A5064702980- Land Use and Ecosystem Services
- Machine Learning and Data Classification
- Urban Transport and Accessibility
- Remote Sensing and LiDAR Applications
- Urban Design and Spatial Analysis
- Soil Geostatistics and Mapping
- Environmental Impact and Sustainability
- Human Mobility and Location-Based Analysis
- Urban Green Space and Health
- Remote Sensing and Land Use
- Energy, Environment, Economic Growth
- Data Management and Algorithms
- Spatial and Panel Data Analysis
- Environmental Changes in China
- Urban Heat Island Mitigation
- Housing Market and Economics
- Metaheuristic Optimization Algorithms Research
- Neural Networks and Applications
- Data Visualization and Analytics
- Economic and Environmental Valuation
- COVID-19 epidemiological studies
- Remote Sensing in Agriculture
- Automated Road and Building Extraction
- Remote-Sensing Image Classification
- Geographic Information Systems Studies
Renmin University of China
2021-2025
Wuhan Polytechnic University
2024
Fuzhou Pulmonary Hospital of Fujian
2022
University of North Carolina at Charlotte
2016-2020
Macau University of Science and Technology
2012
Carbon emission inequality has become a critical factor constraining the coordinated development of socio-economic systems and natural environment. This exacerbates disparity in carbon emissions across regions, hindering efforts to achieve sustainable environmental justice. Previous research primarily focused on structure footprints their influencing factors, but there been limited quantitative inequality, particularly from multi-scale perspective. study constructs 250 m-high-resolution...
The urban development of China is changing from incremental expansion to stock renewal mode. study functional areas has become one the important fundamental works in current and high-quality development. In recent years, big spatiotemporal data been well applied function field. However, spatial-temporal evolution characteristics forecasting optimization for mixed-use not examined well. Thus, this study, we proposed a new approach that applies revised information entropy method analyze...
The Catering Service Industry (CSI) experienced profound impacts due to the COVID-19 pandemic. However, long-term and multi-timepoint analysis using big data remained limited, influencing governmental decision-making. We applied Kernel Density Estimation, Shannon Diversity Index, Geographic detector explore spatial heterogeneity determinants of CSI in Beijing during pandemic, with monthly granularity. temporal-spatial dynamics presented a "W"-shaped trend from 2018 2023, pivotal shifts...
The objective of this study is to estimate the biomass and carbon global-level mangroves as a special type wetland. Mangrove ecosystems play an important role in regulating cycling, thus having significant impact on global environmental change. Extensive studies have been conducted for estimation mangrove stock. However, at level has insufficiently investigated because spatial scale interest large most existing are based physically challenging fieldwork surveys that limited local scales....
Feature selection (FS) is a critical step in hyperspectral image (HSI) classification, essential for reducing data dimensionality while preserving classification accuracy. However, FS HSIs remains an NP-hard challenge, as existing swarm intelligence and evolutionary algorithms (SIEAs) often suffer from limited exploration capabilities or susceptibility to local optima, particularly high-dimensional scenarios. To address these challenges, we propose GWOGA, novel hybrid algorithm that combines...
Accurately evaluating territorial space use efficiency is a prerequisite for promoting the realization of high-quality development. Existing evaluation models all treat decision making units (DMUs) as independent individuals, ignoring geospatial effects between geographical spaces, which leads to unreliable results. This study proposes geographic data envelopment analysis (GeoDEA) model, integrating spatially constrained multivariate clustering model with generalized (DEA). The GeoDEA...
Artificial neural networks (ANNs) have been extensively used for the spatially explicit modeling of complex geographic phenomena. However, because complexity computational process, there has an inadequate investigation on parameter configuration networks. Most studies in literature from GIScience rely a trial-and-error approach to select setting ANN-driven spatial models. Hyperparameter optimization provides support selecting optimal architectures ANNs. Thus, this study, we develop automated...
Settlement models help to understand the social–ecological functioning of landscape and associated land use cover change. One issues settlement modeling is that are typically used explore relationship between locations influential factors (e.g., slope aspect). However, few studies in adopted visibility analysis. Landscape provides useful information for understanding human decision-making with establishment settlements. In past years, machine learning algorithms have demonstrated their...
Landscape-index calculation tools play a pivotal role in ecosystem studies and urban-planning research, enabling objective assessments of landscape patterns’ similarities differences. However, the existing encounter limitations, such as inability to visualize indices spatially challenge computing for both vector raster data simultaneously. Based on QGIS development platform, this study presents an innovative framework landscape-index that addresses these limitations. The seamlessly...
Against the backdrop of rapid global economic development, Beijing-Tianjin-Hebei (BTH) region, a pivotal hub and environmentally sensitive area in China, faces significant challenges sustaining its landscape ecosystem. Given region’s strategic importance vulnerability to environmental pressures, this study investigated intricate relationships between ecological risk, urban expansion, growth (EG) BTH region. Utilizing as focal point, we constructed decoupling model at grid scale explore...
Nowadays, geopolitical, extreme weather and other emergencies have exacerbated the global energy crisis, thus, increased urgency of world’s transition to sustainable energy. Sustainable policies play an important role in process transformation. The research on policy is mainly carried out through conventional qualitative quantitative methods, which bibliometrics meta-analysis methods are paid attention to; however, mining analysis semantics relationships between ignored. This paper uses...