Sar Shoreline Processor: Methodology and First Results

Coastlines are continuously transforming, and satellite-based remote sensing represents a cost-effective observation method able to accurately map and monitor these changes. While optical technology is limited by factors like darkness, clouds, and rain, Synthetic Aperture Radar (SAR) remains unaffected, offering the advantage of potentially providing more frequent updates for shoreline mapping. This study presents an innovative automatic processor to extract shorelines (SLs) from SAR data to track coastline variations over time. It is applied across various sites, showing the effects on the SL positions of the incidence angle between the sensor’s line of sight and the scene topography. The research findings consistently show that SAR-derived SLs align with positions above the high-water mark across all the studied sites. Depending on the topography, the SLs acquired in ascending (ASC) and descending (DESC) tracks show overlapping or mismatch. This paper presents two examples of such occurrences. This offers coastal scientists and stakeholders a unique tool for complementing the analysis conducted by optical sensors, which is especially relevant in regions of the Earth that are constantly affected by cloud cove

Opportunities and challenges for monitoring terrestrial biodiversity in the robotics age

\ua9 The Author(s) 2025.With biodiversity loss escalating globally, a step change is needed in our capacity to accurately monitor species populations across ecosystems. Robotic and autonomous systems (RAS) offer technological solutions that may substantially advance terrestrial biodiversity monitoring, but this potential is yet to be considered systematically. We used a modified Delphi technique to synthesize knowledge from 98 biodiversity experts and 31 RAS experts, who identified the major methodological barriers that currently hinder monitoring, and explored the opportunities and challenges that RAS offer in overcoming these barriers. Biodiversity experts identified four barrier categories: site access, species and individual identification, data handling and storage, and power and network availability. Robotics experts highlighted technologies that could overcome these barriers and identified the developments needed to facilitate RAS-based autonomous biodiversity monitoring. Some existing RAS could be optimized relatively easily to survey species but would require development to be suitable for monitoring of more ‘difficult’ taxa and robust enough to work under uncontrolled conditions within ecosystems. Other nascent technologies (for instance, new sensors and biodegradable robots) need accelerated research. Overall, it was felt that RAS could lead to major progress in monitoring of terrestrial biodiversity by supplementing rather than supplanting existing methods. Transdisciplinarity needs to be fostered between biodiversity and RAS experts so that future ideas and technologies can be codeveloped effectively

Opportunities and challenges for monitoring terrestrial biodiversity in the robotics age

With biodiversity loss escalating globally, a step change is needed in our capacity to accurately monitor species populations across ecosystems. Robotic and autonomous systems (RAS) offer technological solutions that may substantially advance terrestrial biodiversity monitoring, but this potential is yet to be considered systematically. We used a modified Delphi technique to synthesize knowledge from 98 biodiversity experts and 31 RAS experts, who identified the major methodological barriers that currently hinder monitoring, and explored the opportunities and challenges that RAS offer in overcoming these barriers. Biodiversity experts identified four barrier categories: site access, species and individual identification, data handling and storage, and power and network availability. Robotics experts highlighted technologies that could overcome these barriers and identified the developments needed to facilitate RAS-based autonomous biodiversity monitoring. Some existing RAS could be optimized relatively easily to survey species but would require development to be suitable for monitoring of more ‘difficult’ taxa and robust enough to work under uncontrolled conditions within ecosystems. Other nascent technologies (for instance, new sensors and biodegradable robots) need accelerated research. Overall, it was felt that RAS could lead to major progress in monitoring of terrestrial biodiversity by supplementing rather than supplanting existing methods. Transdisciplinarity needs to be fostered between biodiversity and RAS experts so that future ideas and technologies can be codeveloped effectively

Micro-Vibration-Based Slip Detection in Tactile Force Sensors

Tactile sensing provides critical information, such as force, texture, shape or temperature, in manipulation tasks. In particular, tactile sensors traditionally used in robotics are emphasized in contact force determination for grasping control and object recognition. Nevertheless, slip detection is also crucial to successfully manipulate an object. Several approaches have appeared to detect slipping, the majority being a combination of complex sensors with complex algorithms. In this paper, we deal with simplicity, analyzing how a novel, but simple, algorithm, based on micro-vibration detection, can be used in a simple, but low-cost and durable, force sensor. We also analyze the results of using the same principle to detect slipping in other force sensors based on flexible parts. In particular, we show and compare the slip detection with: (i) a flexible finger, designed by the authors, acting as a force sensor; (ii) the finger torque sensor of a commercial robotic hand; (iii) a commercial six-axis force sensor mounted on the wrist of a robot; and (iv) a fingertip piezoresistive matrix sensor

Assessment of Shoreline Change from SAR Satellite Imagery in Three Tidally Controlled Coastal Environments

Coasts are continually changing and remote sensing from satellites has the potential to both map and monitor coastal change at multiple scales. Unlike optical technology, synthetic aperture radar (SAR) is uninfluenced by darkness, clouds, and rain, potentially offering a higher revision period to map shoreline position and change, but this can only be feasible if we have a better interpretation of what shorelines as extracted from SAR imagery represent on the ground. This study aims to assess the application of shorelines extracted from SAR from publicly available satellite imagery to map and capture intra-annual to inter-annual shoreline variability. This is assessed in three tidally controlled coastal study areas that represent sand and gravel beaches with different backshore environments: low-lying dunes and marsh; steep, rocky cliff; and urban environments. We have found that SAR shorelines consistently corresponded to positions above the high-water mark across all three sites. We further discuss the influence of the scene geometry, meteorological and oceanographic conditions, and backshore environment and provide a conceptual interpretation of SAR-derived shorelines. In a low-lying coastal setting, the annual change rate derived through SAR presents a high degree of alignment with the known reference values. The present study contributes to our understanding of the poorly known aspect of using shorelines derived from publicly available SAR satellite missions. It outlines a quantitative approach to automatically assess their quality with a new automatic detection method that is transferable to shoreline evolution assessments worldwide

The geographic scale of speciation in the Indo-Pacific marine red algal genus Portieria

International audienc

The geographic scale of speciation in the Indo-Pacific marine red algal genus Portieria

International audienc