1,721,049 research outputs found
Geomatics for Terrain’s Deformation Monitoring: The H2020 LiquefACT Field Trial in Pieve di Cento, Italy
No full textThe paper presents a case study on the application of Geomatics to terrain’s deformation monitoring. Within the EU H2020 LiquefACT project, the Laboratory of Geomatics of the University of Pavia (Italy) was appointed to quantify the subsidence suffered by the terrain due to some trials conducted in the test site of Pieve di Cento, Northern Italy. Geomatics has long been used for deformation monitoring, but present paper deals with two peculiar elements: the constraints given by the test field, its layout, the allowed and forbidden actions, that forced the surveyors to elaborate an unconventional surveying design, and the use of a state-of-the-art instrument, the Trimble SX10. It mainly is a high-level topographic total station; being robotized, it has interesting laser scanning capabilities. In the paper, the survey design will be illustrated and discussed, and a selection of the obtained results will be presented. They highlight how much geomatics can be flexible and adaptable and, at the same time, precise and accurate
L'uso dell'acqua in ambito urbano: un approccio ecosistemico per valutarne la sostenibilità
No full textAccuracy assessment of ADS40 imagery as a function of flying height and of aerial triangulation strategies
No full textThe paper concerns an in-depth study of the attainable accuracy of Leica ADS40 imagery. The study has been carried out with the Socet-Set and ORIMA programs and takes advantage of the Pavia Test Site, where many artificial and natural, very well measured control points are available. Three flights are considered, having a relative height of approximately 2000, 4000 and 6000 metres. Different configurations are investigated, characterized by the usage of 0, 1, 5 and 12 GCPs. Finally, several adjustment strategies are analyzed: together with the basic adjustment model, the usage of additional parameters (such as datum transformation and reestimation of IMU misalignments), as well as the camera self-calibration are taken into consideration
WEIGHTED ICP POINT CLOUDS REGISTRATION by SEGMENTATION BASED on EIGENFEATURES CLUSTERING
No full textDense point clouds can be nowadays considered the main product of UAV (Unmanned Aerial Vehicle) photogrammetric processing and clouds registration is still a key aspect in case of blocks acquired apart. In the paper some overlapping datasets, acquired with a multispectral Parrot Sequoia camera above some rice fields, are analysed in a single block approach. Since the sensors is equipped with a navigation-grade sensor, the georeferencing information is affected by large errors and the so obtained dense point clouds are significantly far apart: to register them the Iterative Closes Point (ICP) technique is applied. ICP convergence is fundamentally based on the correct selection of the points to be coupled, and the paper proposes an innovative procedure in which a double density points subset is selected in relation to terrain characteristics. This approach reduces the complexity of the calculation and avoids that flat terrain parts, where most of the original points, are de-facto overweighed. Starting from the original dense cloud, eigenfeatures are extracted for each point and clustering is then performed to group them in two classes connected to terrain geometry, flat terrain or not; two metrics are adopted and compared for k-means clustering, Euclidean and City Block. Segmentation results are evaluated visually and by comparison with manually performed classification; ICP are then performed and the quality of registration is assessed too. The presented results show how the proposed procedure seem capable to register clouds even far apart with a good overall accuracy
Procedures for fast orientation of LEICA ADS40 imagery extended abstract
No full textEvery year environmental disasters such as storms, floods and earthquakes cause thousands of deaths and a great deal of damage around the world; the price to pay in terms of human lives and material damages is always considerable. The scientific community is involved in the endeavour for preventing disaster, monitoring environmental problems and supporting rescue efforts. Geomatics is heavily concerned with all the aspects of disaster management. The paper focuses on the Leica ADS40 digital camera as a tool for performing post-disaster rapid mapping: in particular, the direct georeferencing mode is analyzed. The camera's main characteristics are depicted. Three different case studies are taken into consideration. Productivity and geometric accuracy are assessed
Optimization of Electric Bus Charging: Integrating Discrete Event Modeling in Public Transportation Systems
No full textThe transition to electric transportation is gaining more and more importance in the last years leading to new challenges to be addressed. A key role in this framework is represented by public transportation systems. This paper introduces a Discrete Event (DE) optimization model to optimize the charging scheduling of electric buses (EBs). By accounting for time tabling constraints, energy demand satisfaction, and the capability for simultaneous multi-socket charging, our model addresses the complexities inherent in managing EB fleets. Utilizing a periodic model to capture cyclical system behavior, we incorporate a detailed battery model reflecting nonlinear charging profiles to enhance accuracy in power requirement prediction and charging duration estimation Validation of our model is performed using real-world data, demonstrating its practical applicability. Copyright (C) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/
Assessment of the Completeness of OpenStreetMap and Google Maps for the Province of Pavia (Italy)
No full textFree access web-based mapping is nowadays largely used in several areas such as navigation, location-based services or when it is necessary to obtain quickly geographical information. Some of them are based on volunteers' work, among which OpenStreetMap (OSM), while some others were design for commercial purposes, such as Google Maps (GM). Given the variety of contributors and their heterogeneity, one of the critical aspects of OSM is the homogeneity and quality level of its information; furthermore, GM is also largely consulted but presents inhomogeneity between densely populated and rural areas. The paper aims at analysing the buildings completeness of OSM and GM over the Province of Pavia, in Northern Italy: the applied method will be presented together with the results obtained at two different time frames (spring 2018 and winter 2018). Finally, a quick review about the volunteers that had effectively contributed to OSM will be presented
Assessment of Leica CityMapper-2 LiDAR Data within Milan’s Digital Twin Project
No full textThe digital twin is one of the most promising technologies for realizing smart cities in terms of planning and management. For this purpose, Milan, Italy, has started a project to acquire aerial nadir and oblique images and LiDAR and terrestrial mobile mapping data. The Leica CityMapper-2 hybrid sensor has been used for aerial surveys as it can capture precise and high-resolution multiple data (imagery and LiDAR). The surveying activities are completed, and quality checks are in progress. This paper concerns assessing aerial LiDAR data of a significant part of the metropolitan area, particularly evaluating the accuracy, precision, and congruency between strips and the point density estimation. The analysis has been conducted by exploiting a ground control network of GNSS and terrestrial LiDAR measurements created explicitly for this purpose. The vertical component has an accuracy root mean square error (RMSE) of around 5 cm, and a horizontal component of around 12 cm. Meanwhile, the precision RMSE ranges from 2 to 8 cm. These values are suitable for generating products such as DSM/DTM
Mapping land cover types using sentinel-2 imagery: A case study
No full textThis paper presents a case study of automatic classification of the remotely sensed Sentinel-2 imagery, from the EU Copernicus program. The work involved a study site, located in the area next to the city of Pavia, Italy, including fields cultivated by three farms. The aim of this work was to evaluate the so-called supervised classification applied to satellite images and performed with Esri's ArcGIS Pro software and Machine Learning techniques. The classification performed produces a land use map that is able to discriminate between different land cover types. By applying the Support Vector Machine (SVM) algorithm, it was found that, in our case, the pixel-based method offers a better overall performance than the object-based, unless a specific class is exclusively taken into consideration. This activity represents the first step of a project that fits into the context of Precision Agriculture, a recent and rapidly developing research area, whose aim is to optimize traditional cultivation methods
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