A5103234449- Land Use and Ecosystem Services
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Urban Design and Spatial Analysis
- Urban Green Space and Health
- Advanced SAR Imaging Techniques
- Urban Heat Island Mitigation
- Geophysics and Gravity Measurements
- Spatial and Panel Data Analysis
- Remote Sensing in Agriculture
- Remote-Sensing Image Classification
- Satellite Image Processing and Photogrammetry
- COVID-19 epidemiological studies
- Tropical and Extratropical Cyclones Research
- COVID-19 Pandemic Impacts
- Remote Sensing and Land Use
- Planetary Science and Exploration
- Flood Risk Assessment and Management
- Geophysical Methods and Applications
- Environmental Changes in China
- Human Mobility and Location-Based Analysis
- Calibration and Measurement Techniques
- Methane Hydrates and Related Phenomena
- Hydrology and Drought Analysis
- Conservation, Biodiversity, and Resource Management
- Data-Driven Disease Surveillance
Tongji University
2020-2024
Shanghai Ocean University
2018-2022
Institute of Electronics
2021
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...
Urbanization has led to the continuous expansion of built-up areas and ever-growing urban population, threatening quantity quality green space (UGS). Exploring spatiotemporal variations UGS is substantially conducive formulation land-use policies protect ecosystems. As one largest megacities all around world, Shanghai experienced rapid urbanization in past three decades. Insights into how changes response greening are essential for guiding sustainable development. This paper employed...
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,...
Synthetic aperture radar (SAR) image positioning is commonly affected by factors such as platform instability, aging of onboard instruments, and changing observation environments. Thus, geometric calibration needed to improve the accuracy before mapping application. An improved model for SAR images was developed, which does not require long-delayed meteorological data fields. In this method, standard atmospheric Saastamoinen models (SAM-S) are combined delay correction, integrated method...
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)...
Urban systems are featured by spatial autocorrelation, which may produce clustering of model residuals when simulating urban expansion using cellular automata (CA). Accurate identification autocorrelation and reduction residual essential to accurate CA modeling expansion. We developed a new approach (CASEM) error (SEM) that incorporates autocorrelation. Using Zhengzhou City as case study, we calibrated three types models [e.g., logistic regression (Logit), lag (SLM) SEM] from 2000 2010....
Low-lying coastal cities are widely acknowledged as the most densely populated places of urban settlement; they also more vulnerable to risks resulting from intensive land use and cover change, human activities, global climate rising sea levels. This study aims predict how growth is affected by level rise (SLR) in Australian context. We develop an cellular automata model incorporating planning policies potential drivers or constraints under different SLR scenarios adaption strategies....
Urban light rail transit systems have a significant potential to alter future urban development. We developed new cellular automata model (CACG) based on conjugate gradients, and applied it 1) simulate historical development at Jinhua of China, 2) project scenarios incorporating the effect stations (LRTS). The produced realistic pattern for 2018 with overall accuracy exceeding 95%, Kappa coefficient 70% figure-of-merit 32%, indicating model's ability accurately capture dynamics. predicted...
The positioning accuracy of synthetic aperture radar (SAR) images is affected by factors, such as satellite platform instability, aging on-board instruments, and environmental changes. Geometric calibration a commonly employed cost-effective method to enhance the SAR images. classical point-based geometric (PB-GC) model, however, only utilizes location ground control points (GCPs) does not fully exploit spatial relationships among GCPs. This study introduces high-precision that builds upon...
Regional environmental risk (RER) denotes potential threats to the natural environment, human health and socioeconomic development caused by specific risks. It is valuable assess long-term RER in coastal areas with increasing effects of global change. We proposed a new approach considering spatial factors using principal component analysis (PCA) used future land use simulation (FLUS) model project scenarios impact sea level rise (SLR). In our study, status was classified five levels as...
Interferometric SAR (InSAR) is a practical technique to derive three-dimensional information of the earth surface. This paper conducted comparative study DEM reconstruction using single-baseline and multi-baseline InSAR techniques. To improve accuracy generated from InSAR, we improved weight definition approach according coherence coefficients for fusion DEMs. For adopted method based on Maximum Likelihood Estimation (MLE) algorithm which uses external as constraint. A TerraSAR-X dataset...
Abstract COVID-19 is currently spreading widely around the world, causing huge threats on public safety and global society. This study analyzes spatiotemporal spread pattern of in China, reveals China’s epicenters epidemic through spatial clustering, delineates substantial effect distance to Wuhan spread. The 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...
We utilized a two-branch end-to-end network (MultiSenCNN) for land use and cover (LULC) classification flood event mapping using multispectral (MS), panchromatic (Pan) synthetic aperture radar (SAR) images, where flooding was induced by typhoon Lekima in August 2019. Flood damages were assessed considering both the LULC maps. defined three strategies to compare MS + SAR Pan images demonstrate ability of MultiSenCNN algorithm classification. The yielded an average overall accuracy ∼98% Kappa...