Assessment of a Smartphone-Based Camera System for Coastal Image Segmentation and Sargassum monitoring

International audienceCoastal video monitoring has proven to be a valuable ground-based technique to investigate ocean processes. Presently, there is a growing need for automatic, technically efficient, and inexpensive solutions for image processing. Moreover, beach and coastal water quality problems are becoming significant and need attention. This study employs a methodological approach to exploit low-cost smartphone-based images for coastal image classification. The objective of this paper is to present a methodology useful for supervised classification for image semantic segmentation and its application for the development of an automatic warning system for Sargassum algae detection and monitoring. A pixel-wise convolutional neural network (CNN) has demonstrated optimal performance in the classification of natural images by using abstracted deep features. Conventional CNNs demand a great deal of resources in terms of processing time and disk space. Therefore, CNN classification with superpixels has recently become a field of interest. In this work, a CNN-based deep learning framework is proposed that combines sticky-edge adhesive superpixels. The results indicate that a cheap camera-based video monitoring system is a suitable data source for coastal image classification, with optimal accuracy in the range between 75% and 96%. Furthermore, an application of the method for an ongoing case study related to Sargassum monitoring in the French Antilles proved to be very effective for developing a warning system, aiming at evaluating floating algae and algae that had washed ashore, supporting municipalities in beach management

Exploiting remote imagery in an embayed sandy beach for the validation of a runup model framework

International audienceStorm surge and wave runup are key determinants of the potential for beach overwashing during storm events. However, the prediction and quantification of wave runup on embayed beaches is strongly influenced by particular characteristics (e.g., irregular morphology, low tides, absence of swell, etc.) which differ from those on open beaches, and have rarely been investigated in literature. In the present paper, a model framework aimed at predicting wave-induced runup on an embayed sandy beach is validated by means of measurements derived from a video-monitoring station, recently installed in South Italy, during two storm events in 2016. The numerical approach employs MeteOcean forecasted waves within SWAN and SWASH models (in both 2-d and 1-d mode). The combination of multibeam and d-RTK surveys with Unmanned Aerial Vehicle (UAV) imagery provides high resolution depth grid (m 0.015), particularly required in shallow waters, where wave hydrodynamics is highly influenced by the bottom. The results show and discuss the agreement between video measurements and 2-d predictions of runup. A sensitivity analysis of the Manningfls roughness factor is needed in 1-d simulations. The accuracy of the empirical formulas in predicting wave runup in an embayed beach is also investigated , showing mainly an overestimation of the observations

new coastal video monitoring system achievement and development

A new coastal video monitoring system for Apulia region, southeast of Italy, is under development. It is composed of visible and thermal streams and featured to be included in a wider meteo-oceanographic monitoring network. The system is designed for use on sandy beaches. The regional Basin Authority (AdBP) through previous field campaigns has identified for long-term monitoring purposes two hotspots, prone to erosion and flooding: Torre Canne (Fasano, BR) and Torre Lapillo (Porto Cesareo, LE), facing the Adriatic and Ionian seas, respectively. This paper presents the actual architecture and some initial findings of its implementation aiming at a complete automatic analysis of morphological features and hydrodynamic studies, mainly focused in swash zone

Global vulnerability of soil ecosystems to erosion

International audienceContextSoil erosion is one of the main threats driving soil degradation across the globe with important impacts on crop yields, soil biota, biogeochemical cycles, and ultimately human nutrition.ObjectivesHere, using an empirical model, we present a global and temporally explicit assessment of soil erosion risk according to recent (2001–2013) dynamics of rainfall and vegetation cover change to identify vulnerable areas for soils and soil biodiversity.MethodsWe used an adaptation of the Universal Soil Loss Equation together with state of the art remote sensing models to create a spatially and temporally explicit global model of soil erosion and soil protection. Finally, we overlaid global maps of soil biodiversity to assess the potential vulnerability of these soil communities to soil erosion.ResultsWe show a consistent decline in soil erosion protection over time across terrestrial biomes, which resulted in a global increase of 11.7% in soil erosion rates. Notably, soil erosion risk systematically increased between 2006 and 2013 in relation to the baseline year (2001). Although vegetation cover is central to soil protection, this increase was mostly driven by changes in rainfall erosivity. Globally, soil erosion is expected not only to have an impact on the vulnerability of soil conditions but also on soil biodiversity with 6.4% (for soil macrofauna) and 7.6% (for soil fungi) of these vulnerable areas coinciding with regions with high soil biodiversity.ConclusionsOur results indicate that an increasing proportion of soils are degraded globally, affecting not only livelihoods but also potentially degrading local and regional landscapes. Similarly, many degraded regions coincide with and may have impacted high levels of soil biodiversity

WALOWA (wave loads on walls) : large-scale experiments in the delta flume

Overtopping wave loads on vertical structures on top of a dike have been investigated in several small scale experiments in the past. A large-scale validation for a mild foreshore situation is still missing. Hence the WALOWA experimental campaign was carried out to address this topic. In the present paper the objectives of the WALOWA project are outlined in detail, the model and measurement set-up described and the test program presented. Furthermore, preliminary results featuring a single 1000 irregular waves test of the test program are highlighted. This includes the study of the mild and sandy foreshore evolution by comparing profiles before and after the test execution. The profile measurements are obtained with a mechanical profiler. The wave parameters offshore and at the dike toe are numerically simulated using a SWASH model. The numerical results are validated against the measurements. Finally, the force and pressure time series of the waves impacting against the wall are processed and filtered. The load cell measurements and the time series of integrated pressures are compared to each other and for each impact event the maximum force is derived.Hydraulic Structures and Flood RiskEnvironmental Fluid Mechanic

Temperature Effects Explain Continental Scale Distribution of Cyanobacterial Toxins

Insight into how environmental change determines the production and distribution of cyanobacterial toxins is necessary for risk assessment. Management guidelines currently focus on hepatotoxins (microcystins). Increasing attention is given to other classes, such as neurotoxins (e.g., anatoxin-a) and cytotoxins (e.g., cylindrospermopsin) due to their potency. Most studies examine the relationship between individual toxin variants and environmental factors, such as nutrients, temperature and light. In summer 2015, we collected samples across Europe to investigate the effect of nutrient and temperature gradients on the variability of toxin production at a continental scale. Direct and indirect effects of temperature were the main drivers of the spatial distribution in the toxins produced by the cyanobacterial community, the toxin concentrations and toxin quota. Generalized linear models showed that a Toxin Diversity Index (TDI) increased with latitude, while it decreased with water stability. Increases in TDI were explained through a significant increase in toxin variants such as MC-YR, anatoxin and cylindrospermopsin, accompanied by a decreasing presence of MC-LR. While global warming continues, the direct and indirect effects of increased lake temperatures will drive changes in the distribution of cyanobacterial toxins in Europe, potentially promoting selection of a few highly toxic species or strains.Peer reviewe

A new video monitoring system in support of Coastal Zone Management at Apulia Region, Italy

New systems for video monitoring and surveillance of Apulian coasts (South-east of Italy) have been recently employed. The system design aims at obtaining a tool able to automatically perform image acquisition, image processing and dissemination of results on a web portal. In the present paper, the system implementation and video stations installation at two different sites are described. A new specific Shoreline Detection Model (SDM) has been developed, based on boundary extraction procedure from automatic segmented coastal area. In real time, processed images and shoreline maps are uploaded and make freely downloadable. Moreover, shoreline time variation analysis is available on user-selected transects in cross-shore direction. The SDM model validation is here presented at one location. Over a set of testing images, the pixel-based comparison between manually and automatically detected shorelines lead to a mean distance of about View the MathML source. Then, the reconstruction of intertidal bathymetry from video is reported and compared with topographical (d-RTK) field survey, in order to assess the system efficacy and accuracy in coastal area monitoring, resulting in a mean RMS error overall the transects investigated equal to 0.025 m