A5025047397- Remote Sensing in Agriculture
- Remote Sensing and LiDAR Applications
- Land Use and Ecosystem Services
- Luminescence and Fluorescent Materials
- Lanthanide and Transition Metal Complexes
- Organic Light-Emitting Diodes Research
- Soil Carbon and Nitrogen Dynamics
- Climate change and permafrost
- Species Distribution and Climate Change
- Urban Green Space and Health
- Advanced Materials and Mechanics
- Mycorrhizal Fungi and Plant Interactions
- Irrigation Practices and Water Management
- Impact of Light on Environment and Health
- Inorganic Chemistry and Materials
- Advanced Cellulose Research Studies
- Advanced Image Fusion Techniques
- Remote-Sensing Image Classification
- Soil Geostatistics and Mapping
- Ammonia Synthesis and Nitrogen Reduction
- Robotics and Sensor-Based Localization
- Infrared Target Detection Methodologies
- Electric Vehicles and Infrastructure
- Lichen and fungal ecology
- Advanced biosensing and bioanalysis techniques
National University of Singapore
2025
Shanghai Maritime University
2024
Shangqiu Normal University
2024
Nanjing University
2019-2022
Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application
2020-2022
Biological materials, such as bamboo, are naturally optimized composites with exceptional mechanical properties. Inspired by natural composites, traditional methods involve extracting nanofibers from sources and applying them in composite which, however, often results less ideal To address this, this study develops a bottom-up nanofiber assembly strategy to create strong fiber-reinforced hydrogels inspired the hierarchical of bamboo. Self-assembled chitosan-sodium alginate (CSNFs) combined...
The classification of tree species through remote sensing data is great significance to monitoring forest disturbances, biodiversity assessment, and carbon estimation. dense time series a wide swath Sentinel-2 provided the opportunity map accurately in timely manner over large area. Many current studies have applied machine learning (ML) algorithms combined with images classify species, but it still unclear, which algorithm more effective automotive extraction species. In this study, five ML...
The extraction of information about individual trees is essential to supporting the growing fruit in orchard management. Data acquired from spectral sensors mounted on unmanned aerial vehicles (UAVs) have very high spatial and temporal resolution. However, an efficient reliable method for extracting with irregular tree-crown shapes a complicated background lacking. In this study, we developed tested performance approach, based UAV imagery, that includes apple (Plot 1) pear 2). workflow...
The accurate mapping of urban impervious surfaces from remote sensing images is crucial for understanding land-cover change and addressing impervious-surface-change-related environment issues. To date, the authors most studies have built indices to map based on shortwave infrared (SWIR) or thermal (TIR) bands middle–low-spatial-resolution images. However, this limits use high-spatial-resolution data (e.g., GaoFen-2, Quickbird, IKONOS). In addition, separation bare soil has not been...
Accurate assessment of battery State Health (SOH) is crucial for the safe and efficient operation electric vehicles (EVs), which play a significant role in reducing reliance on non-renewable energy sources. This study introduces novel SOH estimation method combining Kolmogorov–Arnold Networks (KAN) Long Short-Term Memory (LSTM) networks. The based fully charged characteristics, extracting key parameters such as voltage, temperature, charging data collected during cycles. Validation was...
Given that forest stand density is an important parameter for studies of carbon, water, and energy cycles a core indicator management, it requires accurate mapping to better assess how impacts the eco-environment. Unfortunately, calculation has long relied on identification individual trees small-scale fine or empirical methods macro estimations large areas, making difficult balance cost accuracy. Thus, this work proposes more efficient method estimate absolute (n/ha) based fractional...
Crop residue left in the field after harvest helps to protect against water and wind erosion, increase soil organic matter, improve quality, so a proper estimate of quantity crop is crucial optimize tillage for research into environmental effects. Although remote-sensing-based techniques cover (CRC) have proven be good tools determining CRC, their application limited by variations moisture soil. In this study, we propose angle index (CRAI) CRC four distinct soils with varying (SM) content...
Being one of the most important infrastructures, airports play a vital role in both civil fields and military fields. However, detect directly based on whole scene remote sensing images (RSIs) with complex background remains challenging. To address this issue, article proposes method that mainly combines spectral features geometric concrete runways to multiple simultaneously from multispectral image medium-high spatial resolution comparatively few bands (contains blue, green, red,...
Plastic-mulching technology has a crucial role to play in modern agriculture by optimizing crop growth environments and enhancing yields. Accurately detecting mapping the distribution of plastic-mulched farmlands (PMFs) is essential for improving both agricultural management production efficiency. By analyzing temporal spectral characteristics PMFs phenological information, we developed phenology-based farmland index (PPMFI). This index, when combined with Sentinel-2 imagery an automated...
A new method of identification technology for forest types, an important and difficult part remote sensing classification, uses object-oriented image classification.It provides a direction type to extract which is based on ZY-3 data. This study applied data the classification method, chose hierarchical segmentation fractal network as evolution combined typical ground objects including spectrum features, texture geometrical characteristics, vegetation indexes, build decision tree model...
During the surgical procedure, repeated puncture would bring great damage to patient and decrease success rate of surgery. Good scene adaptivity robots could reduce possibility occurrence problem. This paper introduces a method for increasing preoperatively image-guided robots. The differential transformation getting Jacobian Matrix is used time spent preparing singularity classification analyzing different types singular points spend less make robot move smooth. With help tumor model,...