ISPRS International Journal of Geo-Information, 2022
Environmental exposure of people plays an important role in assessing the quality of human life. ... more Environmental exposure of people plays an important role in assessing the quality of human life. The most existing methods that estimate the environmental exposure either focus on the individual level or do not consider human mobility. This paper adopts a vector field generated from the observed locations of human activities to model the environmental exposure at the population level. An improved vector-field-generation method was developed by considering people’s decision-making factors, and we proposed two indicators, i.e., the total exposure indicator (TEI) and the average exposure indicator (AEI), to assess various social groups’ environmental exposure. A case study about the risky environmental exposure of coronavirus disease 2019 (COVID-19) was conducted in Guangzhou, China. Over 900 participants with various socioeconomic backgrounds were involved in the questionnaire, and the survey-based activity locations were extracted to generate the vector field using the improved metho...
International Journal of Environmental Research and Public Health, 2021
With the COVID-19 vaccination widely implemented in most countries, propelled by the need to revi... more With the COVID-19 vaccination widely implemented in most countries, propelled by the need to revive the tourism economy, there is a growing prospect for relieving the social distancing regulation and reopening borders in tourism-oriented countries and regions. This need incentivizes stakeholders to develop border control strategies that fully evaluate health risks if mandatory quarantines are lifted. In this study, we have employed a computational approach to investigate the contact tracing integrated policy in different border-reopening scenarios in Hong Kong, China. Explicitly, by reconstructing the COVID-19 transmission from historical data, specific scenarios with joint effects of digital contact tracing and other concurrent measures (i.e., controlling arrival population and community nonpharmacological interventions) are applied to forecast the future development of the pandemic. Built on a modified SEIR epidemic model with a 30% vaccination coverage, the results suggest that s...
Revealing urban functions in cities can be an essential means to describe the characteristics of ... more Revealing urban functions in cities can be an essential means to describe the characteristics of human activities and places. Through the lens of points of interest and tourist online reviews collected in downtown Hong Kong, this study develops a semantic-based framework to detect and compare urban functional identities. The findings depict a unique image of city identity for the downtown area in Hong Kong that contains miscellaneous urban vibrancies. Ultimately, a profound insight is yielded in our study for the understanding of local activities, which can provide human-centric implications for evidence-based urban planning and establish real-world cognitions to the public.
Existing trajectory patterns, such as flock, convoy, swarm, and gathering, are to detect moving c... more Existing trajectory patterns, such as flock, convoy, swarm, and gathering, are to detect moving clusters staying or travelling together for a certain time period. But these patterns model group movement behaviors after moving objects’ gathering together. This may result in loosing golden opportunities to detect emergency incidents earlier, such as traffic congestion and serious stampedes. In this work, we propose a novel group pattern, called converging, which can model converging behaviors of moving objects. As a proof-of-concept, we implemented a visual analytic system GEDetector based on trajectory streams to detect gathering events as early as possible. A user-friendly interface is designed to help users gain insights into gathering events from spatial and temporal aspects. Finally, we demonstrate the effectiveness and efficiency of our system by using a real world dataset.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Relationship between urban diversity and urban vitality is imperative for guiding better design i... more Relationship between urban diversity and urban vitality is imperative for guiding better design in urban development, although existing frameworks are not able to efficiently examine the relationship at multiple scales. In this article, we propose a new framework to integrate nighttime light (NTL) imagery and multisource urban data into multiscale geographically weighted regression (MGWR) models to examine the varying relationship between diversity and vitality across space and time. NTL is used as a proxy for urban nighttime vitality. Public transport, taxi transit, and points of interest data are used to derive three aspects of urban diversity indices: ridership diversity, spatial interaction diversity, and built environment diversity. By comparing the models in holiday and nonholiday weeks in Shenzhen, China, the NTL-based vitality proxy was found to be strongly correlated with the urban diversity indices, given by the satisfactory goodness of fit (r-squared = 0.9) of the MGWR models. The spatially varying relationships between diversity indices and nighttime vitality were observed and patterns discussed. The analysis of the coefficients revealed the importance of stable public transport and fluctuating taxi trips for nighttime vitality. The new index proposed for the diversity of spatial interaction (DSI) is a strong indicator for nighttime vitality, adding to existing vitality indicators. Furthermore, this study found that DSI and density of catering have less temporal variation, indicating their robustness in measuring nighttime vitality.
Urban functional area (UFA) recognition is one of the most important strategies for achieving sus... more Urban functional area (UFA) recognition is one of the most important strategies for achieving sustainable city development. As remote-sensing and social-sensing data sources have increasingly become available, UFA recognition has received a significant amount of attention. Research on UFA recognition that uses a single dataset suffers from a low update frequency or low spatial resolution, while data fusion-based methods are limited in efficiency and accuracy. This paper proposes an integrated model to identify UFA using satellite images and taxi global positioning system (GPS) trajectories in four steps. First, blocks were generated as spatial units in the study area, and the spatiotemporal information entropy of the taxi GPS trajectory (STET) for each block was calculated. Second, a 24-hour time-frequency series was formed based on the pick-up and drop-off points extracted from taxi trajectories and used as the interpretation indicator of the blocks. The K-Means++ and k-Nearest Nei...
IEEE Intelligent Transportation Systems Magazine, 2021
In prior research, a statistically cheap method was developed to monitor transportation network p... more In prior research, a statistically cheap method was developed to monitor transportation network performance by using only a few groups of agents without having to forecast the population flows. The current study validates this "multi-agent inverse optimization" method using taxi GPS trajectories data from the city of Wuhan, China. Using a controlled 2062-link network environment and different GPS data processing algorithms, an online monitoring environment is simulated using the real data over a 4-hour period. Results show that using only samples from one OD pair, the multi-agent inverse optimization method can learn network parameters such that forecasted travel times have a 0.23 correlation with the observed travel times. By increasing to monitoring from just two OD pairs, the correlation improves further to 0.56.
Received signal strength indicator (RSSI)-based positioning is suitable for large-scale applicati... more Received signal strength indicator (RSSI)-based positioning is suitable for large-scale applications due to its advantages of low cost and high accuracy. However, it suffers from low stability because RSSI is easily blocked and easily interfered with by objects and environmental effects. Therefore, this paper proposed a tri-partition RSSI classification and its tracing algorithm as an RSSI filter. The proposed filter shows an available feature, where small test RSSI samples gain a low deviation of less than 1 dBm from a large RSSI sample collected about 10 min, and the sub-classification RSSIs conform to normal distribution when the minimum sample count is greater than 20. The proposed filter also offers several advantages compared to the mean filter, including lower variance range with an overall range of around 1 dBm, 25.9% decreased sample variance, and 65% probability of mitigating RSSI left-skewness. We experimentally confirmed the proposed filter worked in the path-loss expone...
International Journal of Environmental Research and Public Health, 2021
The measurement of medical service accessibility is typically based on driving or Euclidean dista... more The measurement of medical service accessibility is typically based on driving or Euclidean distance. However, in most non-emergency cases, public transport is the travel mode used by the public to access medical services. Yet, there has been little evaluation of the public transport system-based inequality of medical service accessibility. This work uses massive real smart card data (SCD) and an improved potential model to estimate the public transport-based medical service accessibility in Beijing, China. These real SCD data are used to calculate travel costs in terms of time and distance, and medical service accessibility is estimated using an improved potential model. The spatiotemporal variations and patterns of medical service accessibility are explored, and the results show that it is unevenly spatiotemporally distributed across the study area. For example, medical service accessibility in urban areas is higher than that in suburban areas, accessibility during peak periods is...
This paper proposes a novel method for dynamically extracting and monitoring the entrances of are... more This paper proposes a novel method for dynamically extracting and monitoring the entrances of areas of interest (AOIs). Most AOIs in China, such as buildings and communities, are enclosed by walls and are only accessible via one or more entrances. The entrances are not marked on most maps for route planning and navigation in an accurate way. In this work, the extraction scheme of the entrances is based on taxi trajectory data with a 30 s sampling time interval. After fine-grained data cleaning, the position accuracy of the drop-off points extracted from taxi trajectory data is guaranteed. Next, the location of the entrances is extracted, combining the density-based spatial clustering of applications with noise (DBSCAN) with the boundary of the AOI under the constraint of the road network. Based on the above processing, the dynamic update scheme of the entrance is designed. First, a time series analysis is conducted using the clusters of drop-off points within the adjacent AOI, and t...
ISPRS International Journal of Geo-Information, 2019
Public transport plays an important role in developing sustainable cities. A better understanding... more Public transport plays an important role in developing sustainable cities. A better understanding of how different public transit modes (bus, metro, and taxi) interact with each other will provide better sustainable strategies to transport and urban planners. However, most existing studies are either limited to small-scale surveys or focused on the identification of general interaction patterns during times of regular traffic. Transient demographic changes in a city (i.e., many people moving out and in) can lead to significant changes in such interaction patterns and provide a useful context for better investigating the changes in these patterns. Despite that, little has been done to explore how such interaction patterns change and how they are linked to the built environment from the perspective of transient demographic changes using urban big data. In this paper, the tap-in-tap-out smart card data of bus/metro and taxi GPS trajectory data before and after the Chinese Spring Festiv...
Ubiquitous taxi trajectory data has made it possible to apply it to different types of travel ana... more Ubiquitous taxi trajectory data has made it possible to apply it to different types of travel analysis. Of interest is the need to allow someone to monitor travel momentum and associated congestion in any location in space in real time. However, despite an abundant literature in taxi data visualization and its applicability to travel analysis, no easy method exists. To measure taxi travel momentum at a location, current methods require filtering taxi trajectories that stop at a location at a particular time range, which is computationally expensive. We propose an alternative, computationally cheaper way based on pre-processing vector fields from the trajectories. Algorithms are formalized for generating vector kernel density to estimate a travel-model-free vector field-based representation of travel momentum in an urban space. The algorithms are shared online as an open source GIS 3D extension called VectorKD. Using 17 million daily taxi GPS points within Beijing over a four-day period, we demonstrate how to generate in real time a series of projections from a continuously updated vector field of taxi travel momentum to query a point of interest anywhere in a city, such as the CBD or the airport. This method allows a policy-maker to automatically identify temporal net influxes of travel demand to a location. The proposed methodology is shown to be over twenty times faster than a conventional selection query of trajectories. We also demonstrate, using taxi data entering the Beijing Capital International Airport and the CBD, how we can quantify in nearly real time the occurrence and magnitude of inbound or outbound queueing and congestion periods due to taxis cruising or waiting for passengers, all without having to fit any mathematical queueing model to the data.
ISPRS International Journal of Geo-Information, 2016
Conventional ice navigation in the sea is manually operated by well-trained navigators, whose exp... more Conventional ice navigation in the sea is manually operated by well-trained navigators, whose experiences are heavily relied upon to guarantee the ship's safety. Despite the increasingly available ice data and information, little has been done to develop an automatic ice navigation support system to better guide ships in the sea. In this study, using the vector-formatted ice data and navigation codes in northern regions, we calculate ice numeral and divide sea area into two parts: continuous navigable area and the counterpart numerous separate unnavigable area. We generate Voronoi Diagrams for the obstacle areas and build a road network-like graph for connections in the sea. Based on such a network, we design and develop a geographic information system (GIS) package to automatically compute the safest-and-shortest routes for different types of ships between origin and destination (OD) pairs. A visibility tool, Isovist, is also implemented to help automatically identify safe navigable areas in emergency situations. The developed GIS package is shared online as an open source project called NavSpace, available for validation and extension, e.g., indoor navigation service. This work would promote the development of ice navigation support system and potentially enhance the safety of ice navigation in the Arctic sea.
In recent years, there has been tremendous growth in the field of indoor and outdoor positioning ... more In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type.
Towards a Spatiotemporal Database Model for Canadian Ice Service Portal
ABSTRACT A well-designed spatio-temporal database plays a key role in storing and manipulating in... more ABSTRACT A well-designed spatio-temporal database plays a key role in storing and manipulating increasingly explosive geographic big data, especially in its support for the development and application such as web-based online services. In this work, we aimed to design a spatio-temporal database structure that is not only scalable to manage past (over 45 years) and continuously retired data in the Canadian Ice Service (CIS) Archive, but also extensible for supporting web-based sea ice data services, processing services and service APIs. We first introduced the data collection procedure in the CIS, and then analyzed the data items. Based on the above analyses and basic data items, we defined and created a spatio-temporal database structure, such as weekly ice charts and ice graphs. This designed database structure was implemented as an archive database server using the latest ArcGIS Server and Oracle, based on which we developed an online web-based prototype. By monitoring the database responses on server side and accessing speed from web clients, the performance of the designed database was objectively assessed.
This paper investigates the hierarchical structures of 29 selected European countries from the pe... more This paper investigates the hierarchical structures of 29 selected European countries from the perspective of blocks and natural cities and makes an across-country comparison among the countries. Blocks are minimum cycles consisting of road segments in the road network of a whole country; natural cities are defined as the aggregations of small blocks. We test the size distributions of blocks and natural cities at the country level and find that both exhibit heavy-tailed distributions. The power law distribution of city sizes indicates the presence of the scaling property. Therefore, the cities in a country can be repeatedly grouped into a similar two-tier structure of head and tail via the head/tail division rule. The ascending tiers represent the small, medium, large and mega cities. Accordingly, a simple model is developed to evaluate and cross compare the degree of similarity and stability of the scaling properties and hierarchical structures of cities. Moreover, cities and block...
ISPRS International Journal of Geo-Information, 2013
In this paper, we explore spatio-temporal clusters using massive floating car data from a complex... more In this paper, we explore spatio-temporal clusters using massive floating car data from a complex network perspective. We analyzed over 85 million taxicab GPS points (floating car data) collected in Wuhan, Hubei, China. Low-speed and stop points were selected to generate spatio-temporal clusters, which indicated the typical stop-and-go movement pattern in real-world traffic congestion. We found that the sizes of spatio-temporal clusters exhibited a power law distribution. This implies the presence of a scaling property; i.e., they can be naturally divided into a strong hierarchical structure: long time-duration ones (a low percentage) whose values lie above the mean value and short ones (a high percentage) whose values lie below. The spatio-temporal clusters at different levels represented the degree of traffic congestions, for example the higher the level, the worse the traffic congestions. Moreover, the distribution of traffic congestions varied spatio-temporally and demonstrated a multinuclear structure in urban road networks, which suggested there is a correlation to the corresponding internal mobile regularities of an urban system.
Classification of land use and land cover from remote sensing images has been widely used in natu... more Classification of land use and land cover from remote sensing images has been widely used in natural resources and urban information management. The variability and complex background of land use in high-resolution imagery poses greater challenges for remote sensing semantic segmentation. To obtain multi-scale semantic information and improve the classification accuracy of land-use types in remote sensing images, the deep learning models have been wildly focused on. Inspired by the idea of the atrous-spatial pyramid pooling (ASPP) framework, an improved deep learning model named RAANet (Residual ASPP with Attention Net) is constructed in this paper, which constructed a new residual ASPP by embedding the attention module and residual structure into the ASPP. There are 5 dilated attention convolution units and a residual unit in its encoder. The former is used to obtain important semantic information at more scales, and residual units are used to reduce the complexity of the network t...
International Journal of Geographical Information Science, 2012
Scaling of geographic space refers to the fact that for a large geographic area its small constit... more Scaling of geographic space refers to the fact that for a large geographic area its small constituents or units are much more common than the large ones. This paper develops a novel perspective to the scaling of geographic space using large street networks involving both cities and countryside. Given a street network of an entire country, we decompose the street network into individual blocks, each of which forms a minimum ring or cycle such as city blocks and field blocks. The block sizes demonstrate the scaling property, i.e., far more small blocks than large ones. Interestingly, we find that the mean of all the block sizes can easily separate between small and large blocks-a high percentage (e.g., 90%) of smaller ones and a low percentage (e.g., 10%) of larger ones. Based on this regularity, termed as the head/tail division rule, we propose an approach to delineating city boundaries by grouping the smaller blocks. The extracted city sizes for the three largest European countries (France, Germany and UK) exhibit power law distributions. We further define the concept of border number as a topological distance of a block far from the outmost border to map the center(s) of the country and the city. We draw an analogy between a country and a city (or geographic space in general) with a complex organism like the human body or the human brain to further elaborate on the power of this block perspective in reflecting the structure or patterns of geographic space.
International Journal of Geographical Information Science, 2012
Axial lines are defined as the longest visibility lines for representing individual linear spaces... more Axial lines are defined as the longest visibility lines for representing individual linear spaces in urban environments. The least number of axial lines that cover the free space of an urban environment or the space between buildings constitute what is often called an axial map. This is a fundamental tool in space syntax, a theory developed by Bill Hillier and his colleagues for characterizing the underlying urban morphologies. For a long time, generating axial lines with help of some graphic software has been a tedious manual process that is criticized for being time consuming, subjective, or even arbitrary. In this paper, we redefine axial lines as the least number of individual straight line segments mutually intersected along natural streets that are generated from street center lines using the Gestalt principle of good continuity. Based on this new definition, we develop an automatic solution to generating the newly defined axial lines from street center lines. We apply this solution to six typical street networks (three from North America and three from Europe), and generate a new set of axial lines for analyzing the urban morphologies. Through a comparison study between the new axial lines and the conventional or old axial lines, and between the new axial lines and natural streets, we demonstrate with empirical evidence that the newly defined axial lines are a better alternative in capturing the underlying urban structure.
ISPRS International Journal of Geo-Information, 2022
Environmental exposure of people plays an important role in assessing the quality of human life. ... more Environmental exposure of people plays an important role in assessing the quality of human life. The most existing methods that estimate the environmental exposure either focus on the individual level or do not consider human mobility. This paper adopts a vector field generated from the observed locations of human activities to model the environmental exposure at the population level. An improved vector-field-generation method was developed by considering people’s decision-making factors, and we proposed two indicators, i.e., the total exposure indicator (TEI) and the average exposure indicator (AEI), to assess various social groups’ environmental exposure. A case study about the risky environmental exposure of coronavirus disease 2019 (COVID-19) was conducted in Guangzhou, China. Over 900 participants with various socioeconomic backgrounds were involved in the questionnaire, and the survey-based activity locations were extracted to generate the vector field using the improved metho...
International Journal of Environmental Research and Public Health, 2021
With the COVID-19 vaccination widely implemented in most countries, propelled by the need to revi... more With the COVID-19 vaccination widely implemented in most countries, propelled by the need to revive the tourism economy, there is a growing prospect for relieving the social distancing regulation and reopening borders in tourism-oriented countries and regions. This need incentivizes stakeholders to develop border control strategies that fully evaluate health risks if mandatory quarantines are lifted. In this study, we have employed a computational approach to investigate the contact tracing integrated policy in different border-reopening scenarios in Hong Kong, China. Explicitly, by reconstructing the COVID-19 transmission from historical data, specific scenarios with joint effects of digital contact tracing and other concurrent measures (i.e., controlling arrival population and community nonpharmacological interventions) are applied to forecast the future development of the pandemic. Built on a modified SEIR epidemic model with a 30% vaccination coverage, the results suggest that s...
Revealing urban functions in cities can be an essential means to describe the characteristics of ... more Revealing urban functions in cities can be an essential means to describe the characteristics of human activities and places. Through the lens of points of interest and tourist online reviews collected in downtown Hong Kong, this study develops a semantic-based framework to detect and compare urban functional identities. The findings depict a unique image of city identity for the downtown area in Hong Kong that contains miscellaneous urban vibrancies. Ultimately, a profound insight is yielded in our study for the understanding of local activities, which can provide human-centric implications for evidence-based urban planning and establish real-world cognitions to the public.
Existing trajectory patterns, such as flock, convoy, swarm, and gathering, are to detect moving c... more Existing trajectory patterns, such as flock, convoy, swarm, and gathering, are to detect moving clusters staying or travelling together for a certain time period. But these patterns model group movement behaviors after moving objects’ gathering together. This may result in loosing golden opportunities to detect emergency incidents earlier, such as traffic congestion and serious stampedes. In this work, we propose a novel group pattern, called converging, which can model converging behaviors of moving objects. As a proof-of-concept, we implemented a visual analytic system GEDetector based on trajectory streams to detect gathering events as early as possible. A user-friendly interface is designed to help users gain insights into gathering events from spatial and temporal aspects. Finally, we demonstrate the effectiveness and efficiency of our system by using a real world dataset.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2021
Relationship between urban diversity and urban vitality is imperative for guiding better design i... more Relationship between urban diversity and urban vitality is imperative for guiding better design in urban development, although existing frameworks are not able to efficiently examine the relationship at multiple scales. In this article, we propose a new framework to integrate nighttime light (NTL) imagery and multisource urban data into multiscale geographically weighted regression (MGWR) models to examine the varying relationship between diversity and vitality across space and time. NTL is used as a proxy for urban nighttime vitality. Public transport, taxi transit, and points of interest data are used to derive three aspects of urban diversity indices: ridership diversity, spatial interaction diversity, and built environment diversity. By comparing the models in holiday and nonholiday weeks in Shenzhen, China, the NTL-based vitality proxy was found to be strongly correlated with the urban diversity indices, given by the satisfactory goodness of fit (r-squared = 0.9) of the MGWR models. The spatially varying relationships between diversity indices and nighttime vitality were observed and patterns discussed. The analysis of the coefficients revealed the importance of stable public transport and fluctuating taxi trips for nighttime vitality. The new index proposed for the diversity of spatial interaction (DSI) is a strong indicator for nighttime vitality, adding to existing vitality indicators. Furthermore, this study found that DSI and density of catering have less temporal variation, indicating their robustness in measuring nighttime vitality.
Urban functional area (UFA) recognition is one of the most important strategies for achieving sus... more Urban functional area (UFA) recognition is one of the most important strategies for achieving sustainable city development. As remote-sensing and social-sensing data sources have increasingly become available, UFA recognition has received a significant amount of attention. Research on UFA recognition that uses a single dataset suffers from a low update frequency or low spatial resolution, while data fusion-based methods are limited in efficiency and accuracy. This paper proposes an integrated model to identify UFA using satellite images and taxi global positioning system (GPS) trajectories in four steps. First, blocks were generated as spatial units in the study area, and the spatiotemporal information entropy of the taxi GPS trajectory (STET) for each block was calculated. Second, a 24-hour time-frequency series was formed based on the pick-up and drop-off points extracted from taxi trajectories and used as the interpretation indicator of the blocks. The K-Means++ and k-Nearest Nei...
IEEE Intelligent Transportation Systems Magazine, 2021
In prior research, a statistically cheap method was developed to monitor transportation network p... more In prior research, a statistically cheap method was developed to monitor transportation network performance by using only a few groups of agents without having to forecast the population flows. The current study validates this "multi-agent inverse optimization" method using taxi GPS trajectories data from the city of Wuhan, China. Using a controlled 2062-link network environment and different GPS data processing algorithms, an online monitoring environment is simulated using the real data over a 4-hour period. Results show that using only samples from one OD pair, the multi-agent inverse optimization method can learn network parameters such that forecasted travel times have a 0.23 correlation with the observed travel times. By increasing to monitoring from just two OD pairs, the correlation improves further to 0.56.
Received signal strength indicator (RSSI)-based positioning is suitable for large-scale applicati... more Received signal strength indicator (RSSI)-based positioning is suitable for large-scale applications due to its advantages of low cost and high accuracy. However, it suffers from low stability because RSSI is easily blocked and easily interfered with by objects and environmental effects. Therefore, this paper proposed a tri-partition RSSI classification and its tracing algorithm as an RSSI filter. The proposed filter shows an available feature, where small test RSSI samples gain a low deviation of less than 1 dBm from a large RSSI sample collected about 10 min, and the sub-classification RSSIs conform to normal distribution when the minimum sample count is greater than 20. The proposed filter also offers several advantages compared to the mean filter, including lower variance range with an overall range of around 1 dBm, 25.9% decreased sample variance, and 65% probability of mitigating RSSI left-skewness. We experimentally confirmed the proposed filter worked in the path-loss expone...
International Journal of Environmental Research and Public Health, 2021
The measurement of medical service accessibility is typically based on driving or Euclidean dista... more The measurement of medical service accessibility is typically based on driving or Euclidean distance. However, in most non-emergency cases, public transport is the travel mode used by the public to access medical services. Yet, there has been little evaluation of the public transport system-based inequality of medical service accessibility. This work uses massive real smart card data (SCD) and an improved potential model to estimate the public transport-based medical service accessibility in Beijing, China. These real SCD data are used to calculate travel costs in terms of time and distance, and medical service accessibility is estimated using an improved potential model. The spatiotemporal variations and patterns of medical service accessibility are explored, and the results show that it is unevenly spatiotemporally distributed across the study area. For example, medical service accessibility in urban areas is higher than that in suburban areas, accessibility during peak periods is...
This paper proposes a novel method for dynamically extracting and monitoring the entrances of are... more This paper proposes a novel method for dynamically extracting and monitoring the entrances of areas of interest (AOIs). Most AOIs in China, such as buildings and communities, are enclosed by walls and are only accessible via one or more entrances. The entrances are not marked on most maps for route planning and navigation in an accurate way. In this work, the extraction scheme of the entrances is based on taxi trajectory data with a 30 s sampling time interval. After fine-grained data cleaning, the position accuracy of the drop-off points extracted from taxi trajectory data is guaranteed. Next, the location of the entrances is extracted, combining the density-based spatial clustering of applications with noise (DBSCAN) with the boundary of the AOI under the constraint of the road network. Based on the above processing, the dynamic update scheme of the entrance is designed. First, a time series analysis is conducted using the clusters of drop-off points within the adjacent AOI, and t...
ISPRS International Journal of Geo-Information, 2019
Public transport plays an important role in developing sustainable cities. A better understanding... more Public transport plays an important role in developing sustainable cities. A better understanding of how different public transit modes (bus, metro, and taxi) interact with each other will provide better sustainable strategies to transport and urban planners. However, most existing studies are either limited to small-scale surveys or focused on the identification of general interaction patterns during times of regular traffic. Transient demographic changes in a city (i.e., many people moving out and in) can lead to significant changes in such interaction patterns and provide a useful context for better investigating the changes in these patterns. Despite that, little has been done to explore how such interaction patterns change and how they are linked to the built environment from the perspective of transient demographic changes using urban big data. In this paper, the tap-in-tap-out smart card data of bus/metro and taxi GPS trajectory data before and after the Chinese Spring Festiv...
Ubiquitous taxi trajectory data has made it possible to apply it to different types of travel ana... more Ubiquitous taxi trajectory data has made it possible to apply it to different types of travel analysis. Of interest is the need to allow someone to monitor travel momentum and associated congestion in any location in space in real time. However, despite an abundant literature in taxi data visualization and its applicability to travel analysis, no easy method exists. To measure taxi travel momentum at a location, current methods require filtering taxi trajectories that stop at a location at a particular time range, which is computationally expensive. We propose an alternative, computationally cheaper way based on pre-processing vector fields from the trajectories. Algorithms are formalized for generating vector kernel density to estimate a travel-model-free vector field-based representation of travel momentum in an urban space. The algorithms are shared online as an open source GIS 3D extension called VectorKD. Using 17 million daily taxi GPS points within Beijing over a four-day period, we demonstrate how to generate in real time a series of projections from a continuously updated vector field of taxi travel momentum to query a point of interest anywhere in a city, such as the CBD or the airport. This method allows a policy-maker to automatically identify temporal net influxes of travel demand to a location. The proposed methodology is shown to be over twenty times faster than a conventional selection query of trajectories. We also demonstrate, using taxi data entering the Beijing Capital International Airport and the CBD, how we can quantify in nearly real time the occurrence and magnitude of inbound or outbound queueing and congestion periods due to taxis cruising or waiting for passengers, all without having to fit any mathematical queueing model to the data.
ISPRS International Journal of Geo-Information, 2016
Conventional ice navigation in the sea is manually operated by well-trained navigators, whose exp... more Conventional ice navigation in the sea is manually operated by well-trained navigators, whose experiences are heavily relied upon to guarantee the ship's safety. Despite the increasingly available ice data and information, little has been done to develop an automatic ice navigation support system to better guide ships in the sea. In this study, using the vector-formatted ice data and navigation codes in northern regions, we calculate ice numeral and divide sea area into two parts: continuous navigable area and the counterpart numerous separate unnavigable area. We generate Voronoi Diagrams for the obstacle areas and build a road network-like graph for connections in the sea. Based on such a network, we design and develop a geographic information system (GIS) package to automatically compute the safest-and-shortest routes for different types of ships between origin and destination (OD) pairs. A visibility tool, Isovist, is also implemented to help automatically identify safe navigable areas in emergency situations. The developed GIS package is shared online as an open source project called NavSpace, available for validation and extension, e.g., indoor navigation service. This work would promote the development of ice navigation support system and potentially enhance the safety of ice navigation in the Arctic sea.
In recent years, there has been tremendous growth in the field of indoor and outdoor positioning ... more In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type.
Towards a Spatiotemporal Database Model for Canadian Ice Service Portal
ABSTRACT A well-designed spatio-temporal database plays a key role in storing and manipulating in... more ABSTRACT A well-designed spatio-temporal database plays a key role in storing and manipulating increasingly explosive geographic big data, especially in its support for the development and application such as web-based online services. In this work, we aimed to design a spatio-temporal database structure that is not only scalable to manage past (over 45 years) and continuously retired data in the Canadian Ice Service (CIS) Archive, but also extensible for supporting web-based sea ice data services, processing services and service APIs. We first introduced the data collection procedure in the CIS, and then analyzed the data items. Based on the above analyses and basic data items, we defined and created a spatio-temporal database structure, such as weekly ice charts and ice graphs. This designed database structure was implemented as an archive database server using the latest ArcGIS Server and Oracle, based on which we developed an online web-based prototype. By monitoring the database responses on server side and accessing speed from web clients, the performance of the designed database was objectively assessed.
This paper investigates the hierarchical structures of 29 selected European countries from the pe... more This paper investigates the hierarchical structures of 29 selected European countries from the perspective of blocks and natural cities and makes an across-country comparison among the countries. Blocks are minimum cycles consisting of road segments in the road network of a whole country; natural cities are defined as the aggregations of small blocks. We test the size distributions of blocks and natural cities at the country level and find that both exhibit heavy-tailed distributions. The power law distribution of city sizes indicates the presence of the scaling property. Therefore, the cities in a country can be repeatedly grouped into a similar two-tier structure of head and tail via the head/tail division rule. The ascending tiers represent the small, medium, large and mega cities. Accordingly, a simple model is developed to evaluate and cross compare the degree of similarity and stability of the scaling properties and hierarchical structures of cities. Moreover, cities and block...
ISPRS International Journal of Geo-Information, 2013
In this paper, we explore spatio-temporal clusters using massive floating car data from a complex... more In this paper, we explore spatio-temporal clusters using massive floating car data from a complex network perspective. We analyzed over 85 million taxicab GPS points (floating car data) collected in Wuhan, Hubei, China. Low-speed and stop points were selected to generate spatio-temporal clusters, which indicated the typical stop-and-go movement pattern in real-world traffic congestion. We found that the sizes of spatio-temporal clusters exhibited a power law distribution. This implies the presence of a scaling property; i.e., they can be naturally divided into a strong hierarchical structure: long time-duration ones (a low percentage) whose values lie above the mean value and short ones (a high percentage) whose values lie below. The spatio-temporal clusters at different levels represented the degree of traffic congestions, for example the higher the level, the worse the traffic congestions. Moreover, the distribution of traffic congestions varied spatio-temporally and demonstrated a multinuclear structure in urban road networks, which suggested there is a correlation to the corresponding internal mobile regularities of an urban system.
Classification of land use and land cover from remote sensing images has been widely used in natu... more Classification of land use and land cover from remote sensing images has been widely used in natural resources and urban information management. The variability and complex background of land use in high-resolution imagery poses greater challenges for remote sensing semantic segmentation. To obtain multi-scale semantic information and improve the classification accuracy of land-use types in remote sensing images, the deep learning models have been wildly focused on. Inspired by the idea of the atrous-spatial pyramid pooling (ASPP) framework, an improved deep learning model named RAANet (Residual ASPP with Attention Net) is constructed in this paper, which constructed a new residual ASPP by embedding the attention module and residual structure into the ASPP. There are 5 dilated attention convolution units and a residual unit in its encoder. The former is used to obtain important semantic information at more scales, and residual units are used to reduce the complexity of the network t...
International Journal of Geographical Information Science, 2012
Scaling of geographic space refers to the fact that for a large geographic area its small constit... more Scaling of geographic space refers to the fact that for a large geographic area its small constituents or units are much more common than the large ones. This paper develops a novel perspective to the scaling of geographic space using large street networks involving both cities and countryside. Given a street network of an entire country, we decompose the street network into individual blocks, each of which forms a minimum ring or cycle such as city blocks and field blocks. The block sizes demonstrate the scaling property, i.e., far more small blocks than large ones. Interestingly, we find that the mean of all the block sizes can easily separate between small and large blocks-a high percentage (e.g., 90%) of smaller ones and a low percentage (e.g., 10%) of larger ones. Based on this regularity, termed as the head/tail division rule, we propose an approach to delineating city boundaries by grouping the smaller blocks. The extracted city sizes for the three largest European countries (France, Germany and UK) exhibit power law distributions. We further define the concept of border number as a topological distance of a block far from the outmost border to map the center(s) of the country and the city. We draw an analogy between a country and a city (or geographic space in general) with a complex organism like the human body or the human brain to further elaborate on the power of this block perspective in reflecting the structure or patterns of geographic space.
International Journal of Geographical Information Science, 2012
Axial lines are defined as the longest visibility lines for representing individual linear spaces... more Axial lines are defined as the longest visibility lines for representing individual linear spaces in urban environments. The least number of axial lines that cover the free space of an urban environment or the space between buildings constitute what is often called an axial map. This is a fundamental tool in space syntax, a theory developed by Bill Hillier and his colleagues for characterizing the underlying urban morphologies. For a long time, generating axial lines with help of some graphic software has been a tedious manual process that is criticized for being time consuming, subjective, or even arbitrary. In this paper, we redefine axial lines as the least number of individual straight line segments mutually intersected along natural streets that are generated from street center lines using the Gestalt principle of good continuity. Based on this new definition, we develop an automatic solution to generating the newly defined axial lines from street center lines. We apply this solution to six typical street networks (three from North America and three from Europe), and generate a new set of axial lines for analyzing the urban morphologies. Through a comparison study between the new axial lines and the conventional or old axial lines, and between the new axial lines and natural streets, we demonstrate with empirical evidence that the newly defined axial lines are a better alternative in capturing the underlying urban structure.
Uploads
Papers by Xintao Liu