A5021209111- Soil Geostatistics and Mapping
- Remote Sensing in Agriculture
- Geochemistry and Geologic Mapping
- Land Use and Ecosystem Services
- Spectroscopy and Chemometric Analyses
- Remote Sensing and LiDAR Applications
- Atmospheric chemistry and aerosols
- Heavy metals in environment
- Soil erosion and sediment transport
- Atmospheric aerosols and clouds
- Soil Moisture and Remote Sensing
- Soil Carbon and Nitrogen Dynamics
- Smart Agriculture and AI
- Moyamoya disease diagnosis and treatment
- Plant Water Relations and Carbon Dynamics
- Remote Sensing and Land Use
- Remote-Sensing Image Classification
- Hydrology and Watershed Management Studies
- Cryptography and Data Security
- Blockchain Technology Applications and Security
- Air Quality and Health Impacts
- Flood Risk Assessment and Management
- Cerebrovascular and Carotid Artery Diseases
- Neurological Complications and Syndromes
- Atmospheric and Environmental Gas Dynamics
Shenzhen Polytechnic
2022-2025
Chongqing University
2023-2025
Huawei Technologies (China)
2025
Shenzhen University
2019-2024
Gannan Medical University
2024
University of Pittsburgh
2020-2024
Northwest A&F University
2024
Zhejiang Normal University
2024
Beijing Jiaotong University
2022-2024
Harbin Medical University
2020-2024
Soil moisture content (SMC) is an important factor that affects agricultural development in arid regions. Compared with the space-borne remote sensing system, unmanned aerial vehicle (UAV) has been widely used because of its stronger controllability and higher resolution. It also provides a more convenient method for monitoring SMC than normal measurement methods includes field sampling oven-drying techniques. However, research based on UAV hyperspectral data not yet formed standard...
Soils constitute one of the most critical natural resources and maintaining their health is vital for agricultural development ecological sustainability, providing many essential ecosystem services. Driven by climatic variations anthropogenic activities, soil degradation has become a global issue that seriously threatens environment food security. Remote sensing (RS) technologies have been widely used to investigate as it highly efficient, time-saving, broad-scope. This review encompasses...
Unmanned aerial vehicle (UAV)-based hyperspectral remote sensing is an important monitoring technology for the soil moisture content (SMC) of agroecological systems in arid regions. This develops precision farming and agricultural informatization. However, data are generally used mining. In this study, UAV-based imaging with a resolution o 4 cm totaling 70 samples (0–10 cm) were collected from farmland (2.5 × 104 m2) near Fukang City, Xinjiang Uygur Autonomous Region, China. Four estimation...
Soil salinization is one of the most common forms land degradation. The detection and assessment soil salinity critical for prevention environmental deterioration especially in arid semi-arid areas. This study introduced fractional derivative pretreatment visible near infrared (VIS-NIR) spectroscopy. samples (n = 400) collected from Ebinur Lake Wetland, Xinjiang Uyghur Autonomous Region (XUAR), China, were used as dataset. After measuring spectral reflectance laboratory, raw was preprocessed...
The vegetation index (VI) has been successfully used to monitor the growth and predict yield of agricultural crops. In this paper, a long-term observation was conducted for prediction maize using an unmanned aerial vehicle (UAV) estimations chlorophyll contents SPAD-502. A new termed as modified red blue VI (MRBVI) developed yields by establishing relationships between MRBVI- SPAD-502-based contents. coefficients determination (R2s) were 0.462 0.570 in contents’ predictions MRBVI, results...
Timely monitoring and precise estimation of the leaf chlorophyll contents maize are crucial for agricultural practices. The scale effects very important as calculated vegetation index (VI) were quantitative remote sensing. In this study, investigated by analyzing linear relationships between VI from red–green–blue (RGB) images unmanned aerial vehicles (UAV) ground measured using SPAD-502. impacts assessed applying different flight altitudes highest coefficient determination (R2) can reach...
Soil salinization has hampered the achievement of sustainable development goals (SDGs) in many countries worldwide. Several have recently launched hyperspectral remote sensing satellites, opening new avenues for accurate soil-salinity monitoring. Among them, Gaofen-5 (GF-5) from China a high comprehensive performance, including spectral resolution 5 nm, 330 bands, and signal-to-noise ratio 700. However, potential GF-5 estimating soil salinity is not well understood. In this study, we...
To develop an artificial intelligence (AI) model with radiomics and deep learning (DL) features extracted from CT images to distinguish benign malignant ovarian tumors.We enrolled 149 patients pathologically confirmed tumors. A total of 185 tumors were included divided into training testing sets in a 7:3 ratio. All manually segmented preoperative contrast-enhanced images. image using DL. Five models different combinations feature built. Benign classified machine (ML) classifiers. The...
Revealing historical changes in soil organic carbon (SOC) and exploring its future status are important for safeguarding health food security, giving full play to the service function of ecosystems, coping with climate change. However, there is still a gap our understanding SOC stocks China their spatial patterns response Therefore, we attempted fill this knowledge using large amount observation data, digital mapping technology, global circulation models from Coupled Model Inter-comparison...
Monitoring and assessing wetland diversity is crucial for its accurate preservation. Hyperspectral satellites have been proven effective detailed investigations of plant in many places. However, it's unclear whether spectral invert landscape diversity, the inversion accuracy varies with spatial scale. In this study, ZY1-02D hyperspectral remote sensing images Yellow River Estuary were supervised classified by support vector machine. Then, indices (i.e., community richness, Shannon-Wiener...
Soil organic carbon (SOC) is an important soil property that has profound impact on quality and plant growth. With 140 samples collected from Ebinur Lake Wetland National Nature Reserve, Xinjiang Uyghur Autonomous Region of China, this research evaluated the feasibility visible/near infrared (VIS/NIR) spectroscopy data (350-2,500 nm) simulated EO-1 Hyperion to estimate SOC in arid wetland regions. Three machine learning algorithms including Ant Colony Optimization-interval Partial Least...