In traffic operations, the aim of transportation agencies and researchers is typically to reduce congestion and improve safety. To attain these goals, agencies need continuous and accurate information about the traffic situation. Level-of-Service (LO...
This study reflects on the quality aspects of urban meteorological time series obtained by crowdsourcing, specifically the air temperature and humidity data originating from personal weather stations (PWS) and the related implications for empirical a...
Traditional methods of counting bicyclists are resource-intensive and generate data with sparse spatial and temporal detail. Previous research suggests big data from crowdsourced fitness apps offer a new source of bicycling data with high spatial and...
With the development of location-aware devices and the success and high use of Web 2.0 techniques, citizens are able to act as sensors by contributing geographic information. In this context, data quality is an important aspect that should be taken i...
For many environmental applications, an accurate spatial mapping of land cover is a major concern. Currently, land cover products derived from satellite data are expected to offer a fast and inexpensive way of mapping large areas. However, the qualit...
Identifying road segments with a high crash incidence is essential for improving road safety. Conventional methods for detecting these segments rely on historical data from various sensors, which may inadequately capture rapidly changing road conditi...
Crowdsourced data have played an increasing role in research in the sciences over the past decades. From their early instantiations in the 1990s to the search for extraterrestrial intelligence, the concepts of crowdsourcing and citizen science have g...
Maintaining the data freshness and completeness of road intersection information is the key task of urban road map production and updating. Compared to professional surveying methods, crowdsourced trajectory data provide a low-cost, wide-coverage and...
The concept of crowdsourcing is nowadays extensively used to refer to the collection of data and the generation of information by large groups of users/contributors. OpenStreetMap (OSM) is a very successful example of a crowd-sourced geospatial data...
The proliferation of smartphones and internet connectivity has provided the opportunity to use crowdsourced data in traffic management. Nowadays, many people use navigation apps such as Google Maps, Waze, and Flitsmeister to obtain real-time travel i...
Vehicle localization using mounted sensors is an essential technology for various applications, including autonomous vehicles and road mapping. Achieving high positioning accuracy through the fusion of low-cost sensors is a topic of considerable inte...
Crowdsourced online food images, when combined with food image recognition technologies, have the potential to offer a cost-effective and scalable solution for the assessment of the restaurant nutrition environment. While previous research has explor...
Identification of traffic crash hot spots is of great importance for improving roadway safety and maintaining the transportation system’s sustainability. Traditionally, police crash reports (PCR) have been used as the primary source of crash da...
In recent years, the rapid development of autonomous driving and intelligent driver assistance has brought about urgent demands on high-precision road maps. However, traditional road map production methods mainly rely on professional survey technolog...
Image classification is a fundamental task in remote sensing image processing. In recent years, deep convolutional neural networks (DCNNs) have experienced significant breakthroughs in natural image recognition. The remote sensing field, however, is...
Crowdsourced data (CSD) generated by citizens is becoming more popular as its potential utilization in many applications increases due to its currency and availability. However, the quality of CSD, including its relevance, is often questioned as the...
Data labeling systems are designed to facilitate the training and validation of machine learning algorithms under the umbrella of crowdsourcing practices. The current paper presents a novel approach for designing a customized data labeling system, em...
The COVID-19 pandemic affected many aspects of human mobility and resulted in unprecedented changes in population dynamics, including lifestyle and mobility. Recognizing the effects of the pandemic is crucial to understand changes and mitigate negati...
Traces collected by citizens using GNSS (Global Navigation Satellite System) devices during sports activities such as running, hiking or biking are now widely available through different sport-oriented collaborative websites. The traces are collected...
The generation of road interchange networks benefits various applications, such as vehicle navigation and intelligent transportation systems. Traditional methods often focus on common road structures but fail to fully utilize long-term trajectory con...
In the quest to understand urban ecosystems, traditional evaluation techniques often fall short due to incompatible data sources and the absence of comprehensive, real-time data. However, with the recent surge in the availability of crowdsourced data...
To reduce environmental noise pollution and to safeguard people’s well-being, it is urgently necessary to move towards sustainable urban development and reconcile demographic and economic growth with the protection and restoration of the environment...
8 March 2017
With the development of information and communications technology, user-generated content and crowdsourced data are playing a large role in studies of transport and public health. Recently, Strava, a popular website and mobile app dedicated to tracki...
Due to the complexity of outdoor environments, we still face challenges in collecting up-to-date outdoor road network maps because of high data collection costs, resulting in a lack of navigation road network maps in outdoor scenarios. Existing road...
Accurate side road detection is essential for traffic management, urban planning, and vehicle navigation. However, existing research mainly focuses on road network construction, lane extraction, and intersection identification, while fine-grained sid...
To realize the full potential of crowdsourced data collected by smartphone applications in urban research and planning, there is a need for parsimonious, reliable, computationally and temporally efficient data processing routines. The literature indi...
Monitoring vegetation cover is an essential parameter for assessing various natural and anthropogenic hazards that occur at the vicinity of archaeological sites and landscapes. In this study, we used free and open access to Copernicus Earth Observati...
Volunteer geographical information (VGI), either in the context of citizen science or the mining of social media, has proven to be useful in various domains including natural hazards, health status, disease epidemics, and biological monitoring. Nonet...
1 September 2014
In a pilot survey we examined the diffusion of open data and crowdsourcing practices among heritage institutions in Switzerland. The results suggest that so far, only very few institutions have adopted an open data / open content policy. There are ho...
As one of the most important breakthroughs for modern transportation, the indoor location-based technology has been gradually penetrating into our daily lives and underlines the foundation of the Internet of Things (IoT). To improve the positioning a...
As an emerging type of spatio-temporal big data based on positioning technology and navigation devices, vehicle-based crowdsourcing data has become a valuable trajectory data resource. However, crowdsourcing trajectory data has been collected by non-...
Crowdsourcing is one of the spatial data sources, but due to its unstructured form, the quality of noisy crowd judgments is a challenge. In this study, we address the problem of detecting and removing crowdsourced data bias as a prerequisite for bett...
Mobile crowdsourcing refers to systems where the completion of tasks necessarily requires physical movement of crowdworkers in an on-demand workforce. Evidence suggests that in such systems, tasks often get assigned to crowdworkers who struggle to co...
Monitoring pavement conditions is critical to pavement management and maintenance. Traditionally, pavement distress is mainly identified via accelerometers, videos, and laser scanning. However, the geographical coverage and temporal frequency are con...
Today, crowd computing is successfully applied for many information processing problems in a variety of domains. One of the most acute issues with crowd-powered systems is the quality of results (as humans can make errors). Therefore, a number of met...
The increasing number of sensors used in diverse applications has provided a massive number of continuous, unbounded, rapid data and requires the management of distinct protocols, interfaces and intermittent connections. As traditional sensor network...
The paper proposes a crowdsourcing-based approach for annotated data acquisition and means to support Active Learning training approach. In the proposed solution, aimed at data engineers, the knowledge of the crowd serves as an oracle that is able to...
This paper presents an approach to geodiversity assessment based on spatial multicriteria analysis. Instead of relying solely on weighted linear combination (WLC) for aggregating factor ratings and weights to compute a synthetic measure of geodiversi...
Understanding tourism related behavior and traveling patterns is an essential element of transportation system planning and tourism management at tourism destinations. Traditionally, tourism market segmentation is conducted to recognize tourist’s pro...
To address problems in remote sensing image change detection, this study proposes a method for identifying spurious changes based on an eco-geographical zoning knowledge base and crowdsourced data mining. After preliminary change detection using the...
Less-resourced languages are usually left out of phonetic studies based on large corpora. We contribute to the recent efforts to fill this gap by assessing how to use open-access, crowd-sourced audio data from Lingua Libre for phonetic research. Ling...
We present a GIS-based crowdsourcing application that was launched soon after the first COVID-19 cases had been recorded in Greece, motivated by the need for fast, location-wise data acquisition regarding COVID-19 disease spread during spring 2020, d...
Citizen science has shown great potential for bringing large groups of people closer to science, thanks in part to cooperation with universities and research centers. In this context, amateur weather networks played a major role in the last few decad...
The current paper focuses on the development of an enhanced Mobile Journalism (MoJo) model for soundscape heritage crowdsourcing, data-driven storytelling, and management in the era of big data and the semantic web. Soundscapes and environmental soun...
Within the broad problem known as automatic music transcription, we considered the specific task of automatic drum transcription (ADT). This is a complex task that has recently shown significant advances thanks to deep learning (DL) techniques. Most...
The highly contagious and rapidly mutating COVID-19 virus is affecting individuals worldwide. A rapid and large-scale method for COVID-19 testing is needed to prevent infection. Cough testing using AI has been shown to be potentially valuable. In thi...
New approaches to collect in-situ data are needed to complement the high spatial (10 m) and temporal (5 d) resolution of Copernicus Sentinel satellite observations. Making sense of Sentinel observations requires high quality and timely in-situ data f...
One of the most significant challenges in cities concerns urban mobility. Urban mobility involves the use of different modes of transport, which can be individual or collective, and different organizations can produce their respective datasets that,...
The World Urban Database and Access Portal Tools (WUDAPT) is a community initiative to collect worldwide data on urban form (i.e., morphology, materials) and function (i.e., use and metabolism). This is achieved through crowdsourcing, which we define...
Urban parks have important impacts on urban ecosystems and in disaster prevention. They also have diverse social functions that are important to the living conditions and spatial structures of cities. Identifying and classifying the different types o...
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