Empirical allometric equations relating biomass of aboveground components to dendrometric variables for Pinus brutia Ten. trees are derived in this paper.
This paper describes the development of a decision support system (DSS) for prevention planning and emergency management of forest fire events that incorporates weather data management, a geographical data viewer, a priori danger forecasting and fire propagation modeling, automatic fire detection, and optimal resource dispatching. Collection, input, storage, management, and analysis of the information rely on advanced and automated methodologies using remote sensing, GPS, digital mapping, and geographic information systems. The results included short-term dynamic fire danger indices developed for improved and realistic prevention and pre-suppression planning. An automatic fire detection technology based on infrared video was developed and successfully tested on site. Several models for understanding fire propagation on forest fires have been proposed for practical application. Additionally, a DSS was developed with the innovation of covering wildland fire hazard management entirely, providing a complete coverage of technical and administrative activities that support decision makers in real time. The DSS was tested for high fire seasons in two different sites in South Europe.
Geoinformatics plays an essential role during the recovery phase of a post-earthquake situation. The aim of this paper is to present the methodology followed and the results obtained by the utilization of Unmanned Aircraft Systems (UASs) 4K-video footage processing and the automation of geo-information methods targeted at both monitoring the demolition process and mapping the demolished buildings. The field campaigns took place on the traditional settlement of Vrisa (Lesvos, Greece), which was heavily damaged by a strong earthquake (Mw=6.3) on June 12th, 2017. For this purpose, a flight campaign took place on 3rd February 2019 for collecting aerial 4K video footage using an Unmanned Aircraft. The Structure from Motion (SfM) method was applied on frames which derived from the 4K video footage, for producing accurate and very detailed 3D point clouds, as well as the Digital Surface Model (DSM) of the building stock of the Vrisa traditional settlement, twenty months after the earthquake. This dataset has been compared with the corresponding one which derived from 25th July 2017, a few days after the earthquake. Two algorithms have been developed for detecting the demolished buildings of the affected area, based on the DSMs and 3D point clouds, correspondingly. The results obtained have been tested through field studies and demonstrate that this methodology is feasible and effective in building demolition detection, giving very accurate results (97%) and, in parallel, is easily applicable and suit well for rapid demolition mapping during the recovery phase of a post-earthquake scenario. The significant advantage of the proposed methodology is its ability to provide reliable results in a very low cost and time-efficient way and to serve all stakeholders and national and local organizations that are responsible for post-earthquake management.
<p><strong>Abstract.</strong> Building damage assessment caused by earthquakes is essential during the response phase following a catastrophic event. Modern techniques include terrestrial and aerial photogrammetry based on Structure from Motion algorithm and Laser Scanning with the latter to prove its superiority in accuracy assessment due to the high-density point clouds. However, standardized procedures during emergency surveys often could not be followed due to restrictions of outdoor operations because of debris or decrepit buildings, the high human presence of civil protection agencies, expedited deployment of survey team and cost of operations. The aim of this paper is to evaluate whether terrestrial photogrammetry based on a handheld amateur DSLR camera can be used to map building damages, structural deformations and facade production in an accepted accuracy comparing to laser scanning technique. The study area is the Vrisa village, Lesvos, Greece where a Mw&thinsp;6.3 earthquake occurred on June 12th, 2017. A dense point cloud from some digital images created based on Structure from Motion algorithm and compared with a dense point cloud acquired by a laser scanner. The distance measurement and the comparison were conducted with the Multiscale Model to Model Cloud Comparison method. According to the results, the mean of the absolute distances between the two clouds is 0.038&thinsp;m while the 94.9&thinsp;% of the point distances are less than 0.1&thinsp;m. Terrestrial photogrammetry proved to be an accurate methodology for rapid earthquake damage assessment thus its products were used by local authorities for the calculation of the compensation for the property loss.</p>
<p><strong>Abstract.</strong> The aim of this paper is to present the methodology followed and the results obtained by the synergistic exploitation of geo-information methods towards 3D mapping of the impact of the catastrophic earthquake of June 12th 2017 on the traditional settlement of Vrisa on the island of Lesvos, Greece. A campaign took place for collecting: a) more than 150 ground control points using an RTK system, b) more than 20.000 high-resolution terrestrial and aerial images using cameras and Unmanned Aircraft Systems and c) 140 point clouds by a 3D Terrestrial Laser Scanner. The Structure from Motion method has been applied on the high-resolution terrestrial and aerial photographs, for producing accurate and very detailed 3D models of the damaged buildings of the Vrisa settlement. Additionally, two Orthophoto maps and Digital Surface Models have been created, with a spatial resolution of 5&thinsp;cm and 3&thinsp;cm, respectively. The first orthophoto map has been created just one day after the earthquake, while the second one, a month later. In parallel, 3D laser scanning data have been exploited in order to validate the accuracy of the 3D models and the RTK measurements used for the geo-registration of all the above-mentioned datasets. The significant advantages of the proposed methodology are: a) the coverage of large scale areas; b) the production of 3D models having very high spatial resolution and c) the support of post-earthquake management and reconstruction processes of the Vrisa village, since such 3D information can serve all stakeholders, be it national and/or local organizations.</p>
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