Improvement of a location-aware recommender system using volunteered geographic information

Abstract

Recommender systems (RS), as supportive tools, filter information from a massive amount of data based on the determined preferences. Most of the RS require information about the context of users such as their locations. In such cases, location-aware recommender systems (LARS) can be employed to suggest more personalized items to the users. The most current research projects on LARS focus on the development of algorithms, evaluation methods and applications. However, the role of up-to-date spatial databases in LARS is not a well-researched area. The up-to-date spatial information would potentially improve the accuracy of items which are recommended by LARS. Volunteered geographic information (VGI) could be a low-cost source of up-to-date spatial information for LARS. This article proposes an approach to enrich spatial databases of LARS by VGI. Since not all records of VGI are fitted for use in LARS, a mechanism is developed to identify useful information. Some VGI data sets refer to existing spatial data in the database while other VGI data sets are shared for the first time. Therefore, the proposed method assessed the quality of VGI with reference source (for VGI which is existed in the database) and VGI without reference source (for VGI which is shared for the first time). To demonstrate the feasibility of the proposed approach, a mobile application has been developed to recommend suitable restaurants to the users based on their geospatial locations. The evaluation of the method indicates that VGI can potentially enhance the functionality of the LARS in predicting the users’ interests.     

Data trustworthiness and user reputation as indicators of VGI quality

ABSTRACT

Volunteered geographic information (VGI) has entered a phase where there are both a substantial amount of crowdsourced information available and a big interest in using it by organizations. But the issue of deciding the quality of VGI without resorting to a comparison with authoritative data remains an open challenge. This article first formulates the problem of quality assessment of VGI data. Then presents a model to measure trustworthiness of information and reputation of contributors by analyzing geometric, qualitative, and semantic aspects of edits over time. An implementation of the model is running on a small data-set for a preliminary empirical validation. The results indicate that the computed trustworthiness provides a valid approximation of VGI quality.     

Applying VGI to collaborative research in the humanities: the case of ARTL@S

ABSTRACT

Using Artl@s as an example of a project that relies on volunteered geographic information (VGI), this article examines the specific challenges that exist, beyond those frequently discussed in general VGI systems (e.g., participants’ motivation and data quality control) in regard to sharing research data in humanities: (1) most data from the humanities is qualitative and collected from multiple data sources which are often inconsistent and unmappable; (2) data is usually interconnected with multiple relationships among different tables which creates challenges for both mapping and query functionality; (3) data is both geographical and historical. Consequently addresses that no longer exist have to be geolocated and visualized on historical basemaps and spaces must be represented diachronically; (4) the design of web map application needs to balance both sophisticated research requirements and a user-friendly interface; (5) finally contributors expect their data to be cited or acknowledged when used in other studies and users need metadata and citation information in order to reuse and repurpose datasets.

In this article, we discuss how Artl@s, a project which developed a georeferenced historical database of exhibition catalogues, addresses these challenges. Artl@s provides a case study for VGI adoption by digital humanities scholars for research data sharing, as it offers features, such as flexible batch data contribution, interrelated spatial query, automatic geolocalization of historical addresses, and data citation mechanisms.     

Assessing quality of volunteer crowdsourcing contributions: lessons from the Cropland Capture game

Volunteered geographic information (VGI) is the assembly of spatial information based on public input. While VGI has proliferated in recent years, assessing the quality of volunteer-contributed data has proven challenging, leading some to question the efficiency of such programs. In this paper, we compare several quality metrics for individual volunteers’ contributions. The data were the product of the ‘Cropland Capture’ game, in which several thousand volunteers assessed 165,000 images for the presence of cropland over the course of 6 months. We compared agreement between volunteer ratings and an image's majority classification with volunteer self-agreement on repeated images and expert evaluations. We also examined the impact of experience and learning on performance. Volunteer self-agreement was nearly always higher than agreement with majority classifications, and much greater than agreement with expert validations although these metrics were all positively correlated. Volunteer quality showed a broad trend toward improvement with experience, but the highest accuracies were achieved by a handful of moderately active contributors, not the most active volunteers. Our results emphasize the importance of a universal set of expert-validated tasks as a gold standard for evaluating VGI quality.     

Modeling aggregated expertise of user contributions to assess the credibility of OpenStreetMap features

The emergence of volunteered geographic information (VGI) during the past decade has fueled a wide range of research and applications. The assessment of VGI quality and fitness‐of‐use is still a challenge because of the non‐standardized and crowdsourced data collection process, as well as the unknown skill and motivation of the contributors. However, the frequent approach of assessing VGI quality against external data sources using ISO quality standard measures is problematic because of a frequent lack of available external (reference) data, and because for certain types of features, VGI might be more up‐to‐date than the reference data. Therefore, a VGI‐intrinsic measure of quality is highly desirable. This study proposes such an intrinsic measure of quality by developing the concept of aggregated expertise based on the characteristics of a feature's contributors. The article further operationalizes this concept and examines its feasibility through a case study using OpenStreetMap (OSM). The comparison of model OSM feature quality with information from a field survey demonstrates the successful implementation of this novel approach.     

Integrating VGI and 2D hydraulic models into a data assimilation framework for real time flood forecasting and mapping

ABSTRACT

Crowdsourced data can effectively observe environmental and urban ecosystem processes. The use of data produced by untrained people into flood forecasting models may effectively allow Early Warning Systems (EWS) to better perform while support decision-making to reduce the fatalities and economic losses due to inundation hazard. In this work, we develop a Data Assimilation (DA) method integrating Volunteered Geographic Information (VGI) and a 2D hydraulic model and we test its performances. The proposed framework seeks to extend the capabilities and performances of standard DA works, based on the use of traditional in situ sensors, by assimilating VGI while managing and taking into account the uncertainties related to the quality, and the location and timing of the entire set of observational data. The November 2012 flood in the Italian Tiber River basin was selected as the case study. Results show improvements of the model in terms of uncertainty with a significant persistence of the model updating after the integration of the VGI, even in the case of use of few-selected observations gathered from social media. This will encourage further research in the use of VGI for EWS considering the exponential increase of quality and quantity of smartphone and social media user worldwide.     

面向灾害管理的自发地理信息研究及应用

针对目前自发地理信息(VGI)应用于灾害管理的巨大潜力和需求,该文系统地介绍了VGI应用于灾害管理中所面临的机遇及数据可用性、数据质量、数据管理和法律议题等方面的挑战;在此基础上,针对VGI数据质量问题,结合我国灾害管理实际情况,提出了3种提高VGI数据质量的方法,即VGI数据贡献者分类与权限设计、政府引导下的灾害管理VGI数据采集框架以及VGI数据质量评估体系;最后,以开发的地震灾情信息管理原型系统为例,讨论VGI应用于灾害管理中的数据采集框架、数据模型等关键技术问题,具有一定的推广和应用价值。     

Trust as a proxy indicator for intrinsic quality of Volunteered Geographic Information in biodiversity monitoring programs

In this article, we present a fuzzy model for intrinsic quality assessment of Volunteered Geographic Information (VGI) on species occurrences obtained by Citizen Science (CS) biodiversity monitoring programs. The proposed VGI quality assurance approach evaluates the thematic and positional quality of the crowdsourced biodiversity observation in terms of the trustworthiness of the observation by combining three indicators of consistency with habitat, consistency with surroundings, and reputation of contributor, that characterize the geographical and social aspects of trust in VGI. To evaluate the performance and usability of the proposed approach for evaluating the trustworthiness of crowdsourced observations and detecting thematic and positional errors in crowdsourced observations, the developed approach was applied to the crowdsourced observations on Acer macrophyllum collected through the CS biodiversity monitoring projects of E-Flora BC and iNaturalist. The result of a conformity test at the optimal acceptance threshold (sensitivity = 0.99, specificity = 0.8, and Cohen’s kappa = 0.79), the achieved area under the curve (AUC) value (AUC = 0.98), and the results of the complementary investigation on the predictions of the proposed model indicated that the proposed fuzzy trust model exhibited promising predictive performance and was able to flag the majority of attribute and positional errors in the crowdsourced biodiversity observations.     

Finding meaningful participation in volunteer geographic information and citizen science: a case comparison in environmental application

ABSTRACT

Volunteer geographic information (VGI) and citizen science (CS) have been used as a way to promote a form of democratization of knowledge. Crowdsourcing facilitates the massive collection of data through nonexpert volunteers. This study compares 57 VGI and CS projects through a cross-case comparison method to explore the level of involvement of participants, based on three main analytic dimensions (project rationale, actor interaction, and data flow) and 12 sub-variables. The primary goal of this research is to analyze the purpose and the role of technology in VGI and CS projects, using three matrices to explore emerging trade-offs. Finally, we synthesized the workflow of VGI and CS project and compared based on project purposes. At the end of this study, five main purposes were found among the selected projects, uncovering that data collection is the most common purpose. A general workflow can be conceptualized, but detail implementation will involve various trade-offs, especially between local involvement and large-area expert-oriented protocol implementations. By exploring diverse relationships among selected variables of analysis in VGI and CS projects, this study pretends to build a foundation for larger, global meta-analysis that can bring some transparency in the epistemic interactions between experts and nonexperts.     

Geometric quality assessment of trajectory‐generated VGI road networks based on the symmetric arc similarity

As large amounts of trajectories from a wide variety of Volunteered Geographic Information (referred to as VGI) contributors pour into the spatial database, the geometric qualities of the VGI road networks generated from these trajectories are different from the ground truth road dataset and so need to be differently assessed. To address this issue, an assessment approach based on symmetric arc similarity is proposed, and the geometric quality of a VGI road network is assessed by its conformity with the corresponding ground truth road network, the results being visualized as hierarchical thematic maps. To compute the conformity, the geometric similarity between the VGI road arc and the corresponding ground truth road arc, which is selected by the adaptive searching distance, is measured based on the symmetric arc similarity method; the geometric quality is assessed based on an assessment matrix. Also, the symmetric arc similarity method is independent of directions and with a feature of shift‐independence, which is applicable to assess the geometric qualities of different VGI road networks and makes the assessment result consistent with the actual situation of the real world. The robustness and scalability of the approach are examined using VGI road networks from different sources.     

Using control data to determine the reliability of volunteered geographic information about land cover

There is much interest in using volunteered geographic information (VGI) in formal scientific analyses. This analysis uses VGI describing land cover that was captured using a web-based interface, linked to Google Earth. A number of control points, for which the land cover had been determined by experts allowed measures of the reliability of each volunteer in relation to each land cover class to be calculated. Geographically weighted kernels were used to estimate surfaces of volunteered land cover information accuracy and then to develop spatially distributed correspondences between the volunteer land cover class and land cover from 3 contemporary global datasets (GLC-2000, GlobCover and MODIS v.5). Specifically, a geographically weighted approach calculated local confusion matrices (correspondences) at each location in a central African study area and generated spatial distributions of user's, producer's, portmanteau, and partial portmanteau accuracies. These were used to evaluate the global datasets and to infer which of them was 'best’ at describing Tree cover at each location in the study area. The resulting maps show where specific global datasets are recommended for analyses requiring Tree cover information. The methods presented in this research suggest that some of the concerns about the quality of VGI can be addressed through careful data collection, the use of control points to evaluate volunteer performance and spatially explicit analyses. A research agenda for the use and analysis of VGI about land cover is outlined.     

The Scale of VGI in Map Production: A Perspective on European National Mapping Agencies

The perspective of European National Mapping Agencies (NMA) on the role of citizen sensing in map production was explored. The NMAs varied greatly in their engagement with the community generating volunteered geographic information (VGI) and in their future plans. From an assessment of NMA standard practices, it was evident that much VGI was acquired with a positional accuracy that, while less than that typically acquired by NMAs, actually exceeded the requirements of the nominal data capture scale used by most NMAs. Opportunities for VGI use in map revision and updating were evident, especially for agencies that use a continuous rather than cyclical updating policy. Some NMAs had also developed systems to engage with citizen sensors and examples are discussed. Only rarely was VGI used to collect data on features beyond the standard set used by the NMAs. The potential role of citizen sensing and so its current scale of use by NMAs is limited by a series of concerns, notably relating to issues of data quality, the nature and motivation of the contributors, legal issues, the sustainability of data source, and employment fears of NMA staff. Possible priorities for future research and development are identified to help ensure that the potential of VGI in mapping is realized.     

Characterizing urban area dynamics in historic city of Kurukshetra,India, using remote sensing and spatial metric tools

Abstract

Developing countries like India are an urbanization hotspot with many upcoming towns and cities. Growth in small and medium sized towns and cities have been unnoticed and growing without appropriate urban planning. Utilizing the available medium resolution satellite data and geospatial platforms, the growth dynamics of Kurukshetra city was analysed over a period of 24 years. The study employed a combination of change detection technique and spatial metrics (six each of class and landscape levels) analysis to delineate the growth track of the city and its environs. A significant increase in urban built up (dense 237%; open 1038%) is seen majorly at the cost of open area (70%) and tree clad (58%). Phases of city’s aggregation and diffusion are observed using class and landscape level spatial metrics. Understanding and monitoring of land use changes in and around city limits using integrated spatial tools provide better decision making capability.     

Distribution of Errors in a Classified Map of Satellite Data

Abstract

The output from any spatial data processing method may contain some uncertainty. With the increasing use of satellite data products as a source of data for Geographical Information Systems (GIS), there have been some major concerns about the accuracy of the satellite‐based information. Due to the nature of spatial data and remotely sensed data acquisition technology, and conventional classification, any single classified image can contain a number of mis‐classified pixels. Conventional accuracy evaluation procedures can report only the number of pixels that are mis‐classified based on some sampling observation. This study investigates the spatial distribution and the amount of these pixels associated with each cover type in a product of satellite data. The study uses Thematic Mapper (TM) and SPOT multispectral data sets obtained for a study area selected in North East New South Wales, Australia. The Fuzzy c‐Means algorithm is used to identify the classified pixels that contained some uncertainty. The approach is based on evaluating the strength of class membership of pixels. This study is important as it can give an indication of the amount of error resulting from the mis‐classification of pixels of specific cover types as well as the spatial distribution of such pixels. The results show that the spatial distribution of erroneously classified pixels are not random and varies depending on the nature of cover types. The proportions of such pixels are higher in spectrally less clearly defined cover types such as grasslands.     

Effectiveness of Cartogram for the Representation of Spatial Data

Abstract

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Cartogram is a technique for visualisation of the geographical distribution of spatial data. It has two main types, i.e. distance cartogram and area cartogram. Area cartogram is a transformed map in which areas are resized in proportion to an attribute value. A number of techniques have been developed for the generation of area cartograms. Some researchers consider cartogram as a very effective technique for visualisation of spatial data, while others doubt about the effectiveness because of the possible distortion in shape and/or disconnectivity in topology. This study aims to evaluate the effectiveness of area cartogram for visualizing spatial data. In this study, two comparative experiments have been conducted. One is the comparison between thematic maps and cartograms, and the other is the comparison among different types of area cartogram. Two sets of data with different characteristics are used, i.e. 2005 China population data and 1996 US election data. Results show that cartogram is more effective in the representation of the 1996 US election data which provides a qualitative result (i.e. in binary form or nominal data), but thematic map is far more effective in the representation of 2005 China population data which provides a quantitative result (in classes or ordinal data). It is also found that among different types of area cartogram, pseudo-cartogram is the most preferred technique and Dorling cartogram is the least preferred one.     

Building geospatial infrastructure

ABSTRACT

Many visions for geospatial technology have been advanced over the past half century. Initially researchers saw the handling of geospatial data as the major problem to be overcome. The vision of geographic information systems arose as an early international consensus. Later visions included spatial data infrastructure, Digital Earth, and a nervous system for the planet. With accelerating advances in information technology, a new vision is needed that reflects today’s focus on open and multimodal access, sharing, engagement, the Web, Big Data, artificial intelligence, and data science. We elaborate on the concept of geospatial infrastructure, and argue that it is essential if geospatial technology is to contribute to the solution of problems facing humanity.     

Mapping impervious surface distribution in China using multi-source remotely sensed data

ABSTRACT

Impervious surface area (ISA) data are required for such studies as urban environmental modeling, hydrological modeling, and socioeconomic analysis, but updating these datasets in a large area remains a challenge due to the complex urban landscapes consisting of different materials and colors with various spatial patterns. This research explores the integration of multi-source remotely sensed data for mapping China’s ISA distribution at 30-m spatial resolution. The integration of Visible Infrared Imaging Radiometer Suite Day/Night Band (VIIRS DNB) and Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data were used to extract initial ISA with spatial resolution of 250 m using a thresholding approach. The Landsat-derived NDVI and Modified Normalized Difference Water Index (MNDWI) were used to remove vegetation and water areas from the mixed pixels that existed in the initial ISA data. The spectral signatures of these ISA data were further extracted from Landsat multispectral images and used to refine the ISA data using expert knowledge. The results indicate that the integration of multi-source data can successfully map ISA distribution with 30-m spatial resolution in China with producer’s and user’s accuracies of 83.1 and 91.9%, respectively. These ISA data are valuable for better management of urban landscapes and for use as an input in other studies such as socioeconomic and environmental modeling.     

Spatially explicit urban green indicators for characterizing vegetation cover and public green space proximity: a case study on Brussels,Belgium

ABSTRACT

Cities often have a substantial green infrastructure, which provides local ecosystem services that improve the quality of life of urban residents. These services should be explicitly addressed in urban development policies, and areas with insufficient vegetation and limited access to public green spaces should be identified. This paper presents two spatially explicit urban green indicators that are derived using remote sensing imagery, freely available map data and spatial analysis tools from open source geospatial libraries and commercial software. The first indicator represents proportional green cover (public as well as private) in the vicinity of each building within a city. The second indicator quantifies the proximity of public green spaces as walking distances from buildings to actual park entrances. A dasymetric mapping approach was used to take spatial variations in population density into account. This allows representing the indicators from the perspective of citizens instead of buildings, which may be more meaningful for deriving statistics at city level or at the level of neighbourhoods or administrative zones. The potential use of these indicators in a planning context is discussed on a case study carried out for the city of Brussels, Belgium.