Photogrammetry as a participatory recovery tool after disasters: a grounded framework for future guidelines

This paper identifiesthe application domain, context of use, processes and goals of low-cost street-level photogrammetry after urban disasters.The proposal seeks a synergy between top-down and bottom-up initiatives carried out by different actorsduring the humanitarian response phasein data scarce contexts. By focusing on the self-organisation capacities of local people, this paper suggests using collaborative photogrammetry to empower communities hit by disasters and foster their active participation in recovery and reconstruction planning. It shows that this task may prove technically challenging depending on the specifics of the collected imageryand develops agrounded framework to produce user-centred image acquisition guidelines and fit-for-purpose photogrammetric reconstruction workflows, useful in future post-disaster scenarios.To this end, it presents an in-depth analysis of a collaborative photographic mapping initiative undergone by a group of citizen-scientists after the 2016 Central Italy earthquake, followed by the explorative processing of some sample datasets.Specifically, the paper firstly presents avisualethnographic study of thephotographic materialuploadedbyparticipantsfrom September2016 to November 2018in the two Italian municipalities of Arquata del Tronto and Norcia. Secondly, it illustrates from atechnical point of view issues concerningthe processing of crowdsourced data(e.g. image filtering, selection, quality, semantic content and 3D model scaling)and discussesthe viability of using itto enrich the pool of geo-information availableto stakeholders and decision-makers.Final considerations are discussed as part of a grounded framework for future guidelines tailored tomultiplegoals anddata processingscenario

Seismic properties of rocks in Kylylahti Cu-Au-Zn mine

Non peer reviewe

Metal concentrations of sediments in Vanhankaupunginlahti dam basin, river Vantaa

Non peer reviewe

Common Mid Point (CMP) surveying for depth calibration of ground penetrating radar data

Non peer reviewe

Building Digital 3D Learning Environments To Support the Teaching in Geosciences

Non peer reviewe

Coastal management and adaptation: an integrated data-driven approach

Coastal regions are some of the most exposed to environmental hazards, yet the coast is the preferred settlement site for a high percentage of the global population, and most major global cities are located on or near the coast. This research adopts a predominantly anthropocentric approach to the analysis of coastal risk and resilience. This centres on the pervasive hazards of coastal flooding and erosion. Coastal management decision-making practices are shown to be reliant on access to current and accurate information. However, constraints have been imposed on information flows between scientists, policy makers and practitioners, due to a lack of awareness and utilisation of available data sources. This research seeks to tackle this issue in evaluating how innovations in the use of data and analytics can be applied to further the application of science within decision-making processes related to coastal risk adaptation. In achieving this aim a range of research methodologies have been employed and the progression of topics covered mark a shift from themes of risk to resilience. The work focuses on a case study region of East Anglia, UK, benefiting from the input of a partner organisation, responsible for the region’s coasts: Coastal Partnership East. An initial review revealed how data can be utilised effectively within coastal decision-making practices, highlighting scope for application of advanced Big Data techniques to the analysis of coastal datasets. The process of risk evaluation has been examined in detail, and the range of possibilities afforded by open source coastal datasets were revealed. Subsequently, open source coastal terrain and bathymetric, point cloud datasets were identified for 14 sites within the case study area. These were then utilised within a practical application of a geomorphological change detection (GCD) method. This revealed how analysis of high spatial and temporal resolution point cloud data can accurately reveal and quantify physical coastal impacts. Additionally, the research reveals how data innovations can facilitate adaptation through insurance; more specifically how the use of empirical evidence in pricing of coastal flood insurance can result in both communication and distribution of risk. The various strands of knowledge generated throughout this study reveal how an extensive range of data types, sources, and advanced forms of analysis, can together allow coastal resilience assessments to be founded on empirical evidence. This research serves to demonstrate how the application of advanced data-driven analytical processes can reduce levels of uncertainty and subjectivity inherent within current coastal environmental management practices. Adoption of methods presented within this research could further the possibilities for sustainable and resilient management of the incredibly valuable environmental resource which is the coast

OGRS2012 Symposium Proceedings

Do you remember the Open Source Geospatial Research and Education Symposium (OGRS) in Nantes? "Les Machines de l’Île", the Big Elephant, the "Storm Boat" with Claramunt, Petit et al. (2009), and "le Biniou et la Bombarde"? A second edition of OGRS was promised, and that promise is now fulfilled in OGRS 2012, Yverdon-les-Bains, Switzerland, October 24-26, 2012. OGRS is a meeting dedicated to sharing knowledge, new solutions, methods, practices, ideas and trends in the field of geospatial information through the development and the use of free and open source software in both research and education. In recent years, the development of geospatial free and open source software (GFOSS) has breathed new life into the geospatial domain. GFOSS has been extensively promoted by FOSS4G events, which evolved from meetings which gathered together interested GFOSS development communities to a standard business conference. More in line with the academic side of the FOSS4G conferences, OGRS is a rather neutral forum whose goal is to assemble a community whose main concern is to find new solutions by sharing knowledge and methods free of software license limits. This is why OGRS is primarily concerned with the academic world, though it also involves public institutions, organizations and companies interested in geospatial innovation. This symposium is therefore not an exhibition for presenting existing industrial software solutions, but an event we hope will act as a catalyst for research and innovation and new collaborations between research teams, public agencies and industries. An educational aspect has recently been added to the content of the symposium. This important addition examines the knowledge triangle - research, education, and innovation - through the lens of how open source methods can improve education efficiency. Based on their experience, OGRS contributors bring to the table ideas on how open source training is likely to offer pedagogical advantages to equip students with the skills and knowledge necessary to succeed in tomorrow’s geospatial labor market. OGRS brings together a large collection of current innovative research projects from around the world, with the goal of examining how research uses and contributes to open source initiatives. By presenting their research, OGRS contributors shed light on how the open-source approach impacts research, and vice-versa. The organizers of the symposium wish to demonstrate how the use and development of open source software strengthen education, research and innovation in geospatial fields. To support this approach, the present proceedings propose thirty short papers grouped under the following thematic headings: Education, Earth Science & Landscape, Data, Remote Sensing, Spatial Analysis, Urban Simulation and Tools. These papers are preceded by the contributions of the four keynote speakers: Prof Helena Mitasova, Dr Gérard Hégron, Prof Sergio Rey and Prof Robert Weibel, who share their expertise in research and education in order to highlight the decisive advantages of openness over the limits imposed by the closed-source license system

Dynamics and Modelling of the 2015 Calbuco eruption Volcanic Debris Flows (Chile). From field evidence to a primary lahar model

The Calbuco volcanic eruption of 2015, was characterized by two explosive phases with partialand major column collapses that triggered lahars in many of the flanks of the volcano. Large lahar flows descended to the southern flank where highly fractured ice bodies were emplaced on steep slopes.In this study, we present a chronology of the volcanic flows based on a multi parameterdata set that includes social media, reports of authoritative institutions, instrumental monitoringdata and published research literature on the eruption. Our review established thatlahars in the Amarillo river began during the first phase of the eruption due to the sustained emplacement of pyroclastic flows in its catchment. In contrast, we propose that the lahars in theBlanco – Correntoso river system and the Este river were likely to have been triggered by asudden mechanical collapse of the glacier that triggered mixed avalanches which transitionedinto lahars downstream.Our observations include inundation cross-sections, estimates of flow speeds, and characterization of the morphology, grain sizes, and componentry of deposits.Field measurements are used together with instrumental data for calibrating a dynamic, physics-based model of lahar, Laharflow. We model flows in the Blanco – Correntoso river system and explore the influence of the model parameters on flow predictions in an ensemble of simulations. We develop a calibration that accounts for the substantial epistemic uncertainties in our observations and the model formulation, that seeks to determine plausible ranges for the model parameters, including those representing the lahar source. Our approach highlights the parameters in the model that have a dominant effect on the ability of the model to match observations, indicating where further development and additional observations could improve model predictions. The simulations in our ensemble that provide plausible matches to the observations are combined to produce flow inundation maps