scholarly journals OBJECTS GROUPING FOR SEGMENTATION OF ROADS NETWORK IN HIGH RESOLUTION IMAGES OF URBAN AREAS

2016 ◽  
Vol XLI-B7 ◽  
pp. 897-902 ◽  
Author(s):  
M. Maboudi ◽  
J. Amini ◽  
M. Hahn
Keyword(s):  
Image Analysis ◽  
High Resolution ◽  
Urban Areas ◽  
Traffic Management ◽  
Large Scale ◽  
Route Planning ◽  
Technological Advancement ◽  
Image Objects ◽  
High Resolution Images ◽  
Road Segments

Updated road databases are required for many purposes such as urban planning, disaster management, car navigation, route planning, traffic management and emergency handling. In the last decade, the improvement in spatial resolution of VHR civilian satellite sensors – as the main source of large scale mapping applications – was so considerable that GSD has become finer than size of common urban objects of interest such as building, trees and road parts. This technological advancement pushed the development of “Object-based Image Analysis (OBIA)” as an alternative to pixel-based image analysis methods. <br><br> Segmentation as one of the main stages of OBIA provides the image objects on which most of the following processes will be applied. Therefore, the success of an OBIA approach is strongly affected by the segmentation quality. In this paper, we propose a purpose-dependent refinement strategy in order to group road segments in urban areas using maximal similarity based region merging. For investigations with the proposed method, we use high resolution images of some urban sites. The promising results suggest that the proposed approach is applicable in grouping of road segments in urban areas.

scholarly journals OBJECTS GROUPING FOR SEGMENTATION OF ROADS NETWORK IN HIGH RESOLUTION IMAGES OF URBAN AREAS

2016 ◽  
Vol XLI-B7 ◽  
pp. 897-902 ◽  
Author(s):  
M. Maboudi ◽  
J. Amini ◽  
M. Hahn
Keyword(s):  
Image Analysis ◽  
High Resolution ◽  
Urban Areas ◽  
Traffic Management ◽  
Large Scale ◽  
Route Planning ◽  
Technological Advancement ◽  
Image Objects ◽  
High Resolution Images ◽  
Road Segments

Updated road databases are required for many purposes such as urban planning, disaster management, car navigation, route planning, traffic management and emergency handling. In the last decade, the improvement in spatial resolution of VHR civilian satellite sensors – as the main source of large scale mapping applications – was so considerable that GSD has become finer than size of common urban objects of interest such as building, trees and road parts. This technological advancement pushed the development of “Object-based Image Analysis (OBIA)” as an alternative to pixel-based image analysis methods. &lt;br&gt;&lt;br&gt; Segmentation as one of the main stages of OBIA provides the image objects on which most of the following processes will be applied. Therefore, the success of an OBIA approach is strongly affected by the segmentation quality. In this paper, we propose a purpose-dependent refinement strategy in order to group road segments in urban areas using maximal similarity based region merging. For investigations with the proposed method, we use high resolution images of some urban sites. The promising results suggest that the proposed approach is applicable in grouping of road segments in urban areas.

scholarly journals High Resolution Satellite Images for Instantaneous Shoreline Extraction Using New Enhancement Algorithms

Geosciences ◽  
2019 ◽  
Vol 9 (3) ◽  
pp. 123 ◽  
Author(s):  
Donatella Dominici ◽  
Sara Zollini ◽  
Maria Alicandro ◽  
Francesca Della Torre ◽  
Paolo Buscema ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Satellite Images ◽  
Human Life ◽  
Essential Element ◽  
Action Planning ◽  
High Resolution Satellite Images ◽  
High Resolution Images ◽  
Territorial Government ◽  
Very High

Knowledge of a territory is an essential element in any future planning action and in appropriate territorial and environmental requalification action planning. The current large-scale availability of satellite data, thanks to very high resolution images, provides professional users in the environmental, urban planning, engineering, and territorial government sectors, in general, with large amounts of useful data with which to monitor the territory and cultural heritage. Italy is experiencing environmental emergencies, and coastal erosion is one of the greatest threats, not only to the Italian heritage and economy, but also to human life. The aim of this paper is to find a rapid way of identifying the instantaneous shoreline. This possibility could help government institutions such as regions, civil protection, etc., to analyze large areas of land quickly. The focus is on instantaneous shoreline extraction in Ortona (CH, Italy), without considering tides, using WorldView-2 satellite images (50-cm resolution in panchromatic and 2 m in multispectral). In particular, the main purpose of this paper is to compare commercial software and ACM filters to test their effectiveness.

Image analysis for measuring lichen colonization on and within stonework

2009 ◽  
Vol 41 (3) ◽  
pp. 299-313 ◽  
Author(s):  
Claudia GAZZANO ◽  
Sergio E. FAVERO-LONGO ◽  
Enrica MATTEUCCI ◽  
Rosanna PIERVITTORI
Keyword(s):  
Image Analysis ◽  
High Resolution ◽  
Cultural Heritage ◽  
Cross Sections ◽  
Periodic Acid ◽  
Lichen Species ◽  
Pixel Classification ◽  
Percentage Cover ◽  
Periodic Acid Schiff ◽  
High Resolution Images

AbstractThe suitability of image analysis by colour-based pixel classification to quantify lichen colonization on the surface of and within marble, travertine and mortar stonework has been investigated. High resolution images of lichenized stonework surfaces were acquired at different field sites using a scanner, thus avoiding invasive surveys, and the percentage cover of lichen species was subsequently measured in the laboratory using dedicated software. Furthermore, microphotographs of polished cross-sections of lichenized marble, travertine and mortar, stained using the periodic acid-Schiff (PAS) method to visualize hyphae, were produced by the same software to quantify hyphal spread within the substratum, a parameter which can be used more successfully than the commonly used depth of hyphal penetration to quantify how much the lichen has affected the conservation of a stone substratum. Significant statistical differences in hue, saturation and intensity (HSI) of the lichen thalli and PAS-stained hyphae, with respect to the lithic substrata, allowed the software to discriminate and quantify the lichen species cover on, and hyphal spread within, the three investigated lithotypes. Since such a quantitative approach highlights the volume of influence of lichens on stonework, where bioweathering processes are likely to develop, it could be used to support decisions on the preservation of our stone cultural heritage.

scholarly journals CITYWIDE ESTIMATION OF PARKING SPACE USING AERIAL IMAGERY AND OSM DATA FUSION WITH DEEP LEARNING AND FINE-GRAINED ANNOTATION

2021 ◽  
Vol XLIII-B2-2021 ◽  
pp. 479-485
Author(s):  
C. Henry ◽  
J. Hellekes ◽  
N. Merkle ◽  
S. M. Azimi ◽  
F. Kurz
Keyword(s):  
Data Fusion ◽  
Urban Areas ◽  
Traffic Management ◽  
Large Scale ◽  
Private Property ◽  
Contextual Information ◽  
Aerial Imagery ◽  
Parking Space ◽  
Fine Grained ◽  
Actual Use

Abstract. Emerging traffic management technologies, smart parking applications, together with transport researchers and urban planners are interested in fine-grained data on parking space in cities. However, there are no standardized, complete and up-to-date databases for many urban areas. Moreover, manual data collection is expensive and time-consuming. Aerial imagery of entire cities can be used to inventory not only publicly accessible and dedicated parking lots, but also roadside parking areas and those on private property. For a realistic estimation of the total parking space, the observed use of multi-functional traffic areas is taken into account by segmenting not only parking areas but also roads according to their purpose. In this paper, different U-Net based architectures are tested for detecting all these types of visible traffic areas. A new large-scale, high-quality dataset of manual annotations is used in combination with selected contextual information from OpenStreetMap (OSM) to depict the actual use as parking space. Our models achieve a good performance on parking area segmentation, and we show the significant impact of OSM data fusion in deep neural networks on the simultaneous extraction of multiple traffic areas compared to using aerial imagery alone.

scholarly journals Trialing Innovative Technologies in Crisis Management—“Airborne and Terrestrial Situational Awareness” as Support Tool in Flood Response

2020 ◽  
Vol 10 (11) ◽  
pp. 3743 ◽  
Author(s):  
Elisa Schröter ◽  
Ralph Kiefl ◽  
Eric Neidhardt ◽  
Gaby Gurczik ◽  
Carsten Dalaff ◽  
...  
Keyword(s):  
Crisis Management ◽  
Urban Areas ◽  
Large Scale ◽  
New Technologies ◽  
Situational Awareness ◽  
Route Planning ◽  
Added Value ◽  
Aerial Image ◽  
Specific Response ◽  
Test Bed

Flooding represents the most-occurring and deadliest threats worldwide among natural disasters. Consequently, new technologies are constantly developed to improve response capacities in crisis management. The remaining challenge for practitioner organizations is not only to identify the best solution to their individual demands, but also to test and evaluate its benefit in a realistic environment before the disaster strikes. To bridge the gap between theoretic potential and actual integration into practice, the EU-funded project DRIVER+ has designed a methodical and technical environment to assess innovation in a realistic but non-operational setup through trials. The German Aerospace Center (DLR) interdisciplinary merged mature technical developments into the “Airborne and terrestrial situational awareness” system and applied it in a DRIVER+ Trial to promote a sustainable and demand-oriented R&D. Experienced practitioners assessed the added value of its modules “KeepOperational” and “ZKI” in the context of large-scale flooding in urban areas. The solution aimed at providing contextual route planning in police operations and extending situational awareness based on information derived through aerial image processing. The user feedback and systematically collected data through the DRIVER + Test-bed approved that DLR’s system could improve transport planning and situational awareness across organizations. However, the results show a special need to consider, for example, cross-domain data-fusion techniques to provide essential 3D geo-information to effectively support specific response tasks during flooding.

scholarly journals Accident Management System Based on Vehicular Network for an Intelligent Transportation System in Urban Environments

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Yusor Rafid Bahar Al-Mayouf ◽  
Omar Adil Mahdi ◽  
Namar A. Taha ◽  
Nor Fadzilah Abdullah ◽  
Suleman Khan ◽  
...  
Keyword(s):  
Real Time ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Traffic Management ◽  
Management System ◽  
Vehicular Ad Hoc Networks ◽  
Road Traffic ◽  
Route Planning ◽  
Accident Management ◽  
Planning Algorithm

As cities across the world grow and the mobility of populations increases, there has also been a corresponding increase in the number of vehicles on roads. The result of this has been a proliferation of challenges for authorities with regard to road traffic management. A consequence of this has been congestion of traffic, more accidents, and pollution. Accidents are a still major cause of death, despite the development of sophisticated systems for traffic management and other technologies linked with vehicles. Hence, it is necessary that a common system for accident management is developed. For instance, traffic congestion in most urban areas can be alleviated by the real-time planning of routes. However, the designing of an efficient route planning algorithm to attain a globally optimal vehicle control is still a challenge that needs to be solved, especially when the unique preferences of drivers are considered. The aim of this paper is to establish an accident management system that makes use of vehicular ad hoc networks coupled with systems that employ cellular technology in public transport. This system ensures the possibility of real-time communication among vehicles, ambulances, hospitals, roadside units, and central servers. In addition, the accident management system is able to lessen the amount of time required to alert an ambulance that it is required at an accident scene by using a multihop optimal forwarding algorithm. Moreover, an optimal route planning algorithm (ORPA) is proposed in this system to improve the aggregate spatial use of a road network, at the same time bringing down the travel cost of operating a vehicle. This can reduce the incidence of vehicles being stuck on congested roads. Simulations are performed to evaluate ORPA, and the results are compared with existing algorithms. The evaluation results provided evidence that ORPA outperformed others in terms of average ambulance speed and travelling time. Finally, our system makes it easier for ambulance to quickly make their way through traffic congestion so that the chance of saving lives is increased.

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