from dead corals, which could reflect the health of the corals in the area of interest. The classification results show that we achieve state-of-the-art performance compared to other methods tested on the dataset provided in this paper on underwater coral images. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-2-2022 ISSN:2194-9042 ISSN:2194-9050

Underwater photogrammetry provides a means of generating high-resolution products such as dense point clouds, 3D models, and orthomosaics with centimetric scale resolutions. Underwater photogrammetric models can be used to monitor the growth and expansion of benthic communities, including the assessment of the conservation status of seagrass beds and their change over time (time lapse micro-bathymetry) with OBIA classifications (Object-Based Image Analysis). However, one of the most complex aspects of underwater photogrammetry is the accuracy of the 3D models for both the horizontal and vertical components used to estimate the surfaces and volumes of biomass. In this study, a photogrammetry-based micro-bathymetry approach was applied to monitor Posidonia oceanica restoration actions. A procedure for rectifying both the horizontal and vertical elevation data was developed using soundings from high-resolution multibeam bathymetry. Furthermore, a 3D trilateration technique was also tested to collect Ground Control Points (GCPs) together with reference scale bars, both used to estimate the accuracy of the models and orthomosaics. The root mean square error (RMSE) value obtained for the horizontal planimetric measurements was 0.05 m, while the RMSE value for the depth was 0.11 m. Underwater photogrammetry, if properly applied, can provide very high-resolution and accurate models for monitoring seagrass restoration actions for ecological recovery and can be useful for other research purposes in geological and environmental monitoring.

Modern digital cameras are increasing in quality whilst decreasing in size. In the last decade, a number of waterproof consumer digital cameras (action cameras) have become available, which often cost less than $500. A possible application of such action cameras is in the field of Underwater Photogrammetry. Especially with respect to the fact that with the change of the medium to below water can in turn counteract the distortions present. The goal of this paper is to investigate the suitability of such action cameras for underwater photogrammetric applications focusing on the stability of the camera and the accuracy of the derived coordinates for possible photogrammetric applications. For this paper a series of image sequences was capture in a water tank. A calibration frame was placed in the water tank allowing the calibration of the camera and the validation of the measurements using check points. The accuracy assessment covered three test sets operating three GoPro sports cameras of the same model (Hero 3 black). The test set included the handling of the camera in a controlled manner where the camera was only dunked into the water tank using 7MP and 12MP resolution and a rough handling where the camera was shaken as well as being removed from the waterproof case using 12MP resolution. The tests showed that the camera stability was given with a maximum standard deviation of the camera constant σc of 0.0031mm for 7MB (for an average c of 2.720mm) and 0.0072 mm for 12MB (for an average c of 3.642mm). The residual test of the check points gave for the 7MB test series the largest rms value with only 0.450mm and the largest maximal residual of only 2.5 mm. For the 12MB test series the maximum rms value is 0. 653mm. Refereed 14.a N/A Underwater camera, GoPro

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.