OpenStreetMap(OSM)is a dataset in constant change and this dynamic needs to be better understood.Based on 12-year time series of seven OSM data contribution activities extracted from 20 large cities worldwide,we inves...OpenStreetMap(OSM)is a dataset in constant change and this dynamic needs to be better understood.Based on 12-year time series of seven OSM data contribution activities extracted from 20 large cities worldwide,we investigate the temporal dynamic of OSM data production,more specifically,the auto-and cross-correlation,temporal trend,and annual seasonality of these activities.Furthermore,we evaluate and compare nine different temporal regression methods for forecasting such activities in horizons of 1–4 weeks.Several insights could be obtained from our analyses,including that the contribution activities tend to grown linearly in a moderate intra-annual cycle.Also,the performance of the temporal forecasting methods shows that they yield in general more accurate estimations of future contribution activities than a baseline metric,i.e.the arithmetic average of recent previous observations.In particular,the well-known ARIMA and the exponentially weighted moving average methods have shown the best performances.展开更多
Nowadays,several research projects show interest in employing volunteered geographic information(VGI)to improve their systems through using up-to-date and detailed data.The European project CAP4Access is one of the su...Nowadays,several research projects show interest in employing volunteered geographic information(VGI)to improve their systems through using up-to-date and detailed data.The European project CAP4Access is one of the successful examples of such international-wide research projects that aims to improve the accessibility of people with restricted mobility using crowdsourced data.In this project,OpenStreetMap(OSM)is used to extend OpenRouteService,a well-known routing platform.However,a basic challenge that this project tackled was the incompleteness of OSM data with regards to certain information that is required for wheelchair accessibility(e.g.sidewalk information,kerb data,etc.).In this article,we present the results of initial assessment of sidewalk data in OSM at the beginning of the project as well as our approach in awareness raising and using tools for tagging accessibility data into OSM database for enriching the sidewalk data completeness.Several experiments have been carried out in different European cities,and discussion on the results of the experiments as well as the lessons learned are provided.The lessons learned provide recommendations that help in organizing better mapping party events in the future.We conclude by reporting on how and to what extent the OSM sidewalk data completeness in these study areas have benefited from the mapping parties by the end of the project.展开更多
Finding the shortest path through open spaces is a well-known challenge for pedestrian routing engines.A common solution is routing on the open space boundary,which causes in most cases an unnecessarily long route.A p...Finding the shortest path through open spaces is a well-known challenge for pedestrian routing engines.A common solution is routing on the open space boundary,which causes in most cases an unnecessarily long route.A possible alternative is to create a subgraph within the open space.This paper assesses this approach and investigates its implications for routing engines.A number of algorithms(Grid,Spider-Grid,Visibility,Delaunay,Voronoi,Skeleton)have been evaluated by four different criteria:(i)Number of additional created graph edges,(ii)additional graph creation time,(iii)route computation time,(iv)routing quality.We show that each algorithm has advantages and disadvantages depending on the use case.We identify the algorithms Visibility with a reduced number of edges in the subgraph and Spider-Grid with a large grid size to be a good compromise in many scenarios.展开更多
Observations of living organisms by citizen scientists that are reported to online portals are a valuable source of information.They are also a special kind of volunteered geographic information(VGI).VGI data have iss...Observations of living organisms by citizen scientists that are reported to online portals are a valuable source of information.They are also a special kind of volunteered geographic information(VGI).VGI data have issues of completeness,which arise from biases caused by the opportunistic nature of the data collection process.We examined the completeness of bird species represented in citizen science observation data from eBird and iNaturalist in US National Parks(NPs).We used approaches for completeness estimation which were developed for data from OpenStreetMap,a crowdsourced map of the world.First,we used an extrinsic approach,comparing species lists from citizen science data with National Park Service lists.Second,we examined two intrinsic approaches using total observation numbers in NPs and the development of the number of new species being added to the data-set over time.Results from the extrinsic approach provided appropriate completeness estimations to evaluate the intrinsic approaches.We found that total observation numbers are a good estimator of species completeness of citizen science data from US NPs.There is also a close relationship between species completeness and the ratio of new species added to observation data vs.observation numbers in a given year.展开更多
Global land cover(LC)maps have been widely employed as the base layer for a number of applications including climate change,food security,water quality,biodiversity,change detection,and environmental planning.Due to t...Global land cover(LC)maps have been widely employed as the base layer for a number of applications including climate change,food security,water quality,biodiversity,change detection,and environmental planning.Due to the importance of LC,there is a pressing need to increase the temporal and spatial resolution of global LC maps.A recent advance in this direction has been the GlobeLand30 dataset derived from Landsat imagery,which has been developed by the National Geomatics Center of China(NGCC).Although overall accuracy is greater than 80%,the NGCC would like help in assessing the accuracy of the product in different regions of the world.To assist in this process,this study compares the GlobeLand30 product with existing public and online datasets,that is,CORINE,Urban Atlas(UA),OpenStreetMap,and ATKIS for Germany in order to assess overall and per class agreement.The results of the analysis reveal high agreement of up to 92%between these datasets and GlobeLand30 but that large disagreements for certain classes are evident,in particular wetlands.However,overall,GlobeLand30 is shown to be a useful product for characterizing LC in Germany,and paves the way for further regional and national validation efforts.展开更多
Currently,very few roof shape information for complex buildings is available on OSM.Moreover,additional data requirements(e.g.3D point clouds)limit the applicability of many roof reconstruction approaches.To mitigate ...Currently,very few roof shape information for complex buildings is available on OSM.Moreover,additional data requirements(e.g.3D point clouds)limit the applicability of many roof reconstruction approaches.To mitigate this issue,we propose an approach to roof shape recommendations for complex buildings by exploring the inherited characteristics of building footprints:the disclosure of rectangles combinations in a partition of footprints and the symmetrical features of footprints.First,it decomposes a complex footprint into rectangles by using an advanced minimal non-overlapping cover algorithm.Second,a graph-based symmetry detection algorithm is proposed to identify all the symmetrical sub-clusters in partitions.Then,a set of selection rules are defined to rank partitions,and the best ones are chosen for roof shape recommendation.Finally,a set of combination rules and a symmetry rule are defined.It enables to evaluate the probability of a footprint being a certain combination of roof shapes.Experimental results show the growth of the probability of correctly recommending roof shapes for single rectangles and buildings from a prior probability of 17–45%and from a prior probability of 0.29–14.3%,removing 60%and 93%of the incorrect roof shape options,respectively.展开更多
In landmark-based way-finding,determining the most salient landmark from several candidates at decision points is challenging.To overcome this problem,current approaches usually rely on a linear model to measure the s...In landmark-based way-finding,determining the most salient landmark from several candidates at decision points is challenging.To overcome this problem,current approaches usually rely on a linear model to measure the salience of landmarks.However,linear models are not always able to establish an accurate quantitative relationship between the attributes of a landmark and its perceived salience.Furthermore,the numbers of evaluated scenes and of volunteers participating in the testing of these models are often limited.With the aim of overcoming these gaps,we propose learning a non-linear salience model by means of genetic programming.We compared our proposed approach with conventional algorithms by using photographs of two hundred test scenes collected from two shopping malls.Two hundred volunteers who were not in these environments were asked to answer questionnaires about the collected photographs.The results from this experiment showed that in 76%of the cases,the most salient landmark(according to the volunteers’perception)was correctly predicted by our proposed approach.This accuracy rate is considerably higher than the ones achieved by conventional linear models.展开更多
Collaborative mapping projects,such as OpenStreetMap(OSM),have received tremendous amounts of contributed data from voluntary participants over time.So far,most research efforts deal with data quality issues,but the O...Collaborative mapping projects,such as OpenStreetMap(OSM),have received tremendous amounts of contributed data from voluntary participants over time.So far,most research efforts deal with data quality issues,but the OSM evolution across space and over time has not been noted.Therefore,this study is dedicated to the evolution of the contributed information in order to understand an emergent phenomenon of so-called collaborative contributing.The main objective of this paper is to monitor the evolutional pattern of OSM and predict potential future states through a cellular automata(CA)model.This is exceedingly relevant for numerous OSM-based applications.Descriptive spatiotemporal analysis of the contributions for the time period 2007–2012,using the city of Heidelberg(Germany)as a case study,reveals that early contributions are given three years after the launching of OSM,while after nearly six years,most of the areas are discovered.The simulation results for the validated CA model,predicting OSM states for 2014,provide clear evidence that most of the areas have been explored three years after people began mapping until 2010,and thereafter,the densification process has begun and will cover most parts of the city although the amount of contribution depends on the land use types.展开更多
OpenStreetMap(OSM)has seen an exponential increase in the last few years and large volumes of geodata have been received from volunteered individuals.The collected geodata are heterogeneous in terms of different dimen...OpenStreetMap(OSM)has seen an exponential increase in the last few years and large volumes of geodata have been received from volunteered individuals.The collected geodata are heterogeneous in terms of different dimensions such as spatial patterns of contributions,quality,patterns of contributing individuals,and type of contributions.Because contributors’personal information is anonymously stored by the OSM administrators,alternative methods are needed to investigate the role of contributors’characteristics on their mapping behavior.This study is intended to explore the potential socio-economic characteristics of contributors in highly contributed areas to have better insights about the latent patterns of involved individuals in a highly dynamic state of the most active country in OSM,Germany.A logistic regression model(LRM)is applied to discover the potential correlations between dependent and independent variables.The findings explain that the areas with high population density,middle level of education,high income,high rate of overnight stays,high number of foreigners,and residents aged from 18 to 69 are more likely to be involved in OSM.Furthermore,the degree of dynamism in OSM is a function of proximity to built-up areas.Finally,concluding remarks concerning the independent variables and model sensitivity are presented.展开更多
文摘OpenStreetMap(OSM)is a dataset in constant change and this dynamic needs to be better understood.Based on 12-year time series of seven OSM data contribution activities extracted from 20 large cities worldwide,we investigate the temporal dynamic of OSM data production,more specifically,the auto-and cross-correlation,temporal trend,and annual seasonality of these activities.Furthermore,we evaluate and compare nine different temporal regression methods for forecasting such activities in horizons of 1–4 weeks.Several insights could be obtained from our analyses,including that the contribution activities tend to grown linearly in a moderate intra-annual cycle.Also,the performance of the temporal forecasting methods shows that they yield in general more accurate estimations of future contribution activities than a baseline metric,i.e.the arithmetic average of recent previous observations.In particular,the well-known ARIMA and the exponentially weighted moving average methods have shown the best performances.
基金supported by the European Community’s Seventh Framework Programme[FP7/2007–2013],[Grant No 612096(CAP4Access)].
文摘Nowadays,several research projects show interest in employing volunteered geographic information(VGI)to improve their systems through using up-to-date and detailed data.The European project CAP4Access is one of the successful examples of such international-wide research projects that aims to improve the accessibility of people with restricted mobility using crowdsourced data.In this project,OpenStreetMap(OSM)is used to extend OpenRouteService,a well-known routing platform.However,a basic challenge that this project tackled was the incompleteness of OSM data with regards to certain information that is required for wheelchair accessibility(e.g.sidewalk information,kerb data,etc.).In this article,we present the results of initial assessment of sidewalk data in OSM at the beginning of the project as well as our approach in awareness raising and using tools for tagging accessibility data into OSM database for enriching the sidewalk data completeness.Several experiments have been carried out in different European cities,and discussion on the results of the experiments as well as the lessons learned are provided.The lessons learned provide recommendations that help in organizing better mapping party events in the future.We conclude by reporting on how and to what extent the OSM sidewalk data completeness in these study areas have benefited from the mapping parties by the end of the project.
基金supported by European Commission[grant number 612096(CAP4Access)].
文摘Finding the shortest path through open spaces is a well-known challenge for pedestrian routing engines.A common solution is routing on the open space boundary,which causes in most cases an unnecessarily long route.A possible alternative is to create a subgraph within the open space.This paper assesses this approach and investigates its implications for routing engines.A number of algorithms(Grid,Spider-Grid,Visibility,Delaunay,Voronoi,Skeleton)have been evaluated by four different criteria:(i)Number of additional created graph edges,(ii)additional graph creation time,(iii)route computation time,(iv)routing quality.We show that each algorithm has advantages and disadvantages depending on the use case.We identify the algorithms Visibility with a reduced number of edges in the subgraph and Spider-Grid with a large grid size to be a good compromise in many scenarios.
文摘Observations of living organisms by citizen scientists that are reported to online portals are a valuable source of information.They are also a special kind of volunteered geographic information(VGI).VGI data have issues of completeness,which arise from biases caused by the opportunistic nature of the data collection process.We examined the completeness of bird species represented in citizen science observation data from eBird and iNaturalist in US National Parks(NPs).We used approaches for completeness estimation which were developed for data from OpenStreetMap,a crowdsourced map of the world.First,we used an extrinsic approach,comparing species lists from citizen science data with National Park Service lists.Second,we examined two intrinsic approaches using total observation numbers in NPs and the development of the number of new species being added to the data-set over time.Results from the extrinsic approach provided appropriate completeness estimations to evaluate the intrinsic approaches.We found that total observation numbers are a good estimator of species completeness of citizen science data from US NPs.There is also a close relationship between species completeness and the ratio of new species added to observation data vs.observation numbers in a given year.
基金The authors would also like to acknowledge the support and contribution of COST Action TD1202‘Mapping and the Citizen Sensor’as well as COST Action IC1203‘European Network Exploring Research into Geospatial Information Crowdsourcing’(ENERGIC).
文摘Global land cover(LC)maps have been widely employed as the base layer for a number of applications including climate change,food security,water quality,biodiversity,change detection,and environmental planning.Due to the importance of LC,there is a pressing need to increase the temporal and spatial resolution of global LC maps.A recent advance in this direction has been the GlobeLand30 dataset derived from Landsat imagery,which has been developed by the National Geomatics Center of China(NGCC).Although overall accuracy is greater than 80%,the NGCC would like help in assessing the accuracy of the product in different regions of the world.To assist in this process,this study compares the GlobeLand30 product with existing public and online datasets,that is,CORINE,Urban Atlas(UA),OpenStreetMap,and ATKIS for Germany in order to assess overall and per class agreement.The results of the analysis reveal high agreement of up to 92%between these datasets and GlobeLand30 but that large disagreements for certain classes are evident,in particular wetlands.However,overall,GlobeLand30 is shown to be a useful product for characterizing LC in Germany,and paves the way for further regional and national validation efforts.
文摘Currently,very few roof shape information for complex buildings is available on OSM.Moreover,additional data requirements(e.g.3D point clouds)limit the applicability of many roof reconstruction approaches.To mitigate this issue,we propose an approach to roof shape recommendations for complex buildings by exploring the inherited characteristics of building footprints:the disclosure of rectangles combinations in a partition of footprints and the symmetrical features of footprints.First,it decomposes a complex footprint into rectangles by using an advanced minimal non-overlapping cover algorithm.Second,a graph-based symmetry detection algorithm is proposed to identify all the symmetrical sub-clusters in partitions.Then,a set of selection rules are defined to rank partitions,and the best ones are chosen for roof shape recommendation.Finally,a set of combination rules and a symmetry rule are defined.It enables to evaluate the probability of a footprint being a certain combination of roof shapes.Experimental results show the growth of the probability of correctly recommending roof shapes for single rectangles and buildings from a prior probability of 17–45%and from a prior probability of 0.29–14.3%,removing 60%and 93%of the incorrect roof shape options,respectively.
基金the National Key R&D Program of China(No.2016YFB0502203)the National Natural Science Foundation of China(Grant No.41271440)the China Scholarship Council.
文摘In landmark-based way-finding,determining the most salient landmark from several candidates at decision points is challenging.To overcome this problem,current approaches usually rely on a linear model to measure the salience of landmarks.However,linear models are not always able to establish an accurate quantitative relationship between the attributes of a landmark and its perceived salience.Furthermore,the numbers of evaluated scenes and of volunteers participating in the testing of these models are often limited.With the aim of overcoming these gaps,we propose learning a non-linear salience model by means of genetic programming.We compared our proposed approach with conventional algorithms by using photographs of two hundred test scenes collected from two shopping malls.Two hundred volunteers who were not in these environments were asked to answer questionnaires about the collected photographs.The results from this experiment showed that in 76%of the cases,the most salient landmark(according to the volunteers’perception)was correctly predicted by our proposed approach.This accuracy rate is considerably higher than the ones achieved by conventional linear models.
文摘Collaborative mapping projects,such as OpenStreetMap(OSM),have received tremendous amounts of contributed data from voluntary participants over time.So far,most research efforts deal with data quality issues,but the OSM evolution across space and over time has not been noted.Therefore,this study is dedicated to the evolution of the contributed information in order to understand an emergent phenomenon of so-called collaborative contributing.The main objective of this paper is to monitor the evolutional pattern of OSM and predict potential future states through a cellular automata(CA)model.This is exceedingly relevant for numerous OSM-based applications.Descriptive spatiotemporal analysis of the contributions for the time period 2007–2012,using the city of Heidelberg(Germany)as a case study,reveals that early contributions are given three years after the launching of OSM,while after nearly six years,most of the areas are discovered.The simulation results for the validated CA model,predicting OSM states for 2014,provide clear evidence that most of the areas have been explored three years after people began mapping until 2010,and thereafter,the densification process has begun and will cover most parts of the city although the amount of contribution depends on the land use types.
基金The authors acknowledge the constructive comments of the anonymous reviewers and the editor-inchief,which helped to improve the study.Jamal Jokar Arsanjani was funded by the Alexander von Humboldt foundation.
文摘OpenStreetMap(OSM)has seen an exponential increase in the last few years and large volumes of geodata have been received from volunteered individuals.The collected geodata are heterogeneous in terms of different dimensions such as spatial patterns of contributions,quality,patterns of contributing individuals,and type of contributions.Because contributors’personal information is anonymously stored by the OSM administrators,alternative methods are needed to investigate the role of contributors’characteristics on their mapping behavior.This study is intended to explore the potential socio-economic characteristics of contributors in highly contributed areas to have better insights about the latent patterns of involved individuals in a highly dynamic state of the most active country in OSM,Germany.A logistic regression model(LRM)is applied to discover the potential correlations between dependent and independent variables.The findings explain that the areas with high population density,middle level of education,high income,high rate of overnight stays,high number of foreigners,and residents aged from 18 to 69 are more likely to be involved in OSM.Furthermore,the degree of dynamism in OSM is a function of proximity to built-up areas.Finally,concluding remarks concerning the independent variables and model sensitivity are presented.
