Using Airborne Remote Sensing to Increase Situational Awareness  in Civil Protection and Humanitarian Relief – The Importance of  User Involvement

Römer, Hannes; Kiefl, Ralph; Henkel, Fabian; Wenxi, C.; Nippold, Ronald; Kurz, Franz; Kippnich, Uwe

doi:10.5194/isprs-archives-xli-b8-1363-2016

Cited by 7 publications

(10 citation statements)

References 9 publications

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“…In preparation for missions, the derivation of a surface model shortly before or even during the event would make it possible to assess even temporary constructions on site, and help emergency forces prepare [13]. During the event, it is important to maintain an overview of the site and its utilization capacity [19]. The capacity (number of persons) is valuable information when it comes to the organization of supply and evacuation measures.…”

Section: D Data From Optical Remote Sensing For Crisis and Event Manmentioning

confidence: 99%

2D vs. 3D Change Detection Using Aerial Imagery to Support Crisis Management of Large-Scale Events

et al. 2018

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Large-scale events represent a special challenge for crisis management. To ensure that participants can enjoy an event safely and carefree, it must be comprehensively prepared and attentively monitored. Remote sensing can provide valuable information to identify potential risks and take appropriate measures in order to prevent a disaster, or initiate emergency aid measures as quickly as possible in the event of an emergency. Especially, three-dimensional (3D) information that is derived using photogrammetry can be used to analyze the terrain and map existing structures that are set up at short notice. Using aerial imagery acquired during a German music festival in 2016 and the celebration of the German Protestant Church Assembly of 2017, the authors compare two-dimensional (2D) and novel fusion-based 3D change detection methods, and discuss their suitability for supporting large-scale events during the relevant phases of crisis management. This study serves to find out what added value the use of 3D change information can provide for on-site crisis management. Based on the results, an operational, fully automatic processor for crisis management operations and corresponding products for end users can be developed.

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Section: D Data From Optical Remote Sensing For Crisis and Event Manmentioning

confidence: 99%

2D vs. 3D Change Detection Using Aerial Imagery to Support Crisis Management of Large-Scale Events

et al. 2018

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“…In the Earth Observation (EO) field, there is a large variety of Remote Sensing (RS) data sets that represent a precious resource for SA applications. RS actually plays a central role for the interpretation of the environment and can be used as an auxiliary tool for an effective decision-making [7][8][9][10][11]. The RS analyst derives information from RS data to reduce the uncertainties associated with standard geospatial intelligence.…”

Section: Introductionmentioning

confidence: 99%

“…This early-warning system exploits airborne remote sensing and in situ data collections for providing terrestrial traffic data. This service aids public offices and organizations with security responsibilities and traffic authorities when dealing with disasters and large public events [9]. As an example, more recently, in 2019, DLR organized a test in The Hague, The Netherlands, for assessing the role of VABENE++ to support disaster response tasks in a large-scale flooding scenario [11].…”

Section: Introductionmentioning

confidence: 99%

Situational Awareness of Large Infrastructures Using Remote Sensing: The Rome–Fiumicino Airport during the COVID-19 Lockdown

Pulella

Sica

2021

Remote Sensing

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Situational awareness refers to the process of aggregating spatio-temporal variables and measurements from different sources, aiming to improve the semantic outcome. Remote Sensing satellites for Earth Observation acquire key variables that, when properly aggregated, can provide precious insights about the observed area. This article introduces a novel automatic system to monitor the activity levels and the operability of large infrastructures from satellite data. We integrate multiple data sources acquired by different spaceborne sensors, such as Sentinel-1 Synthetic Aperture Radar (SAR) time series, Sentinel-2 multispectral data, and Pleiades Very-High-Resolution (VHR) optical data. The proposed methodology exploits the synergy between these sensors for extracting, at the same time, quantitative and qualitative results. We focus on generating semantic results, providing situational awareness, and decision-ready insights. We developed this methodology for the COVID-19 Custom Script Contest, a remote hackathon funded by the European Space Agency (ESA) and the European Commission (EC), whose aim was to promote remote sensing techniques to monitor environmental factors consecutive to the spread of the Coronavirus disease. This work focuses on the Rome–Fiumicino International Airport case study, an environment significantly affected by the COVID-19 crisis. The resulting product is a unique description of the airport’s area utilization before and after the air traffic restrictions imposed between March and May 2020, during Italy’s first lockdown. Experimental results confirm that the proposed algorithm provides remarkable insights for supporting an effective decision-making process. We provide results about the airport’s operability by retrieving temporal changes at high spatial and temporal resolutions, together with the airplane count and localization for the same period in 2019 and 2020. On the one hand, we detected an evident change of the activity levels on those airport areas typically designated for passenger transportation, e.g., the one close to the gates. On the other hand, we observed an intensification of the activity levels over areas usually assigned to landside operations, e.g., the one close to the hangar. Analogously, the airplane count and localization have shown a redistribution of the airplanes over the whole airport. New parking slots have been identified as well as the areas that have been dismissed. Eventually, by combining the results from different sensors, we could affirm that different airport surface areas have changed their functionality and give a non-expert interpretation about areas’ usage.

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“…In order to prevent situations of danger or damage at large events and to be able to act quickly and effectively in an emergency, decision-makers need information with spatial reference for a situation picture that is as close to reality as possible during the event. Due to the increasing availability of high resolution remote sensing data and the growing awareness of the possibility of deriving area-wide information from it, this is more and more being integrated into disaster management procedures (Aina, Bello, 2014, Römer et al, 2016. In the event of an emergency, it must be ensured that rescue routes are wide enough and, above all, free of any objects that would obstruct the passability of the emergency services and that participants can leave the site at any time.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, an end-to-end monitoring system has been developed, improved and tested under real world conditions and was successfully demonstrated at several large scale events (Römer et al, 2016). It aims to support the management of events and authorities in charge of security and rescuing effort by recording and providing optical aerial imagery and relevant derived information.…”

Section: Introductionmentioning

confidence: 99%

Automatic Object Segmentation to Support Crisis Management of Large-Scale Events

Azimi

Kiefl

Gstaiger

et al. 2021

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. The management of large-scale events with a widely distributed camping area is a special challenge for organisers and security forces and requires both comprehensive preparation and attentive monitoring to ensure the safety of the participants. Crucial to this is the availability of up-to-date situational information, e.g. from remote sensing data. In particular, information on the number and distribution of people is important in the event of a crisis in order to be able to react quickly and effectively manage the corresponding rescue and supply logistics. One way to estimate the number of persons especially at night is to classify the type and size of objects such as tents and vehicles on site and to distinguish between objects with and without a sleeping function. In order to make this information available in a timely manner, an automated situation assessment is required. In this work, we have prepared the first high-quality dataset in order to address the aforementioned challenge which contains aerial images over a large-scale festival of different dates. We investigate the feasibility of this task using Convolutional Neural Networks for instance-wise semantic segmentation and carry out several experiments using the Mask-RCNN algorithm and evaluate the results. Results are promising and indicate the possibility of function-based tent classification as a proof-of-concept. The results and thereof discussions can pave the way for future developments and investigations.

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Using Airborne Remote Sensing to Increase Situational Awareness in Civil Protection and Humanitarian Relief – The Importance of User Involvement

Cited by 7 publications

References 9 publications

2D vs. 3D Change Detection Using Aerial Imagery to Support Crisis Management of Large-Scale Events

2D vs. 3D Change Detection Using Aerial Imagery to Support Crisis Management of Large-Scale Events

Situational Awareness of Large Infrastructures Using Remote Sensing: The Rome–Fiumicino Airport during the COVID-19 Lockdown

Automatic Object Segmentation to Support Crisis Management of Large-Scale Events

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