Qingquan Li

Shenzhen University · President Office

In China, road maintenance milling typically employs uniform-depth milling, where the milling machine operates at a fixed depth without considering the actual conditions of pavement. Addressing this limitation, this paper proposes an innovative method for extracting variable-depth milling parameters for asphalt pavements based on point cloud data....

Particulate organic carbon (POC) plays crucial roles in the global ocean carbon cycle and the oceanic biological pump. Satellite remote sensing has been demonstrated to be an effective technique for the retrieval of surface oceanic POC concentration. However, the complex spatiotemporal variations of the relationships between POC and oceanic optical...

Origin-Destination (OD) flow, as an abstract representation of the object’s movement or interaction, has been used to reveal the movement patterns of human activities and the coupling process of the human-land system. As a developing spatial analysis method, OD flow clustering can be used to identify the dominant trends and spatial structures of ur...

Data mining of network-constrained trajectories has broad applications in the GIScience field. The calculation of a complete trajectory similarity matrix is a key step in various data mining algorithms. However, computing this matrix is computational-intensive for large datasets, as it involves numerous point-to-point shortest-path (PPSP) queries....

Internal deformation monitoring is of great significance to the safe operation and maintenance of dams. Some scholars have carried out dam internal deformation monitoring by pipeline inertial measurement with a pipeline measurement robot, which has improved the monitoring accuracy and efficiency considerably, compared with the traditional monitorin...

Precise deformation surveying is essential for ensuring safety and sustainable development in densely populated cities. Synthetic Aperture Radar Interferometry (InSAR) is a technique well-suited for large-scale deformation measurement. It is widely applied in monitoring geological disasters such as earthquakes, landslides, and volcanoes. However, i...

Informal settlements' geographic and demographic mapping is essential for evaluating human-centric sustainable development in cities, thus fostering the road to Sustainable Development Goal 11. However, fine-grained informal settlements' geographic and demographic information is not well available. To fill the gap, this study proposes an effective...

Accurate urban traffic forecasting is essential for intelligent transportation systems (ITS). However, the majority of existing forecasting methodologies predominantly concentrate on point-based forecasts (e.g., traffic detector forecasts). A limited number of them pay attention to the urban bidirectional road segments and the complex road network...

Ensuring equitable access to health services is crucial for public welfare and social equity, and is a key objective of the United Nations’ Sustainable Development Goals (SDGs). However, existing datasets often define hospital accessibility using travel time to hospitals in geographic dimension only, without considering the supply (hospital capacit...

China is the world's leading CO2 emitter, and achieving carbon reduction without affecting economic development is highly challenging. Unprecedented urban land expansion has led to an abundance of roof resources. Using large-scale earth-observation data from 2020 and scenario analysis, we explore the possible carbon sinks of roof greening and its c...

Accurate satellite retrieval of oceanic particulate organic nitrogen (PON) concentrations could contribute to a better and more comprehensive understanding of global marine biogeochemical processes. However, no satisfactory satellite PON retrieval model could be found in the literature. With an attempt to develop applicable PON models, large divers...

With the coming of the era of Internet of Everything and 5G, streaming data access via a uniform approach is a great challenge with metadata heterogeneity, streaming characteristics, and data inconsistency. Therefore, streaming data access via a uniform approach is a great challenge. In our study, we propose a unified and efficient streaming vehicl...

Pavement cracks are crucial indicators for assessing the structural health of asphalt roads. Existing automated crack detection models depend on large quantities of precisely annotated crack sample data. The irregular morphology of cracks makes manual annotation time-consuming and costly, thereby posing challenges to the practical application of th...

Addressing climate change and urban energy problems is a great challenge. Building Integrated Photovoltaics (BIPV) plays a pivotal role in energy conservation and carbon emission reduction. However, traditional approaches to assessing solar radiation on buildings with physical models are computing-intensive and time-consuming. This study presents a...

To improve the accuracy and efficiency of LiDAR mapping, cooperative simultaneous localization and mapping (SLAM) has been considered for complex large scenes. Recognizing the same positions and detecting global loop closures are important for achieving cooperative SLAM. However, most of the current position recognition and loop closure detection m...

Three-dimensional (3D) mapping is important to achieve early warning for construction safety and support the long-term safety maintenance of tunnels. However, generating 3D point cloud maps of excavation tunnels that tend to be deficient in features, have rough lining structures, and suffer from dynamic construction interference, can be a challengi...

Visual perception technology is an important means to facilitate safe navigation for visually impaired people based on Internet of Things (IoT)-enabled camera sensors. However, due to the rapid development of urban traffic systems, traveling outdoors is becoming increasingly complicated. Visually impaired individuals must implement different types...

Localization information is increasingly crucial for incorporating location context into Internet of Things (IoT) data. As an important task in visual localization, keyframe selection helps effective augmentation of visual odometry. Although considerable progress has been made in the research field of keyframe selection, they have rarely focused on...

This paper presents an activity semantics-based indoor localization approach using smartphones. The activities of pedestrian consist of several continuous activities during the walking process, such as turning at a corner. In our approach, we first use deep learning-based pedestrian dead reckoning (PDR) to obtain the velocities and distances of ped...

Gaining a comprehensive understanding of the characteristics and propagation of precipitation-based meteorological drought to terrestrial water storage (TWS)-derived hydrological drought is of the utmost importance. This study aims to disentangle the frequency–time relationship between precipitation-derived meteorological and TWS-based hydrological...

Disparities between the supply of nighttime economic services and the demand of local residents have caused a series of problems. By linking massive mobile phone data and an anchor-based activity inference algorithm, we propose a data-driven framework to quantify the separate development of the nighttime economy and housing from a human activity st...

Indoor positioning is a critical component for numerous applications and services. However, GNSS systems face challenges in delivering accurate positioning information in indoor environments. Current indoor positioning research primarily concentrates on enhancing the positioning performance of individual terminals through various techniques. As we...

During a pandemic or natural disaster, people may alter transit usage behavior due to perception of changes in the environment. To effectively respond to these crises, it is important for governments and public transit agencies to understand when these changes occurred and how they were affected by relevant policies and responsive strategies. In th...

Track geometry is an important parameter reflecting the safety of bridge railway, which is of great significance for the structure control of railway track. The measurement of track geometry is an indispensable part of structural health monitoring for bridge railway. However, existing methods for track static track geometry measurement are inadequa...

Thermal images capture temperature information of the environments instead of texture, making it well suitable for obtaining position in dark environments. Many methods have been proposed to handle RGB images while thermal image-based localization methods are not well studied. To address it, we propose, DarkLoc+, a thermal image-based indoor locali...

A robust back-end module with loop closure detection is crucial for accurate positioning and mapping in LiDAR-based Simultaneous Localization and Mapping (SLAM) systems, particularly in Internet of Things (IoT) environments where multiple devices collaborate. Traditional methods that rely on images or point clouds often fail in environments with si...

Accurate atmospheric correction (AC) is one fundamental and essential step for successful ocean colour remote-sensing applications. Currently, most ACs and the associated ocean colour remote-sensing applications are restricted to solar zenith angles (SZAs) lower than 70°. The ACs under high SZAs present degraded accuracy or even failure problems, r...

Urban traffic anomaly diagnosis is crucial for urban road management and smart city construction. Most existing methods perform anomaly detection from a data-driven perspective and ignore the unique spatiotemporal characteristics of traffic anomalies, resulting in reduced accuracy or incorrect extraction of anomalies. In this study, we integrate ge...

There is a growing interest in the optimization of vehicle fleets management in urban environments. However, limited attention has been paid to the integrated optimization of electric taxi fleets accounting for different operations as well as complex spatiotem-poral demand dynamics. To this end, this study develops a real-time recommendation framew...

Social distancing and contact tracing are effective nonpharmaceutical means to ensure public safety and control the rapid spread of infectious diseases. Internet of Things (IoT) sensors can provide reliable data sources for contact tracing, especially in urban public areas. However, existing contact tracing studies mainly use 2D coordinates or dist...

Asia stands out as a priority for urgent biodiversity conservation due to its large protected areas (PAs) and threatened species. Since the 21st century, both the highlands and lowlands of Asia have been experiencing the dramatic human expansion. However, the threat degree of human expansion to biodiversity is poorly understood. Here, the threat de...

With the rising travel demand of crowds, urban road networks are under increasing pressure, which makes them progressively more fragile. Accurate identification of critical intersections is essential for urban management, resource allocation and traffic supervision. However, existing intersection evaluation methods fail to fully exploit transportat...

Clustering the trajectories of vehicles moving on road networks is a key data mining technique for understanding human mobility patterns, as well as their interactions with urban environments. The development of efficient and scalable trajectory clustering algorithms, however, still faces challenges because of the computational costs when measuring...

As one of the most densely populated and rapidly growing metropolitan areas worldwide, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China has been developing extensive metro networks to relieve the escalating traffic congestion inner cities and to shorten public transport time inter cities. Metro construction possibly triggers ground def...

The South-to-North Water Diversion Project (SNWDP) is a megaproject which has been constructed to alleviate imbalanced water resource distribution between northern and southern China. It encompasses three routes distributed in the east, central, and west of China, respectively. The central route (CR) of the SNWDP starts from the Danjiangkou Reservo...

Camera-based indoor localization is a fundamental aspect of indoor navigation, virtual reality, and location-based services. Deep learning methods have exhibited remarkable performance with low storage requirements and high efficiency. However, existing methods mainly derive features implicitly for pose regression without considering explicit struc...

A practical back-end module with loop closure detection is very useful and important for a LiDAR simultaneous localization and mapping (SLAM) system to perform high-precision positioning and mapping tasks. However, most existing loop closure detection methods are based on images or point clouds, and these methods may produce errors when the structu...

Waypoint Estimation (WE) has a wide range of applications for indoor walkers, such as fire rescue, and navigation to find exit doors, lifts, or stairs as examples of waypoints, etc. Data-driven waypoint estimation has been on the rise with advancements in deep learning algorithms. The current waypoint estimation methods, however, face two challenge...

The monitoring of internal deformation in rockfill dams using pre-buried flexible pipelines is a promising technique; however, achieving precise measurements over a long-range pipeline is crucial and challenging. In this paper, we present a high-precision pipeline measuring system for monitoring internal deformation in rockfill dams, which can simu...

With the rapid development of robotics, miniaturized and inexpensive robots have gradually entered the public's field of vision. Smartphone-based robots have the potential to provide high-precision indoor localization, and they are easy to promote and apply. In this paper, we propose a tight integrated positioning system based on Wi-Fi round trip t...

In recent years, several novel satellite platforms and sensors have been proposed for the Earth Radiation Budget (ERB). Simulating the sensor-measured signals could be helpful for optimizing the settings of sensors and exploring their potential in ERB. The anisotropic factor, depicting the anisotropy of Earth’s radiation, is essential in the simula...

The availability of Spatiotemporal Big Data has provided a golden opportunity for time geographical studies that have long been constrained by the lack of individual-level data. However, how to store, manage and query a huge number of time geographic entities effectively and efficiently with complex spatiotemporal characteristics and relationships...

Background Mobility restriction was one of the primary measures used to restrain the spread of COVID-19 globally. Governments implemented and relaxed various mobility restriction measures in the absence of evidence for almost 3 years, which caused severe adverse outcomes in terms of health, society, and economy. Objective This study aimed to quanti...

Understanding complex urban systems necessitates untangling the relationships between diverse urban elements such as population, infrastructure, and socioeconomic activities. Scaling laws are basic but effective rules for evaluating a city’s internal growth logic and assessing its efficiency by investigating whether urban indicators scale with popu...

Monitoring the spatiotemporal variations of the Earth Radiation Budget (ERB) could help to improve our understanding of global climate change. The Earth's reflected shortwave and emitted longwave radiation are important components of energy exchange between the Earth-Atmosphere system and outer space, and are main parameters to be measured by ERB s...

As an important task for the management of bike sharing systems, accurate forecast of travel demand could facilitate dispatch and relocation of bicycles to improve user satisfaction. In recent years, many deep learning algorithms have been introduced to improve bicycle usage forecast. A typical practice is to integrate convolutional (CNN) and recur...

Landmark detection technology has a wide range of applications in people's lives, including map correcting, localization and navigation, etc. Besides, landmarks are also utilized to label different areas for automatic floor plan construction. Currently, vision-based landmark detection methods have some limitations, such as light, camera shaking, an...

Steel structures that benefit from having lightweight, ductility, and seismic behaviors are capable of improving the overall performance of civil engineering in environmental protection, project quality, process management, and ease of construction, making the procedure more feasible for builders. The application of steel structure techniques has b...

Image-based indoor localization provides fundamental support for applications such as indoor navigation, virtual reality, and location-based services. Most research focuses on developing methods in good lighting conditions via RGB images; while for low lighting situations, especially at night, RGB-based methods cannot perform well. Depth images are...

High-quality 3D point cloud maps are essential for precise indoor environments modeling. However, constructing such maps in multi-storey indoor environments is challenging due to the presence of narrow non-structural spaces, such as staircases, corners, and corridors with similar textures. Simultaneous localization and mapping (SLAM) in these scene...

Shenzhen has experienced rapid urbanization since the establishment of the Special Economic Zone in 1978. However, it is rare to witness high-speed urbanization in Shenzhen. It is important to study the LUCC progress in Shenzhen (regarding refusing multisource data), which can provide a reference for governments to solve the problems of land resour...

With the development of quadrotor-based location services, accurate indoor quadrotor localization plays an important role in various applications. Tight fusion refers to the process of integrating multisensor data into state estimation for optimization, and finally obtaining pose information. In this article, we propose a novel tight fusion method...

Fine-grained crowd distribution forecasting benefits smart transportation operations and management, such as public transport dispatch, traffic demand prediction, and transport emergency response. Considering the co-evolutionary patterns of crowd distribution, the interactions among places are essential for modelling crowd distribution variations....

Most automated sewer inspection tasks are based on closed-circuit television (CCTV) methods and focus on image classification or object detection but fail to obtain information on fine-grained sewer defects. Targeting the sewer defect detection from a video and performing the sewer inspection in a lightweight, low-cost, and practical manner, this s...

In image-based pipe defect detection research, the effective utilization of the information in the two-dimension (2D) image is directly related to the sampling of the image. The existing inspection methods do not analyze the pipeline imaging but rather directly use the object detection method for defect detection, resulting in a bottleneck problem...

Understanding the relationship between mixed land use and urban vibrancy is vital in advanced urban planning applications. This study presents a Bayesian spatially varying coefficient (SVC) model to explore the spatially nonstationary relationship between mixed land use and urban vibrancy after controlling for other factors. We first use the convol...

Most intensive human activities occur in lowlands. However, sporadic reports indicate that human activities are expanding in some Asian highlands. Here we investigate the expansions of human activities in highlands and their effects over Asia from 2000 to 2020 by combining earth observation data and socioeconomic data. We find that ∼23% of human ac...

The advent of sensor-rich smart devices (e.g., smart-phones) has enabled a lot of applications and services. One of these applications and services is smartphone-based vehicle indoor positioning, which is a key technology for smart car parking and driverless cars. So far, most vehicle indoor positioning solutions either use infrastructures (e.g., W...

Road surface condition detection is an important application for many intelligent transportation systems (ITSs). A manhole cover depression is one of the common factors affecting road conditions. Smartphones are equipped with different sensors, which can be used to collect image data and inertial data. A new large-scale manhole cover detection data...

The spatial information has been widely utilized in Spectral Mixture Analysis (SMA) studies over the years. However, the spatial autocorrelation, as a prerequisite of these studies, was seldomly examined. In the complex urban systems, it remains largely unknown whether and how land cover spectra at different locations are spatially autocorrelated a...

Particle size distribution (PSD), which is an important characteristic of marine suspended particles, plays a role in how light transfers in the ocean and impacts the ocean’s inherent optical properties (IOPs). However, PSD properties and the correlations with IOPs are rarely reported in coastal waters with complex optical properties. This study in...

The integrity and accuracy of the pedestrian road network is the key to ensuring pedestrian navigation services. Most of the current pedestrian road networks are constructed based on outdoor road facilities, lacking data support for indoor walkable paths, and cannot provide accurate and true optimal path planning services in navigation applications...