The Exploitation of Data from Remote and Human Sensors for Environment Monitoring in the SMAT Project

Meo, Rosa; Roglia, Elena; Bottino, A.

doi:10.3390/s121217504

Cited by 14 publications

(8 citation statements)

References 40 publications

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“…Unmanned aerial vehicles (UAVs) have low cost, good flexibility, low risk and high efficiency. Therefore, UAVs have been widely used in various tasks, such as modern maritime supervision [1,2], information collecting [3,4], search and rescue [5,6], environmental monitoring [7,8], exploration and mapping [9,10], etc.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification

Xiu

Wen²,

Yuan

et al. 2019

Sensors

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In order to monitor and manage vessels in channels effectively, identification and tracking are very necessary. This work developed a maritime unmanned aerial vehicle (Mar-UAV) system equipped with a high-resolution camera and an Automatic Identification System (AIS). A multi-feature and multi-level matching algorithm using the spatiotemporal characteristics of aerial images and AIS information was proposed to detect and identify field vessels. Specifically, multi-feature information, including position, scale, heading, speed, etc., are used to match between real-time image and AIS message. Additionally, the matching algorithm is divided into two levels, point matching and trajectory matching, for the accurate identification of surface vessels. Through such a matching algorithm, the Mar-UAV system is able to automatically identify the vessel’s vision, which improves the autonomy of the UAV in maritime tasks. The multi-feature and multi-level matching algorithm has been employed for the developed Mar-UAV system, and some field experiments have been implemented in the Yangzi River. The results indicated that the proposed matching algorithm and the Mar-UAV system are very significant for achieving autonomous maritime supervision.

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Section: Introductionmentioning

confidence: 99%

A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification

Xiu

Wen²,

Yuan

et al. 2019

Sensors

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“…The unmanned aircraft system (UAS) can be used as a supplementary resort to manned aerial photography and SRS because of its unique advantages such as being real time, flexible, high image resolution, and low cost. It refers to a class of aircrafts which can easily and safely fly without the onboard presence of a pilot [5][6][7][8][9] and can offer several opportunities in disaster-related situations when equipped with RS instrumentations [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Development of an UAS for Earthquake Emergency Response and Its Application in Two Disastrous Earthquakes

Peng¹,

Xu²,

Yang³

et al. 2018

Earthquakes - Forecast, Prognosis and Earthquake Resistant Construction

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To support humanitarian action after a disaster, we require reliable data like high-resolution satellite images for analyses aimed to define the damages of facilities and/or infrastructures. However, we cannot obtain satellite images in few days after an event. Thus, in situ surveys are preferred. Advances in unmanned aircraft system (UAS) have promoted them to become precious tools for capturing and assessing the extents and volume of damages. Safety, flexibility, low cost, and ease of operation make UAS suitable for disaster assessment. In this chapter, we developed an example of UAS for swiftly acquiring disaster information. With the selected fixed-wing UAS, we successfully performed data acquisition at specified scales. For the image analysis, we applied a photogrammetric workflow to deal with the very high resolution of the images obtained without ground control points. The results obtained from two destructive earthquakes demonstrated that the presented system plays a key role on the processes of investigating and gathering information about a disaster in the earthquake epicentral areas, like road detection, structural damage survey, secondary disaster investigation, and quick disaster assessment. It can effectively provide disaster information in hardly entered areas to salvation headquarters for rapidly developing the relief measures.

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“…The descriptive prominence of a venue is computed using the concept of contrast from background. Meo et al [4] propose a statistical approach to estimate the spatial characterization of an area considering the surroundings without imposing a priori knowledge on the geographic area characterization. An area is then marked depending on the statistical distribution of the observed features gathered from OpenStreetMap.…”

Section: Introductionmentioning

confidence: 99%

Geographic Summaries from Crowdsourced Data

Rizzo

Falcone

Meo

et al. 2014

Lecture Notes in Computer Science

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Abstract. In this paper, we present a research prototype for creating geographic summaries using the whereabouts of Foursquare users. Exploiting the density of the venue types in a particular region, the system adds a layer over any typical cartography geographic maps service, creating a first glance summary over the venues sampled from the Foursquare knowledge base. Each summary is represented by a convex hull. The shape is automatically computed according to the venue densities enclosed in the area. The summary is then labeled with the most prominent category or categories. The prominence is given by the observed venue category density. The prototype provides two outputs: a light-weight representation structured in GeoJSON, and a semantic description using the Open Annotation Ontology. We evaluate the quality of the summaries using the Sum of Squared Errors (SSE) and the Jaccard distance. The system is available at http://geosummly.eurecom.fr.

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The Exploitation of Data from Remote and Human Sensors for Environment Monitoring in the SMAT Project

Cited by 14 publications

References 40 publications

A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification

A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification

Development of an UAS for Earthquake Emergency Response and Its Application in Two Disastrous Earthquakes

Geographic Summaries from Crowdsourced Data

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