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D5.3: Report on test data for double-curvature rigid specimen
No full textIn this report the data of the high-speed ditching tests performed at the CNR Institute of Marine Engineering (former CNR-INSEAN) on double curvature specimens are presented. The report provides details on the specimen shapes as well as on their design and built. The shapes and conditions of the tests are basically those given in Deliverable D5.1 but after the discussion had during the M6 and M12 meetings, an additional shape, intermediate between S1 and S2, named S1B, is also considered. Some aspects concerning the electronic instrumentation and its calibration are also reported. The purpose of the high-speed ditching tests on double curvature specimen is to investigate the role of transverse and longitudinal curvatures on the ventilation/cavitation phenomena taking place at the rear of the fuselage. Besides helping the interpretation of the physics, the data of the tests are very important to assess the capabilities of computational approaches to correctly represent those phenomena which may have important consequences on the dynamics of the aircraft at ditching
Evaluating transdisciplinary science to open research-implementation spaces in European social-ecological systems
No full textResearchers in multiple, related fields that address complex social and environmental challenges, have shown ongoing enthusiasm for applying transdisciplinary social-ecological systems (SES) research to promote sustainability. However, few studies have evaluated the effectiveness of SES approach, assessed its achievements, and identified challenges to its implementation toward knowledge production for environmental conservation. We report the results of a qualitative, participatory evaluation of several SES projects across Europe using an evaluation methodology tailored to transdisciplinary projects. We conducted 66 stakeholder interviews at four designated Long-Term Socio-ecological Research (LTSER) platforms - Danube Delta and Braila Island (Romania); Cairngorms (Scotland); and Do?ana (Spain). Using qualitative analysis, we synthesized data from interviews and then returned to the sites to present findings to stakeholders in focus group discussions in order to incorporate their feedback into conclusions. We conclude that although particular scientists at each platform have taken on entrepreneurial roles to operationalize transdisciplinary science, a business-as-usual attitude tends to dominate institutions, limiting meaningful progress toward transdisciplinary objectives, including: integration of social science research, giving non-researcher stakeholders a more meaningful role in advancing relevant research, and improving knowledge exchange among different stakeholder groups, among other issues. While we found that all the components of transdisciplinary SES research exist at the sites, there is no overarching strategy to link long-term planning and funding, knowledge integration, and priority-setting with stakeholders to ensure the relevance of research for policy and practice. We conclude with reflections about implementing our evaluation methodology, and a call for periodic, participatory evaluation into the future
Graminoid invasion in an insular endemism hotspot and its protected areas
No full textInvasive plant species are increasingly altering species composition and the functioning of ecosystems from a local to a global scale. The grass species Pennisetum setaceum has recently raised concerns as an invader on dierent archipelagos worldwide. Among these aected archipelagos are the Canary Islands, which are a hotspot of endemism. Consequently, conservation managers and stakeholders are interested in the potential spreading of this species in the archipelago. We identify the current extent of the suitable habitat for P. setaceum on the island of La Palma to assess how it affects island ecosystems, protected areas (PAs), and endemic plant species richness. We recorded in situ occurrences of P. setaceum from 2010 to 2018 and compiled additional ones from databases at a 500 m x 500 m resolution. To assess the current suitable habitat and possible distribution patterns of P. setaceum on the island, we built an ensemble model. We projected habitat suitability for island ecosystems and PAs and identified risks for total as well as endemic plant species richness. The suitable habitat for P. setaceum is calculated to cover 34.7% of the surface of La Palma. In open ecosystems at low to mid elevations, where native ecosystems are already under pressure by land use and human activities, the spread of the invader will likely lead to additional threats to endemic plant species. Forest ecosystems (e.g., broadleaved evergreen and coniferous forests) are not likely to be aected by the spread of P. setaceum because of its heliophilous nature. Our projection of suitable habitat of P. setaceum within ecosystems and PAs on La Palma supports conservationists and policymakers in prioritizing management and control measures and acts as an example for the potential threat of this graminoid invader on other islands
Snow cover evolution in the Gran Paradiso National Park, Italian Alps, using the earth observation data cube
No full textMountainous regions are particularly vulnerable to climate change, and the impacts are already extensive and observable, the implications of which go far beyond mountain boundaries and the environmental sectors. Monitoring and understanding climate and environmental changes in mountain regions is, therefore, needed. One of the key variables to study is snow cover, since it represents an essential driver of many ecological, hydrological and socioeconomic processes in mountains. As remotely sensed data can contribute to filling the gap of sparse in-situ stations in high-altitude environments, a methodology for snow cover detection through time series analyses using Landsat satellite observations stored in an Open Data Cube is described in this paper, and applied to a case study on the Gran Paradiso National Park, in the western Italian Alps. In particular, this study presents a proof of concept of the preliminary version of the snow observation from space algorithm applied to Landsat data stored in the Swiss Data Cube. Implemented in an Earth Observation Data Cube environment, the algorithm can process a large amount of remote sensing data ready for analysis and can compile all Landsat series since 1984 into one single multi-sensor dataset. Temporal filtering methodology and multi-sensors analysis allows one to considerably reduce the uncertainty in the estimation of snow cover area using high-resolution sensors. The study highlights that, despite this methodology, the lack of available cloud-free images still represents a big issue for snow cover mapping from satellite data. Though accurate mapping of snow extent below cloud cover with optical sensors still represents a challenge, spatial and temporal filtering techniques and radar imagery for future time series analyses will likely allow one to reduce the current cloud cover issue
A portal offering standard visualization and analysis on top of an open data cube for sub-national regions: The Catalan data cube example
No full textThe amount of data that Sentinel fleet is generating over a territory such as Catalonia makes it virtually impossible to manually download and organize as files. The Open Data Cube (ODC) offers a solution for storing big data products in an efficient way with a modest hardware and avoiding cloud expenses. The approach will still be useful up to the next decade. Yet, ODC requires a level of expertise that most people who could benefit from the information do not have. This paper presents a web map browser that gives access to the data and goes beyond a simple visualization by combining the OGC WMS standard with modern web browser capabilities to incorporate time series analytics. This paper shows how we have applied this tool to analyze the spatial distribution of the availability of Sentinel 2 data over Catalonia and revealing differences in the number of useful scenes depending on the geographical area that ranges from one or two images per month to more than one image per week. The paper also demonstrates the usefulness of the same approach in giving access to remote sensing information to a set of protected areas around Europe participating in the H2020 ECOPotential project
D5.5: Report on test data for single-curvature deformable specimen
No full textIn this report the data of the high-speed ditching tests performed at the CNR-INM (Institute of Marine Engineering) former CNR-INSEAN, on single curvature, deformable specimens are presented. The report provides details on the specimen shapes and internal structure, the design and the instrumentation. The specimen designed was agreed with Airbus Defence and Space and mimics the internal structure of the aircraft. A total of four specimen were built and tested, two of them with a skin of uniform thickness of 1.6 mm and two with the skin thickness reduced by milling to 1.2 mm in the empty spaces between stringers and frames. The specimens with skin of uniform thickness were tested at 6 degrees pitch, V/U=0.0333, at a horizontal velocity U?48 m/s displaying a satisfactory repeatability of the data. Hence, the first specimen with the milled skin was tested still at 6 degrees pitch whereas the second specimen was tested at 10 degrees. In the latter case a large crack occurred on the skin soon after the impact and the large water ingress broke the cables and only a limited number of channel data is available. The purpose of the high-speed ditching tests on the single curvature deformable specimens is to provide a quite realistic dataset which can be used for the validation and development of the computational methods and to assess their ability to reproduce the correct fluid-structure interaction phenomena during ditching
Optimizing sampling effort and information content of biodiversity surveys: a case study of alpine grassland
No full textAims: Current rates of biodiversity loss do not allow for inefficient monitoring. Optimized monitoring maximizes the ratio between information and sampling effort (i.e., time and costs). Sampling effort increases with the number and size of sampling units. We hypothesize that an optimal size and number of sampling units can be determined providing maximal information via minimal effort. We apply an approach that identifies the optimal size and number of sampling quadrats. The approach can be adapted to any study system. Here we focus on alpine grassland, a diverse but threatened ecosystem. Location: Gran Paradiso National Park, Italy. Methods: We sampled nine 20m?20 m-plots. Each plot consisted of 100 2m?2 m-subplots. Species richness and Shannon diversity were quantified for different sizes and quantities of subplots. We simulated larger subplot sizes by unifying adjacent 2m?2 m-subplots. Shannon\u27s information entropy was used to quantify information content among richness and diversity values resulting from different subplot sizes and quantities. The optimal size and number of subplots is the lowest size and number of subplots returning maximal information. This optimal subplot size and number was determined by Mood\u27s median test and segmented linear regression, respectively. Results: The information content among richness values increased with subplot size, irrespective of the number of subplots. Therefore, the largest subplot size available is the optimal size for information about richness. Information content among diversity values increased with subplot size if 18 or less subplots were considered, and decreased if at least 27 subplots were sampled. The subplot quantity consequently determined whether the smallest or largest subplot size available is the optimal size, and whether the optimal size can be generalized across richness and diversity. Given a 2m?2m size, we estimated an optimal quantity of 54. Given a size of 4m?4 m, we estimated an optimal number of 36. The optimal number of plots can be generalized across both indices because it barely differed between the indices given a fixed subplot size. Conclusions: The information content among richness and diversity values depends on the sampling scale. Shannon\u27s information entropy can be used to identify the optimal number and size of plots that return most information with least sampling effort. Our approach can be adapted to other study systems to create an efficient in-situ sampling design, which improves biodiversity monitoring and conservation under rapid environmental change
Canopy height estimation from single multispectral 2D airborne imagery using texture analysis and machine learning in structurally rich temperate forests
No full textCanopy height is a fundamental biophysical and structural parameter, crucial for biodiversity monitoring, forest inventory and management, and a number of ecological and environmental studies and applications. It is a determinant for linking the classification of land cover to habitat categories towards building one-to-one relationships. Light detection and ranging (LiDAR) or 3D Stereoscopy are the commonly used and most accurate remote sensing approaches to measure canopy height. However, both require significant time and budget resources. This study proposes a cost-effective methodology for canopy height approximation using texture analysis on a single 2D image. An object-oriented approach is followed using land cover (LC) map as segmentation vector layer to delineate landscape objects. Global texture feature descriptors are calculated for each land cover object and used as variables in a number of classifiers, including single and ensemble trees, and support vector machines. The aim of the analysis is the discrimination among classes in a wide range of height values used for habitat mapping (from less than 5 cm to 40 m). For that task, different spatial resolutions are tested, representing a range from airborne to spaceborne quality ones, as well as their combinations, forming a multiresolution training set. Multiple dataset alternatives are formed based on the missing data handling, outlier removal, and data normalization techniques. The approach was applied using orthomosaics from DMC II airborne images, and evaluated against a reference LiDAR-derived canopy height model (CHM). Results reached overall object-based accuracies of 67% with the percentage of total area correctly classified exceeding 88%. Sentinel-2 simulation and multiresolution analysis (MRA) experiments achieved even higher accuracies of up to 85% and 91%, respectively, at reduced computational cost, showing potential in terms of transferability of the framework to large spatial scales
Quantifying uncertainties in earth observation-based ecosystem service assessments
No full textEcosystem service (ES) assessments are widely promoted as a tool to support decision-makers in ecosystem management, and the mapping of ES is increasingly supported by the spatial data on ecosystem properties provided by Earth Observation (EO). However, ES assessments are often associated with high levels of uncertainty, which affects their credibility. We demonstrate how different types of information on ES (including EO data, process models, and expert knowledge) can be integrated in a Bayesian Network, where the associated uncertainties are quantified. The probabilistic approach is used to map the provision and demand of avalanche protection, an important regulating service in mountain regions, and to identify the key sources of uncertainty. The model outputs show high uncertainties, mainly due to uncertainties in process modelling. Our results demonstrate that the potential of EO to improve the accuracy of ES assessments cannot be fully utilized without an improved understanding of ecosystem processes
