UAV-based multitemporal remote sensing surveys of volcano unstable flanks: a case study from Stromboli

UAV-based photogrammetry is becoming increasingly popular even in application fields that, until recently, were deemed unsuitable for this technique. Depending on the characteristics of the investigated scenario, the generation of three-dimensional (3D) topographic models may in fact be affected by significant inaccuracies unless site-specific adaptations are implemented into the data collection and processing routines. In this paper, an ad hoc procedure to exploit high-resolution aerial photogrammetry for the multitemporal analysis of the unstable Sciara del Fuoco (SdF) slope at Stromboli Island (Italy) is presented. Use of the technique is inherently problematic because of the homogeneous aspect of the gray ash slope, which prevents a straightforward identification of match points in continuous frames. Moreover, due to site accessibility restrictions enforced by local authorities after the volcanic paroxysm in July 2019, Ground Control Points (GCPs) cannot be positioned to constrain georeferencing. Therefore, all 3D point clouds were georeferenced using GCPs acquired in a 2019 (pre-paroxysm) survey, together with stable Virtual Ground Control Points (VGCPs) belonging to a LiDAR survey carried out in 2012. Alignment refinement was then performed by means of an iterative algorithm based on the closest points. The procedure succeeded in correctly georeferencing six high-resolution point clouds acquired from April 2017 to July 2021, whose time-focused analysis made it possible to track several geomorphological structures associated with the continued volcanic activity. The procedure can be further extended to smaller-scale analyses such as the estimation of locally eroded/accumulated volumes and pave the way for rapid UAV-based georeferenced surveys in emergency conditions at the SdF

Low cost infrared and near infrared sensors for UAVs

Thermal remote sensing has a wide range of applications, though the extent of its use is inhibited by cost. Robotic and computer components are now widely available to consumers on a scale that makes thermal data a readily accessible resource. In this project, thermal imagery collected via a lightweight remote sensing Unmanned Aerial Vehicle (UAV) was used to create a surface temperature map for the purpose of providing wildland firefighting crews with a cost-effective and time-saving resource. The UAV system proved to be flexible, allowing for customized sensor packages to be designed that could include visible or infrared cameras, GPS, temperature sensors, and rangefinders, in addition to many data management options. Altogether, such a UAV system could be used to rapidly collect thermal and aerial data, with a geographic accuracy of less than one meter

Optimization of Three-Dimensional (3D) Multi-Sensor Models For Damage Assessment in Emergency Context: Rapid Mapping Experiences in the 2016 Italian Earthquake

Geomatics techniques offer the chance to manage very cost-effective solutions for three-dimensional (3D) modelling, from both the aerial and terrestrial point of view, with the help of range and image-based sensors. 3D spatial data that is based on integrated documentation techniques, featured by a very high-scale and an accurate metric and radiometric information nowadays are proposed here as metric databases that are applicable for assisting the operative fieldwork in the case of rapid mapping strategies. In sudden emergency contexts for damage and risk assessment, the structural consolidation and the security measures operations meet the problem of the danger and accessibility constraints of areas, for the operators, as well as to the tight deadlines needs in first aid. The use of Unmanned Aerial Vehicles (UAVs) equipped with cameras are more and more involved in aerial survey and reconnaissance missions; at the same time, the ZEB1 portable Light Detection and Ranging (LiDAR) mapping solution implemented in handle tools helped by Simultaneous Localization And Mapping (SLAM) algorithms can help for a quick preliminary survey. Both of these approaches that are presented here in the critical context of a post-seismic event, which is Pescara del Tronto (AP), deeply affected by the 2016-2017 earthquake in Central Italy. The Geomatics research group and the Disaster Recovery team (DIRECT—http://areeweb.polito.it/direct/) is working in collaboration with the Remotely Piloted Aircraft Systems (RPAS) group of the Italian Firefighter

Multi-Temporal Image Co-Registration Of Uav Blocks: A Comparison Of Different Approaches

Traditionally, data co-registration of survey epochs in photogrammetry relied on Ground Control Points (GCP) to keep the reference system unchanged. In the last years, Unmanned Aerial Systems (UAV) are increasingly used in photogrammetric environmental monitoring. The diffusion of affordable UAV platforms equipped with GNSS (Global Navigation Satellite System) centimetre-grade receivers might reduce, but not eliminate, the need for GCP. Conversely, if GNSS-assisted orientation cannot be used or if additional ground control and reliability checks are required, alternatives to repeated GCP survey have been proposed, taking advantage of Structure from Motion (SfM) photogrammetry. In particular, co-registering different epochs image blocks together, identifying corresponding features, has been demonstrated as a viable and efficient approach. In this paper four different strategies easily implementable in a generic commercial photogrammetric software are presented and compared considering three different test sites in Italy subject to different amounts of environmental changes. The influence of the amount and distribution of inter-epoch corresponding points on the accuracy of the reconstruction is investigated. The results show that some of the tested strategies obtains very good results and can be used (although not needed) also in RTK centimetre-grade UAV surveys, leveraging the additional information coming from previous epochs survey to actually increase the survey accuracy and reliability

MULTI-TEMPORAL IMAGE CO-REGISTRATION OF UAV BLOCKS: A COMPARISON OF DIFFERENT APPROACHES

Abstract. Traditionally, data co-registration of survey epochs in photogrammetry relied on Ground Control Points (GCP) to keep the reference system unchanged. In the last years, Unmanned Aerial Systems (UAV) are increasingly used in photogrammetric environmental monitoring. The diffusion of affordable UAV platforms equipped with GNSS (Global Navigation Satellite System) centimetre-grade receivers might reduce, but not eliminate, the need for GCP. Conversely, if GNSS-assisted orientation cannot be used or if additional ground control and reliability checks are required, alternatives to repeated GCP survey have been proposed, taking advantage of Structure from Motion (SfM) photogrammetry. In particular, co-registering different epochs image blocks together, identifying corresponding features, has been demonstrated as a viable and efficient approach. In this paper four different strategies easily implementable in a generic commercial photogrammetric software are presented and compared considering three different test sites in Italy subject to different amounts of environmental changes. The influence of the amount and distribution of inter-epoch corresponding points on the accuracy of the reconstruction is investigated. The results show that some of the tested strategies obtains very good results and can be used (although not needed) also in RTK centimetre-grade UAV surveys, leveraging the additional information coming from previous epochs survey to actually increase the survey accuracy and reliability

Micro Aerial Vehicles (MAV) Assured Navigation in Search and Rescue Missions Robust Localization, Mapping and Detection

This Master's Thesis describes the developments on robust localization, mapping and detection algorithms for Micro Aerial Vehicles (MAVs). The localization method proposes a seamless indoor-outdoor multi-sensor architecture. This algorithm is capable of using all or a subset of its sensor inputs to determine a platform's position, velocity and attitude (PVA). It relies on the Inertial Measurement Unit as the core sensor and monitors the status and observability of the secondary sensors to select the most optimum estimator strategy for each situation. Furthermore, it ensures a smooth transition between filters structures. This document also describes the integration mechanism for a set of common sensors such as GNSS receivers, laser scanners and stereo and mono cameras. The mapping algorithm provides a fully automated fast aerial mapping pipeline. It speeds up the process by pre-selecting the images using the flight plan and the onboard localization. Furthermore, it relies on Structure from Motion (SfM) techniques to produce an optimized 3D reconstruction of camera locations and sparse scene geometry. These outputs are used to compute the perspective transformations that project the raw images on the ground and produce a geo-referenced map. Finally, these maps are fused with other domains in a collaborative UGV and UAV mapping algorithms. The real-time aerial detection of victims is based on a thermal camera. The algorithm is composed by three steps. Firstly, a normalization of the image is performed to get rid of the background and to extract the regions of interest. Later the victim detection and tracking steps produce the real-time geo-referenced locations of the detections. The thesis also proposes the concept of a MAV Copilot, a payload composed by a set of sensors and algorithm the enhances the capabilities of any commercial MAV. To develop and validate these contributions, a prototype of a search and rescue MAV and the Copilot has been developed. These developments have been validated in three large-scale demonstrations of search and rescue operations in the context of the European project ICARUS: a shipwreck in Lisbon (Portugal), an earthquake in Marche (Belgium), and the Fukushima nuclear disaster in the euRathlon 2015 competition in Piombino (Italy)

Image Stitching for UAV remote sensing application

The objective of the project is to write an algorithm that is able to join top view images to create a big map. The project is done in the School of Castelldefels of UPC, within the research laboratory Icarus of EETAC Faculty. The goal of the project is to detect an area of this map, thanks to the analysis of this images. The images are taken by the two camera aboard on an Unmanned Aerial Vehicle (UAV) built by the Icarus group leaded by Enric Pastor. The implemented code is uploaded in Upc' svn at the adress: https://svn.fib.upc.es/svn/vincenzo.can

A Comprehensive Review of AI-enabled Unmanned Aerial Vehicle: Trends, Vision , and Challenges

In recent years, the combination of artificial intelligence (AI) and unmanned aerial vehicles (UAVs) has brought about advancements in various areas. This comprehensive analysis explores the changing landscape of AI-powered UAVs and friendly computing in their applications. It covers emerging trends, futuristic visions, and the inherent challenges that come with this relationship. The study examines how AI plays a role in enabling navigation, detecting and tracking objects, monitoring wildlife, enhancing precision agriculture, facilitating rescue operations, conducting surveillance activities, and establishing communication among UAVs using environmentally conscious computing techniques. By delving into the interaction between AI and UAVs, this analysis highlights the potential for these technologies to revolutionise industries such as agriculture, surveillance practices, disaster management strategies, and more. While envisioning possibilities, it also takes a look at ethical considerations, safety concerns, regulatory frameworks to be established, and the responsible deployment of AI-enhanced UAV systems. By consolidating insights from research endeavours in this field, this review provides an understanding of the evolving landscape of AI-powered UAVs while setting the stage for further exploration in this transformative domain

Hydrogeomorphological analysis and modelling for a comprehensive understanding of flash-flood damage processes: the 9 October 2018 event in northeastern Mallorca

[EN] A flash-flood event hit the northeastern part of Mallorca on 9 October 2018, causing 13 casualties. Mal- lorca is prone to catastrophic flash floods acting on a sce- nario of deep landscape transformation caused by Mediter- ranean tourist resorts. As global change may exacerbate dev- astating flash floods, analyses of catastrophic events are cru- cial to support effective prevention and mitigation measures. Field-based remote-sensing and modelling techniques were used in this study to evaluate rainfall¿runoff processes at the catchment scale linked to hydrological modelling. Continu- ous streamflow monitoring data revealed a peak discharge of 442 m³ s¿¹ with an unprecedented runoff response. This ex- ceptional behaviour triggered the natural disaster as a com- bination of heavy rainfall (249 mm in 10 h), karstic features and land cover disturbances in the Begura de Salma River catchment (23 km²). Topography-based connectivity indices and geomorphic change detection were used as rapid post- catastrophe decision-making tools, playing a key role dur- ing the rescue search. These hydrogeomorphological preci- sion techniques were combined with the Copernicus Emer- gency Management Service and ¿ground-based¿ damage as- sessment, which showed very accurately the damage-driving factors in the village of Sant Llorenç des Cardassar. The main challenges in the future are to readapt hydrological modelling to global change scenarios, implement an early flash-flood warning system and take adaptive and resilient measures on the catchment scale.This research was supported by the Spanish Ministry of Science, Innovation and Universities, the Spanish Agency of Research (AEI) and the European Regional Development Fund (ERDF) through the project CGL2017-88200-R "Functional hydrological and sediment connectivity at Mediterranean catchments: global change scenarios -MEDhyCON2".Estrany, J.; Ruiz-Perez, M.; Mutzner, R.; Fortesa, J.; Nacher Rodriguez, B.; Tomas-Burguera, M.; Garcia-Comendador, J.... (2020). Hydrogeomorphological analysis and modelling for a comprehensive understanding of flash-flood damage processes: the 9 October 2018 event in northeastern Mallorca. 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