TaLAM: Mapping Land Cover in Lowlands and Uplands with Satellite Imagery

End-of-Project ReportThe Towards Land Cover Accounting and Monitoring (TaLAM) project is part of Ireland’s response to creating a national land cover mapping programme. Its aims are to demonstrate how the new digital map of Ireland, Prime2, from Ordnance Survey Ireland (OSI), can be combined with satellite imagery to produce land cover maps

A Mediterranean coastal database for assessing the impacts of sea-level rise and associated hazards

We have developed a new coastal database for the Mediterranean basin that is intended for coastal impact and adaptation assessment to sea-level rise and associated hazards on a regional scale. The data structure of the database relies on a linear representation of the coast with associated spatial assessment units. Using information on coastal morphology, human settlements and administrative boundaries, we have divided the Mediterranean coast into 13 900 coastal assessment units. To these units we have spatially attributed 160 parameters on the characteristics of the natural and socio-economic subsystems, such as extreme sea levels, vertical land movement and number of people exposed to sea-level rise and extreme sea levels. The database contains information on current conditions and on plausible future changes that are essential drivers for future impacts, such as sea-level rise rates and socio-economic development. Besides its intended use in risk and impact assessment, we anticipate that the Mediterranean Coastal Database (MCD) constitutes a useful source of information for a wide range of coastal applications.Peer ReviewedPostprint (published version

3D and 4D Simulations for Landscape Reconstruction and Damage Scenarios. GIS Pilot Applications

The project 3D and 4D Simulations for Landscape Reconstruction and Damage Scenarios: GIS Pilot Applications has been devised with the intention to deal with the demand for research, innovation and applicative methodology on the part of the international programme, requiring concrete results to increase the capacity to know, anticipate and respond to a natural disaster. This project therefore sets out to develop an experimental methodology, a wide geodatabase, a connected performant GIS platform and multifunctional scenarios able to profitably relate the added values deriving from different geotechnologies, aimed at a series of crucial steps regarding landscape reconstruction, event simulation, damage evaluation, emergency management, multi-temporal analysis. The Vesuvius area has been chosen for the pilot application owing to such an impressive number of people and buildings subject to volcanic risk that one could speak in terms of a possible national disaster. The steps of the project move around the following core elements: creation of models that reproduce the territorial and anthropic structure of the past periods, and reconstruction of the urbanized area, with temporal distinctions; three-dimensional representation of the Vesuvius area in terms of infrastructuralresidential aspects; GIS simulation of the expected event; first examination of the healthcareepidemiological consequences; educational proposals. This paper represents a proactive contribution which describes the aims of the project, the steps which constitute a set of specific procedures for the methodology which we are experimenting, and some thoughts regarding the geodatabase useful to “package” illustrative elaborations. Since the involvement of the population and adequate hazard preparedness are very important aspects, some educational and communicational considerations are presented in connection with the use of geotechnologies to promote the knowledge of risk

Seafloor characterization using airborne hyperspectral co-registration procedures independent from attitude and positioning sensors

The advance of remote-sensing technology and data-storage capabilities has progressed in the last decade to commercial multi-sensor data collection. There is a constant need to characterize, quantify and monitor the coastal areas for habitat research and coastal management. In this paper, we present work on seafloor characterization that uses hyperspectral imagery (HSI). The HSI data allows the operator to extend seafloor characterization from multibeam backscatter towards land and thus creates a seamless ocean-to-land characterization of the littoral zone

A Multi-view Context-aware Approach to Android Malware Detection and Malicious Code Localization

Existing Android malware detection approaches use a variety of features such as security sensitive APIs, system calls, control-flow structures and information flows in conjunction with Machine Learning classifiers to achieve accurate detection. Each of these feature sets provides a unique semantic perspective (or view) of apps' behaviours with inherent strengths and limitations. Meaning, some views are more amenable to detect certain attacks but may not be suitable to characterise several other attacks. Most of the existing malware detection approaches use only one (or a selected few) of the aforementioned feature sets which prevent them from detecting a vast majority of attacks. Addressing this limitation, we propose MKLDroid, a unified framework that systematically integrates multiple views of apps for performing comprehensive malware detection and malicious code localisation. The rationale is that, while a malware app can disguise itself in some views, disguising in every view while maintaining malicious intent will be much harder. MKLDroid uses a graph kernel to capture structural and contextual information from apps' dependency graphs and identify malice code patterns in each view. Subsequently, it employs Multiple Kernel Learning (MKL) to find a weighted combination of the views which yields the best detection accuracy. Besides multi-view learning, MKLDroid's unique and salient trait is its ability to locate fine-grained malice code portions in dependency graphs (e.g., methods/classes). Through our large-scale experiments on several datasets (incl. wild apps), we demonstrate that MKLDroid outperforms three state-of-the-art techniques consistently, in terms of accuracy while maintaining comparable efficiency. In our malicious code localisation experiments on a dataset of repackaged malware, MKLDroid was able to identify all the malice classes with 94% average recall

Biologically informed ecological niche models for an example pelagic, highly mobile species

Background: Although pelagic seabirds are broadly recognised as indicators of the health of marine systems, numerous gaps exist in knowledge of their at-sea distributions at the species level. These gaps have profound negative impacts on the robustness of marine conservation policies. Correlative modelling techniques have provided some information, but few studies have explored model development for non-breeding pelagic seabirds. Here, I present a first phase in developing robust niche models for highly mobile species as a baseline for further development.Methodology: Using observational data from a 12-year time period, 217 unique model parameterisations across three correlative modelling algorithms (boosted regression trees, Maxent and minimum volume ellipsoids) were tested in a time-averaged approach for their ability to recreate the at-sea distribution of non-breeding Wandering Albatrosses (Diomedea exulans) to provide a baseline for further development.Principle Findings/Results: Overall, minimum volume ellipsoids outperformed both boosted regression trees and Maxent. However, whilst the latter two algorithms generally overfit the data, minimum volume ellipsoids tended to underfit the data. Conclusions: The results of this exercise suggest a necessary evolution in how correlative modelling for highly mobile species such as pelagic seabirds should be approached. These insights are crucial for understanding seabird–environment interactions at macroscales, which can facilitate the ability to address population declines and inform effective marine conservation policy in the wake of rapid global change

Incorporating Spatial Data and GIS to Improve SEA of Land use Plans: Opportunities and Limitations: Case Studies in the Republic of Ireland

This research aimed at establishing whether spatial data and Geographic Information Systems (GIS) can contribute to Strategic Environmental Assessment (SEA). To achieve this, an integrated GISEA approach was developed and applied to a number of spatial planning SEAs in the Republic of Ireland. The practical applicability of the approach was examined, evaluating the potential benefits derived from using spatial data and GIS in SEA and assessing the potential barriers to an effective GIS use. The implementation of the SEA Directive incorporated a new dimension into plan-making by calling for the assessment of potential environmental effects that may derive from implementing a plan. The intrinsic spatial nature of land use plans poses specific requirements on the tools and assessment methods used. GIS – with their capacity to visually display and spatially assess information- have the potential to support SEA processes. Moreover, GIS tools can tackle the spatio-temporal dimensions that conventional assessment methods (e.g. matrices and checklists) fail to address. To explore the validity of these arguments, GISEA was applied to seven Irish development plans. These were supported by interviews with the planners and technicians involved, and through review of published SEA environmental reports. The case studies demonstrated that GIS can provide the mappable aspects of SEA; they facilitate the process by enhancing understanding of environmental and planning considerations, and improving the accuracy of assessments. These observations concur with published literature on the predicted benefits of applying GIS at various environmental assessment levels. Nevertheless, the results revealed that framework and procedural difficulties remain (e.g. institutional arrangements and technical data issues). These are more apparent at higher planning tiers and in certain SEA stages such as public participation. The contribution of GIS largely depends on scope for spatial information, availability and quality of relevant datasets, and willingness of involved organisations to facilitate data provision and disclosure. Therefore, formulation of spatially-specific land use plans and improved data accessibility and quality can contribute to an effective GIS use in SEA. Further research and practice are required to disclose the full potential of GISEA, but the work-placement aspect of this research has already had a direct impact on the level of GIS use in Irish SEA practice