Unmanned Aerial Vehicles for Debris Survey in Coastal Areas: Long-Term Monitoring Programme to Study Spatial and Temporal Accumulation of the Dynamics of Beached Marine Litter

Unmanned aerial vehicles (UAVs) are becoming increasingly accessible tools with widespread use as environmental monitoring systems. They can be used for anthropogenic marine debris survey, a recently growing research field. In fact, while the increasing efforts for offshore investigations lead to a considerable collection of data on this type of pollution in the open sea, there is still little knowledge of the materials deposited along the coasts and the mechanism that leads to their accumulation pattern. UAVs can be effective in bridging this gap by increasing the amount of data acquired to study coastal deposits, while also limiting the anthropogenic impact in protected areas. In this study, UAVs have been used to acquire geo-referenced RGB images in a selected zone of a protected marine area (the Migliarino, Massacciuccoli, and San Rossore park near Pisa, Italy), during a long-term (ten months) monitoring programme. A post processing system based on visual interpretation of the images allows the localization and identification of the anthropogenic marine debris within the scanned area, and the estimation of their spatial and temporal distribution in different zones of the beach. These results provide an opportunity to investigate the dynamics of accumulation over time, suggesting that our approach might be appropriate for monitoring and collecting such data in isolated, and especially in protected, areas with significant benefits for different types of stakeholders

Mapping of Yucca gloriosa invasion along Mediterranean coastal dunes using unmanned aerial vehicles (UAVs)

Invasive Alien Plants (IAPs) are defined as those species whose introduction and/or spread outside their natural distribution can threaten the biological diversity of an ecosystem. They represent a severe threat to biodiversity and can severely alter the performance of crucial ecosystems such as coastal dunes. Coastal dunes are composed of specialized fauna and flora, converting them into strategic ecosystems due to their unique ecological functions. Coastal dunes are one of the most invaded European environments, with a total flora composed of up to 7% of IAPs. One of these IAPs is Yucca gloriosa L. (Asparagaceae), a homoploid hybrid native plant from the United States of America introduced to Europe for ornamental purposes. For Italy, Y. gloriosa is a typical invasive species related to fixed dunes dominated by Juniperus sp. pl. (with which it competes). Concerning biological invasions, maybe the most effective management strategy is early detection and mapping. In that sense, this work explores and tests the potential of unmanned aerial vehicles (UAVs) for detecting, mapping, and managing the Y. gloriosa invasion along the Mediterranean coastal dunes of a protected area located in Tuscany (Italy). In detail, this work focuses on four aspects: i) determine the suitability of RGB images to map Y. gloriosa, ii) identify the best time of data acquisition, iii) detect changes affecting the occurrence and cover of Y. gloriosa, and iv) propose a set of management actions to preserve a coastal dune ecosystem subjected to plant invasion. The UAV images allowed the generation of ultra-high spatial resolution maps to assess the Y. gloriosa invasion and distribution along the surveyed sandy dunes. The morphological characteristics of this plant – especially at the foliar level – make the invasion of Y. gloriosa particularly suitable for being evaluated and managed using UAV mapping, especially in coastal dunes vegetation that can be a mosaic of different plant communities hard to identify when airborne or satellite images are used. According to the obtained results, the spring season is the perfect time to collect data because light conditions are ideal, with minimal shading effects. Also, due to the peculiar morphology of Y. gloriosa leaves, the timing of data collection seems not crucial for mapping this IAP on coastal dune habitats. Despite the massive eradication action funded by a LIFE project during the period 2005-2009, Y. gloriosa is still present in the protected area and affects the priority habitat of juniper. This might be linked to the fact that Y. gloriosa is a perennial rhizomatous shrub capable of switching its photosynthesis from the C3 to CAM pathway and, therefore, withstand the harsh environmental conditions of dune ecosystems. The early detection using UAVs is the first line of defense against IAPs colonization over any ecosystem. From a conservation and management point of view, this work suggests the development of annual biomonitoring of Y. gloriosa to check its distribution over time and control its spread where it becomes particularly invasive. In this case, one possible strategy will be to keep the IAP in isolated nuclei of plants that are easier to remove with mechanical methods. In a broader view, the study area and the Mediterranean coast must include the ban on introducing non-native species as a strategy, adopting a short-term non-native Management Plan as urgent action

Motor Learning and Virtual Reality in Down Syndrome; a Literature Review

 Down syndrome (DS) is caused by trisomy of human chromosome 21 (Hsa21) and results in a large number of phenotypes including learning difficulties, cardiac defects and distinguishing facial features. The purpose of this study was to analyse research findings about “motor learning†and “virtual reality†in patients with DS. Relevant studies were identified by searching PubMed, Web of Science and BVS. Using key words, we searched for articles that included Down syndrome, virtual reality, and motor learning. Only studies on humans were eligible. The search  identified seven relevant papers. Most studies showed that individuals with Down syndrome are able to learn new tasks, and that improvements can be enhanced via the use of virtual reality. We conclude that individuals with Down syndrome respond positively and effectively, with improvements in sensory motor control, when stimulated with tasks that are complementary to conventional therapy, including therapy involving virtual reality

Maze computer performance in Down syndrome

Introduction: These changes are the main causes of defi cits in perceptual-motor skills responsible for motor skill acquisition and performance of functional activities. AIMS: The current study aimed at verifying the quantitative performance of people with DS in undertaking a computer task to compare the performances of typical development (TD). Method: 60 subjects participated in the study, 30 with Down’s syndrome and 30 with typical development, matched by sex. Individuals were aged from 10–36. The groups were divided into three subgroups by age: Group 1 (G1) 10–18; Group 2 (G2) 18–25; Group 3 (G3) 25–36. They performed a computer maze task. During the acquisition phase all groups attempted the maze 30 times, and then after 5 minutes they performed 5 repetitions of Maze 1 for the retention phase. Finally, for the transfer phase, they performed fi ve repetitions in Maze 2. The dependent variables were submitted to a group, age group, gender and block ANOVA with repeated measures on the last factor. Results: In acquisition phase there was a significant decrease in movement time (MT) between the fi rst and last acquisition block, but only for the DS-group. In retention, there was a significant effect of Group, and an interaction between Block and Group, indicating that MTs increased from retention to transfer, but only for the DS-group. Conclusion: It was found that participants with DS improved performance during acquisition and retention, but they had diffi culty in performing the transfer of the computational task for a similar situation. The age and gender were not signifi cant in any of the stages of the study.Introduction: These changes are the main causes of defi cits in perceptual-motor skills responsible for motor skill acquisition and performance of functional activities. AIMS: The current study aimed at verifying the quantitative performance of people with DS in undertaking a computer task to compare the performances of typical development (TD). Method: 60 subjects participated in the study, 30 with Down’s syndrome and 30 with typical development, matched by sex. Individuals were aged from 10–36. The groups were divided into three subgroups by age: Group 1 (G1) 10–18; Group 2 (G2) 18–25; Group 3 (G3) 25–36. They performed a computer maze task. During the acquisition phase all groups attempted the maze 30 times, and then after 5 minutes they performed 5 repetitions of Maze 1 for the retention phase. Finally, for the transfer phase, they performed fi ve repetitions in Maze 2. The dependent variables were submitted to a group, age group, gender and block ANOVA with repeated measures on the last factor. Results: In acquisition phase there was a significant decrease in movement time (MT) between the fi rst and last acquisition block, but only for the DS-group. In retention, there was a significant effect of Group, and an interaction between Block and Group, indicating that MTs increased from retention to transfer, but only for the DS-group. Conclusion: It was found that participants with DS improved performance during acquisition and retention, but they had diffi culty in performing the transfer of the computational task for a similar situation. The age and gender were not signifi cant in any of the stages of the study

Evaluation of speed-accuracy trade-off in a computer task to identify motor difficulties in individuals with Duchenne Muscular Dystrophy: A cross-sectional study

Introduction: Individuals with Duchenne Muscular Dystrophy (DMD) present with progressive loss of motor function which can impair both control of speed and accuracy of movement. Aim: to evaluate movement time during a task at various levels of difficulty and to verify whether the level of difficulty affects the speed and/ or accuracy during the task. Methods: the DMD group comprised of 17 individuals age matched with 17 individuals with typical development (TD group). The task evaluates the relationship between speed and accuracy, consisting of the execution of manual movements (using the mouse of the computer) aimed at a target at three different levels of difficulty (ID). Results: A MANOVA demonstrated statistically significant differences in dispersion data and intercept values between the groups with greater movement time in the DMD group. An ANOVA indicated differences between groups for ID, except for when there was a higher accuracy demand (higher ID). In the other IDs that required lower accuracy demand, individuals in the DMD group had significantly longer movement time when compared to the TD group. Conclusion: These results show that the TD and DMD did not differ in the higher ID, therefore it can be concluded that for those with DMD, motor performance is more affected by speed than accuracy of movement. What this paper adds? It is known that individuals with DMD have considerable motor deficits, however this paper shows that when the task involves higher accuracy compared with speed, people with DMD have performance similar to typically developed peers. This insight is a novel finding and can inform the rehabilitation team, to focus on training of speed, whilst maintaining accuracy for better execution of daily life tasks

Citizen Science, Education, and Learning: Challenges and Opportunities

Citizen science is a growing field of research and practice, generating new knowledge and understanding through the collaboration of citizens in scientific research. As the field expands, it is becoming increasingly important to consider its potential to foster education and learning opportunities. Although progress has been made to support learning in citizen science projects, as well as to facilitate citizen science in formal and informal learning environments, challenges still arise. This paper identifies a number of dilemmas facing the field—from competing scientific goals and learning outcomes, differing underlying ontologies and epistemologies, diverging communication strategies, to clashing values around advocacy and activism. Although such challenges can become barriers to the successful integration of citizen science into mainstream education systems, they also serve as signposts for possible synergies and opportunities. One of the key emerging recommendations is to align educational learning outcomes with citizen science project goals at the planning stage of the project using co-creation approaches to ensure issues of accessibility and inclusivity are paramount throughout the design and implementation of every project. Only then can citizen science realise its true potential to empower citizens to take ownership of their own science education and learning

Monitoring Light Pollution with an Unmanned Aerial Vehicle: A Case Study Comparing RGB Images and Night Ground Brightness

There are several tools and methods to quantify light pollution due to direct or reflected light emitted towards the sky. Unmanned aerial vehicles (UAV) are still rarely used in light pollution studies. In this study, a digital camera and a sky quality meter mounted on a UAV have been used to study the relationship between indices computed on night images and night ground brightness (NGB) measured by an optical device pointed downward towards the ground. Both measurements were taken simultaneously during flights at an altitude of 70 and 100 m, and with varying exposure time. NGB correlated significantly both with the brightness index (−0.49 ÷ −0.56) and with red (−0.52 ÷ −0.58) and green band indices (−0.42 ÷ −0.58). A linear regression model based on the luminous intensity index was able to estimate observed NGB with an RMSE varying between 0.21 and 0.46 mpsas. Multispectral analysis applied to images taken at 70 m showed that increasing exposure time might cause a saturation of the colors of the image, especially in the red band, that worsens the correlation between image indices and NGB. Our study suggests that the combined use of low cost devices such as UAV and a sky quality meter can be used for assessing hotspot areas of light pollution originating from the surface

Monitoring Light Pollution with an Unmanned Aerial Vehicle: A Case Study Comparing RGB Images and Night Ground Brightness

There are several tools and methods to quantify light pollution due to direct or reflected light emitted towards the sky. Unmanned aerial vehicles (UAV) are still rarely used in light pollution studies. In this study, a digital camera and a sky quality meter mounted on a UAV have been used to study the relationship between indices computed on night images and night ground brightness (NGB) measured by an optical device pointed downward towards the ground. Both measurements were taken simultaneously during flights at an altitude of 70 and 100 m, and with varying exposure time. NGB correlated significantly both with the brightness index (−0.49 ÷ −0.56) and with red (−0.52 ÷ −0.58) and green band indices (−0.42 ÷ −0.58). A linear regression model based on the luminous intensity index was able to estimate observed NGB with an RMSE varying between 0.21 and 0.46 mpsas. Multispectral analysis applied to images taken at 70 m showed that increasing exposure time might cause a saturation of the colors of the image, especially in the red band, that worsens the correlation between image indices and NGB. Our study suggests that the combined use of low cost devices such as UAV and a sky quality meter can be used for assessing hotspot areas of light pollution originating from the surface

Citizen Science for Marine Litter Detection and Classification on Unmanned Aerial Vehicle Images

Unmanned aerial vehicles (UAV, aka drones) are being used for mapping macro-litter in the environment. As drone images require a manual processing task for detecting marine litter, it is of interest to evaluate the accuracy of non-expert citizen science operators (CSO) in performing this task. Students from Italian secondary schools (in this work, the CSO) were invited to identify, mark, and classify stranded litter items on a UAV orthophoto collected on an Italian beach. A specific training program and working tools were developed for the aim. The comparison with the standard in situ visual census survey returned a general underestimation (50%) of items. However, marine litter bulk categorisation was fairly in agreement with the in situ survey, especially for sources classification. The concordance level among CSO ranged between 60% and 91%, depending on the item properties considered (type, material, and colour). As the assessment accuracy was in line with previous works developed by experts, remote detection of marine litter on UAV images can be improved through citizen science programs, upon an appropriate training plan and provision of specific tools. © 2021 by the authors. Licensee MDPI, Basel, Switzerland