A5101469932- Land Use and Ecosystem Services
- Urban Design and Spatial Analysis
- Urban Heat Island Mitigation
- Spatial and Panel Data Analysis
- Advanced Vision and Imaging
- Image and Signal Denoising Methods
- Sparse and Compressive Sensing Techniques
- Video Coding and Compression Technologies
- Urban Green Space and Health
- Advanced Image Processing Techniques
- COVID-19 Pandemic Impacts
- COVID-19 epidemiological studies
- Computer Graphics and Visualization Techniques
- Conservation, Biodiversity, and Resource Management
- Energy, Environment, and Transportation Policies
- Image and Video Quality Assessment
- Market Dynamics and Volatility
- Human Mobility and Location-Based Analysis
- Video Analysis and Summarization
- Face recognition and analysis
- Advanced Image and Video Retrieval Techniques
- Advanced Optical Imaging Technologies
- Biometric Identification and Security
- Monetary Policy and Economic Impact
- Advanced Decision-Making Techniques
Dongguan University of Technology
2019-2025
Shandong Marine Resource and Environment Research Institute
2024
Shandong Academy of Sciences
2024
Qilu University of Technology
2024
Shandong Institute of Automation
2024
Fujian Normal University
2024
Tongji University
2020-2023
State Key Laboratory of Remote Sensing Science
2023
National Institute for Parasitic Diseases
2023
Anhui Medical University
2023
Land surface temperature (LST) is a fundamental Earth parameter, on both regional and global scales. We used seven Landsat images to derive LST at Suzhou City, in spring summer 1996, 2004, 2016, examined the spatial factors that influence patterns. Candidate include (1) land coverage indices, such as normalized difference built-up index (NDBI), vegetation (NDVI), water (NDWI), (2) proximity distances city center, town centers, major roads, (3) location. Our results showed intensity of urban...
The automatic extraction of buildings from high-resolution aerial imagery plays a significant role in many urban applications. Recently, the convolution neural network (CNN) has gained much attention remote sensing field and achieved remarkable performance building segmentation visible images. However, most existing CNN-based methods still have problem tending to produce predictions with poor boundaries. To address this problem, article, novel semantic named edge-detail-network (E-D-Net) is...
Regularization method is an effective tool for synthetic aperture radar (SAR) image despeckling. Design of the regularization terms describing priors plays a vital role in this kind method. In article, new combinational model speckle reduction (CRM-SR) proposed, which term elaborately designed to contain both fractional-order total variation (FrTV) and nonlocal low rank (NLR) regularization. The inherits advantages FrTV NLR improves performance SAR despeckling and, therefore, better...
This paper presents a new robust PCA method for foreground-background separation on freely moving camera video with possible dense and sparse corruptions. Our proposed registers the frames of corrupted then encodes varying perspective arising from motion as missing data in global model. formulation allows our algorithm to produce panoramic background component that automatically stitches together partially overlapping reconstruct full field view. We model registered sum low-rank captures...
The COVID-19 pandemic is currently spreading widely around the world, causing huge threats to public safety and global society. This study analyzes spatiotemporal pattern of in China, reveals China’s epicenters through spatial clustering, delineates substantial effect distance Wuhan on spread. results show that daily new cases mostly occurred before March 6, then moved Grand Bay Area (Shenzhen, Hong Kong Macau). total China were mainly distributed east Huhuanyong Line, where accounted for...
Megacities serve as crucial catalysts for national economic and social development, Shanghai, one of China’s most prominent metropolitan areas, exemplifies this transformative urbanization. To study Shanghai’s urban expansion, we extracted land cover data from 1985 to 2020 using impervious area products simulated expansion dynamics 2021 2035 by employing the cellular automata model. Leveraging these data, analyzed a 50-year period investigated drivers, including factors, population growth,...
Spatiotemporal changes in lake water resources critically affect the livelihoods and sustainable development of local social economy. Understanding evolution resource its influence on economic is important for achieving goals. Taking Africa's largest lake, Lake Victoria, as study area, a framework was developed to investigate long-term (2000–2019) volume variations their development. First, an estimation model constructed based optimized joint process multi-mission altimetry data surface...
Cellular automata (CA) is a spatially explicit modeling tool that has been shown to be effective in simulating urban growth dynamics and projecting future scenarios across scales. At the core of CA models are transition rules define land transformation from non-urban urban. Our objective compare simulation prediction abilities different metaheuristics included R package optimx. We applied five optimx near-optimally parameterize construct for simulation. One advantage their ability optimize...
Incorporating spatial nonstationarity in urban models is essential to accurately capture its spatiotemporal dynamics. Spatially-varying coefficient methods, e.g. geographically weighted regression (GWR) and the Bayesian spatially-varying (BSVC) model, can reflect nonstationarity. However, GWR possess weak ability eliminating negative effects of non-constant variance because method sensitive data outliers bandwidth selection. We proposed a new cellular automata (CA) approach based on BSVC for...
Cellular automata (CA) is a bottom-up self-organizing modeling tool for simulating contagion-like phenomena such as complex land-use change and urban growth. It not known how CA responds to changes in spatial observation scale when larger-scale study area partitioned into subregions, each with its own model. We examined the impact of changing on model growth at UA-Shanghai (a region within one-hour high-speed rail distance from Shanghai) using particle swarm optimization-based (PSO-CA)...