Qingfeng Guan
Biographic Data
| ID | 3584394 |
|---|---|
| NAME | Qingfeng Guan |
| GIVEN NAMES | Qingfeng |
| FAMILY NAME | Guan |
| SIGNATURE | GUAN Q |
| AFFILIATIONS | China University of Geosciences |
| ORCID | 0000-0002-7392-3709 |
| VERIFIED | Yes |
| TOTAL WORKS | 43 |
| TOTAL CITATIONS | 33 |
| AUTHOR COUNT | 43 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2005 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 3 |
Decoding future land use dynamics through neighborhood sequences
Discovering the causal mechanism of day-night extreme heat driven by 2D and 3D urban landscape changes
A geographic semantic-driven multimodal fusion LCZ framework for revealing inequality in heat exposure among children and elderly
Dynamic Load Balancing Based on Hypergraph Partitioning for Parallel Geospatial Cellular Automata Models
Parallel computing techniques have been adopted in geospatial cellular automata (CA) models to improve computational efficiency, enabling large-scale complex simulations of land use and land cover (LULC) changes at fine scales. However, the spatial distribution of computational intensity often changes along with the spatiotemporal dynamics of LULC during the simulation, leading to an increase in load imbalance among computing units and degradatio…
Unveiling land competition through interaction networks
CoCA
The impact of sub-pixel scale urban function on urban heat island
Measuring the spatial and size polycentricity
MapGenerator
Automated map generation, especially generating maps from natural language descriptions, not only democratizes access to geographic data but also strengthens decision-making, improves communication and allows for customization. However, map generation faces some challenges, such as lowering the professional threshold, improving generation quality, and ensuring geographic consistency. In recent years, large generative models (e.g. text-to-image mo…
GISedu-GPT
From human mobility to building functions
An Adaptive Spatiotemporal Sampling Method for Optimal Environmental Sensor Placement
The optimal placement of sensors is crucial for the maximization of resource utilization in environmental monitoring. The location optimization methods for maximal coverage are not suitable for applications that aim to predict the values of environmental variables at locations where no sensor is placed. For such a task, spatial sampling strategies have been developed to enhance the prediction accuracy by optimal placement of a limited number of s…
From Street View Imagery to the Countryside
Evaluating residents’ subjective perceptions of the rural environment is crucial for formulating effective rural planning. Due to the difficulty in obtaining rural data and the limitations of traditional questionnaire survey methods, existing research mostly focuses on small-scale perception evaluations in specific areas, making it difficult to reveal rural perception characteristics at the regional scale. To address this issue, our study propose…
Resilience Patterns of Multiscale Human Mobility Under Extreme Rainfall Events Using Massive Individual Trajectory Data
Enhancing Place Emotion Analysis with Multi-View Emotion Recognition from Geo-Tagged Photos
User-generated geo-tagged photos (UGPs) have emerged as a valuable tool for analyzing large-scale tourist place emotions with unprecedented detail. This process involves extracting and analyzing human emotions associated with specific locations. However, previous studies have been limited to analyzing individual faces in the UGPs. This approach falls short of representing the contextual scene characteristics, such as environmental elements and ov…
Applicability and sensitivity analysis of vector cellular automata model for land cover change
HashGAT-VCA
Modeling the Subpixel Land-Use Dynamics and Its Influence on Urban Heat Islands
Causal inference of urban heat island effect and its spatial heterogeneity
MapGPT
Optimizing urban functional land towards “dual carbon” target
Temporal-VCA
Multi-perspective perception of urban relative poverty and its associated factors analysis
Using Zipf's Law to Optimize Urban Spatial Layouts in an Urban Agglomeration Area
The study of the land use optimization of urban agglomerations is of great significance to the rational utilization of land resources and the sustainable development of urban agglomerations. Previous studies have simply regarded the urban agglomeration as a whole area or each city as an isolated individual, without considering the regional coordinated development of urban agglomerations in land use optimization objectives. This study proposed the…
Urban Perception Assessment from Street View Images Based on a Multifeature Integration Encompassing Human Visual Attention
Urban perception is a multifaceted process, spanning from vision to cognitive interpretation. Earlier studies on urban perception assessment have primarily concentrated on the analysis of graphic features of street view images such as color or semantic elements, neglecting the vital human sensory fixation features in cognitive processes. This study leveraged eye-tracking technology to accumulate human visual attention data during emotion scoring …
Simulating urban expansion by incorporating an integrated gravitational field model into a demand-driven random forest-cellular automata model
MapGPT
Gauging urban resilience in the United States during the Covid-19 pandemic via social network analysis
Urban Perception Assessment from Street View Images Based on a Multifeature Integration Encompassing Human Visual Attention
Urban perception is a multifaceted process, spanning from vision to cognitive interpretation. Earlier studies on urban perception assessment have primarily concentrated on the analysis of graphic features of street view images such as color or semantic elements, neglecting the vital human sensory fixation features in cognitive processes. This study leveraged eye-tracking technology to accumulate human visual attention data during emotion scoring …
CarbonVCA
An Artificial-Neural-Network-based, Constrained CA Model for Simulating Urban Growth
Insufficient research has been done on integrating artificial-neural-network-based cel-lular automata (CA) models and constrained CA models, even though both types have been studied for several years. In this paper, a constrained CA model based on an artificial neural network (ANN) was developed to simulate and forecast urban growth. Neural networks can learn from available urban land-use geospatial data and thus deal with redundancy, inaccuracy,…
Optimizing urban functional land towards “dual carbon” target
Multi-perspective perception of urban relative poverty and its associated factors analysis
From Street View Imagery to the Countryside
Evaluating residents’ subjective perceptions of the rural environment is crucial for formulating effective rural planning. Due to the difficulty in obtaining rural data and the limitations of traditional questionnaire survey methods, existing research mostly focuses on small-scale perception evaluations in specific areas, making it difficult to reveal rural perception characteristics at the regional scale. To address this issue, our study propose…
Temporal-VCA
Using Zipf's Law to Optimize Urban Spatial Layouts in an Urban Agglomeration Area
The study of the land use optimization of urban agglomerations is of great significance to the rational utilization of land resources and the sustainable development of urban agglomerations. Previous studies have simply regarded the urban agglomeration as a whole area or each city as an isolated individual, without considering the regional coordinated development of urban agglomerations in land use optimization objectives. This study proposed the…
Under the Dome
The spatial distribution of buildings is one of the key factors influencing the local environment within a city. The quantitative measurement of building distribution can provide critical information for exploring local climate patterns in urban areas. Previous studies mainly focused on the two-dimensional spatial distribution of buildings and ignored the differences in height. In this study, a three-dimensional (3D) urban texture model based on …
Sensing Mixed Urban Land-Use Patterns Using Municipal Water Consumption Time Series
The biased population coverage and short temporal lengths of newly emerged data sets (e.g., data sets of social media, mobile phones, and smart cards) obstruct the effective analysis of long-term dynamics of landuse patterns, particularly in small and developing cities. This study proposed a framework to delineate and analyze mixed land-use patterns and their evolution using municipal water consumption data. A two-step classification strategy was…
An Artificial-Neural-Network-based, Constrained CA Model for Simulating Urban Growth
Insufficient research has been done on integrating artificial-neural-network-based cel-lular automata (CA) models and constrained CA models, even though both types have been studied for several years. In this paper, a constrained CA model based on an artificial neural network (ANN) was developed to simulate and forecast urban growth. Neural networks can learn from available urban land-use geospatial data and thus deal with redundancy, inaccuracy,…
A human-machine adversarial scoring framework for urban perception assessment using street-view images
Though global-coverage urban perception datasets have been recently created using machine learning, their efficacy in accurately assessing local urban perceptions for other countries and regions remains a problem. Here we describe a human-machine adversarial scoring framework using a methodology that incorporates deep learning and iterative feedback with recommendation scores, which allows for the rapid and cost-effective assessment of the local …
Introduction to Big Data Computing for Geospatial Applications
The convergence of big data and geospatial computing has brought challenges and opportunities to GIScience with regards to geospatial data management, processing, analysis, modeling, and visualization. This special issue highlights recent advancements in integrating new computing approaches, spatial methods, and data management strategies to tackle geospatial big data challenges and meanwhile demonstrates the opportunities for using big data for …
Spatiotemporal dynamics and the contributing factors of residential vacancy at a fine scale
Understanding the drivers of sustainable land expansion using a patch-generating land use simulation (PLUS) model
Variability in and mixtures among residential vacancies at granular levels
Spatiotemporal distribution of human trafficking in China and predicting the locations of missing persons
Mixed-cell cellular automata
Discovering the homogeneous geographic domain of human perceptions from street view images
Modeling the dynamics and walking accessibility of urban open spaces under various policy scenarios
Simulating urban expansion by incorporating an integrated gravitational field model into a demand-driven random forest-cellular automata model
Sensing Mixed Urban Land-Use Patterns Using Municipal Water Consumption Time Series
The biased population coverage and short temporal lengths of newly emerged data sets (e.g., data sets of social media, mobile phones, and smart cards) obstruct the effective analysis of long-term dynamics of landuse patterns, particularly in small and developing cities. This study proposed a framework to delineate and analyze mixed land-use patterns and their evolution using municipal water consumption data. A two-step classification strategy was…
Under the Dome
The spatial distribution of buildings is one of the key factors influencing the local environment within a city. The quantitative measurement of building distribution can provide critical information for exploring local climate patterns in urban areas. Previous studies mainly focused on the two-dimensional spatial distribution of buildings and ignored the differences in height. In this study, a three-dimensional (3D) urban texture model based on …
Predicting mobile users' next location using the semantically enriched geo-embedding model and the multilayer attention mechanism
How do urban services facilities affect social segregation among people of different economic levels? A case study of Shenzhen city
Social segregation hinders the development of cities and has become a hot topic in urban research. Existing studies have focused on the difference in the distribution of crowd activities to measure segregation but have ignored the impact of the urban environment on crowd gathering and segregation. To study the impact and understand social segregation more comprehensively, we coupled mobile phone datasets and housing price data to divide city dwel…
CarbonVCA
Extracting the pickpocketing information implied in the built environment by treating it as the anomalies
Gauging urban resilience in the United States during the Covid-19 pandemic via social network analysis
Enhancing Place Emotion Analysis with Multi-View Emotion Recognition from Geo-Tagged Photos
User-generated geo-tagged photos (UGPs) have emerged as a valuable tool for analyzing large-scale tourist place emotions with unprecedented detail. This process involves extracting and analyzing human emotions associated with specific locations. However, previous studies have been limited to analyzing individual faces in the UGPs. This approach falls short of representing the contextual scene characteristics, such as environmental elements and ov…
Applicability and sensitivity analysis of vector cellular automata model for land cover change
HashGAT-VCA
Modeling the Subpixel Land-Use Dynamics and Its Influence on Urban Heat Islands
Causal inference of urban heat island effect and its spatial heterogeneity
MapGPT
Optimizing urban functional land towards “dual carbon” target
Geography (31 works) · Computer Science (28 works) · Land Use and Ecosystem Services (21 works) · Cartography (15 works) · Environmental Science (12 works) · Artificial Intelligence (11 works) · Human Mobility and Location-Based Analysis (11 works) · Cellular automaton (10 works) · Mathematics (10 works) · Psychology (10 works)