A5082813692- Innovative Energy Harvesting Technologies
- Land Use and Ecosystem Services
- Remote-Sensing Image Classification
- Statistical and numerical algorithms
- Remote Sensing and Land Use
- Geophysics and Gravity Measurements
- Remote Sensing in Agriculture
- Magnetic Bearings and Levitation Dynamics
- Railway Engineering and Dynamics
- Geochemistry and Geologic Mapping
- Vibration Control and Rheological Fluids
- Water Quality Monitoring Technologies
- Water Quality Monitoring and Analysis
- Aquatic Ecosystems and Biodiversity
- Marine and coastal ecosystems
- Aquatic Ecosystems and Phytoplankton Dynamics
- Remote Sensing and LiDAR Applications
- Impact of Light on Environment and Health
- Simulation and Modeling Applications
- Child Nutrition and Water Access
- Innovations in Concrete and Construction Materials
- Grouting, Rheology, and Soil Mechanics
- Machine Learning and ELM
- Soil erosion and sediment transport
- Hydrology and Watershed Management Studies
Beijing University of Technology
2025
Northwest A&F University
2025
Tongji University
2014-2024
Commercial Aircraft Corporation of China (China)
2024
Northeast Petroleum University
2024
State Key Laboratory of Remote Sensing Science
2020-2023
South China Agricultural University
2023
Hangzhou Normal University
2023
Jiangsu Changjiang Electronics Technology (China)
2018
Chongqing Vocational Institute of Engineering
2018
Point cloud fitting plays an important role in various applications of laser scanning technology. Currently, the most dominant algorithms are linear least-squares (LS) method and random sample consensus (RANSAC) algorithm, which noises point coordinates influence corresponding stochastic model cannot be fully considered. In this study, mathematical is uniformly described using nonlinear Gauss–Helmert (NGH) model, relationship between measurements parameters, as well effects all errors, can...
Variance component estimation (VCE) is widely applied to adjust random models in the fusion processing of multiple classes observations. In our previous study, least-squares VCE (LS-VCE) for classical Gauss–Markov (GM) model was extended a universal adjustment model: nonlinear Gauss–Helmert (GH) model. However, due its limited ability resist outliers, accuracy estimated variance components and parameters will be negatively affected presence outliers. this article, inflation principle robust...
The way drivers obtain road information has evolved from using only guide signs to both and navigation systems. However, the effectiveness of their separate combination settings not yet been explored, making it difficult determine whether configurations should be optimized. This study explores signs, systems, combination. First, a driving-simulation experiment was conducted. Subsequently, four objective indicators based on driving behavior rather than subjective or attitudinal were selected....
Efficient monitoring of soil inorganic nitrogen is crucial for precision agriculture fertilization and ecological environmental protection. Traditional detection methods are complex challenging real-time in situ measurements. This study proposes an innovative approach based on dielectric response characteristics, enabling non-destructive rapid by analyzing polarization behavior electromagnetic field. Using a vector network analyzer (E5071-C), we systematically measured the spectra red yellow...
Spectral unmixing has been widely used by researchers in quantitative remote sensing due to the prevalence of mixed pixels low- or middle-resolution images. In this article, six linear and nonlinear approaches – fully constrained least squares (FCLS), bilinear-Fan model (BFM), polynomial post-nonlinear (PPNM), supervised fuzzy c-means (SFCM), Support Vector Machine (SVM), artificial neural network (ANN) are applied with multispectral Landsat Thematic Mapper (TM) data order systematically...
Leaf chlorophyll content is crucial for monitoring plant growth and photosynthetic capacity. The Soil Plant Analysis Development (SPAD) values are widely utilized as a relative index in ecological agricultural surveys vegetation remote sensing applications. Multi-spectral cameras cost-effective alternative to hyperspectral monitoring. However, the limited spectral bands of multi-spectral restrict number indices (VIs) that can be synthesized, necessitating exploration other options SPAD...
Non-point source (NPS) pollution has greatly threatened socio-economic development and human health due to water environment degradation. It is very important quantitatively analyze spatio-temporal variation rules of NPS sources surrounding drinking area (DWSA) their impact on the with time-series satellite images. In this paper, we study a systematic remote sensing monitoring method DWSA upper Huangpu River, Shanghai. Firstly, an optimized Extreme Learning Machine (ELM) classification...
Natural wetland ecosystems provide not only important habitats for many wildlife species, but also food migratory and resident animals. In Shanghai, the Chongming Dongtan International Wetland, located at mouth of Yangtze River, plays an role in maintaining both ecosystem health ecological security island. Meanwhile it provides especially stopover overwintering site birds, being middle East Asian-Australasian Flyway. However, with increase development intensity human activities, this suffers...
The registration of 3-D point clouds is an important procedure during the terrestrial laser scanning data processing. Recently, due to their high flexibility and powerful mathematical model, a large amount least-squares-based (LSs-based) methods are proposed widely applied estimate transformation parameters registration. In these LSs-based some based on generalized Gauss–Markov model do not correct influence random errors source clouds. Although there other errors-in-variables (EIV) they...
The spatiotemporal changes of lake water resources objectively reflect not only the process balance, but also ecological environment in area. In recent decades, climate and human activities have caused great impacts on spatial distribution earth’s surface cycle, which has a series crises environmental problems, such as drying-up inland lakes, disappearance oasis, shortage or flooding pollution. Therefore, monitoring fully understanding dynamic lakes is scientific significance for grasping...
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...
Recently, the 3D symmetric transformation, which can simultaneously consider measurement errors of source and target coordinates, has become a hot research topic especially in geodetic datum transformation point clouds registration. However, there are rare studies on outlier resisting for most them only focused similarity transformation. In this study, to unify affine, similarity, rigid transformations, universal expression was abstracted as partial EIV model with equality constraints. Then...
Excessive nitrogen and phosphorus (N/P) input is the important reason for lake eutrophication, a widespread environmental problem that harms freshwater ecosystems worldwide. Land use land cover changes (LULCCs) strongly affect migration transformation process on of N/P. Aiming to improve accuracy N/P estimation deeply understand spatiotemporal impact LULCCs distribution, this study proposed an optimized framework, InVEST-UM, by integrating unmixing algorithm with conventional InVEST model. A...