A5102776483- Soil Moisture and Remote Sensing
- Climate change and permafrost
- Precipitation Measurement and Analysis
- Remote Sensing in Agriculture
- Hydrology and Drought Analysis
- Organic Electronics and Photovoltaics
- Conducting polymers and applications
- Crystallization and Solubility Studies
- Remote Sensing and LiDAR Applications
- Climate variability and models
- Molecular Junctions and Nanostructures
- Soil and Unsaturated Flow
- X-ray Diffraction in Crystallography
- Hydrology and Watershed Management Studies
- Synthetic Aperture Radar (SAR) Applications and Techniques
- Meteorological Phenomena and Simulations
- Urban Heat Island Mitigation
- Landslides and related hazards
- Plant Water Relations and Carbon Dynamics
- Remote Sensing and Land Use
University of Chinese Academy of Sciences
2024-2025
China University of Mining and Technology
2022-2024
Polymer self-assembly offers an important route to construct well-defined nanostructures. However, it remains challenging assemble polymers into vertically oriented Here, we use a seed-induced confinement strategy aligned semiconducting nanobrushes from polyfluorene-based on conductive substrates. Mechanism studies elucidate that the immobilized seeds substrate initiate vertical growth of nanobrushes, and supercritical drying as well rigid charged coronas collectively contribute retaining...
Agricultural drought (AD) is a serious threat to food security for many regions worldwide. Understanding the dynamics of AD contributes preventing or mitigating its adverse impacts. Soil moisture (SM) anomaly relatively straightforward indicator AD. However, most previous studies on China were conducted with non-remotely sensed SM indicators due lack long-term and spatial-continuous datasets. Here, such an dataset was created by enhancing satellite remote sensing machine learning method...
Agricultural drought seriously threatens the food and ecological security of most world's developing countries. Data-driven integrated agricultural index with remote sensing provides an effective tool to monitor, evaluate, predict drought. However, there is still a lack comprehensive analytical work on taking machine learning (ML) deep (DL) methods construct such index. In other words, it unclear whether recent DL can improve monitoring as compared currently widely used ML methods....
Soil evaporative efficiency (SEE) was estimated as the relative difference of soil temperature (Ts) to its maximum (Tsmax) and minimum (Tsmin) values at 'minimum maximum' moisture (SM), i.e., SEE= (Tsmax−Ts)/(Tsmax−Tsmin). This thermal indicator SM (SMI) has been proven effective in downscaling satellite microwave some local areas. However, Tsmax Tsmin were usually determined an empirical way which is not conducive a wider range applications or global downscaling. In addition Ts-based SMI...
A novel dual-additive strategy utilizing both solvent and solid additives was used to refine the active-layer morphology in all-polymer solar cells.
The forest is an important part of carbon resources. Forest growing stock volume (GSV) parameter forest. Water Cloud Model (WCM) a simple equation that describes the interaction between ground objects and electromagnetic waves. It has also been applied in estimation GSV. When estimating GSV, WCM parameters are usually calculated using least squares, but squares method relies on field reference data. subsequent development algorithm BIOMASAR uses sliding window does not rely measured However,...
Abstract. Surface soil moisture is vital for Earth's environmental and energy cycles. However, it still rare to have remote sensing data with a long-term temporal extent, global seamless spatial coverage, near-real-time update frequency. Here, we provided dataset from July 1981 December 2022, matching CCI SMAP through novel bias correction method (fitting beta CDF matching, BCDF), filling the gaps of corrected XGBoost Algorithms along various covariates. The new was abbreviated as GSSM has...
Soil evaporative efficiency (SEE) was estimated as the relative difference of soil temperature (Ts) to its maximum (Tsmax) and minimum (Tsmin) values at ‘minimum maximum’ moisture (SM), i.e., SEE=(Tsmax-Ts)/(Tsmax-Tsmin). This thermal indicator SM (SMI) has been proven effective in downscaling satellite microwave for some local areas. However, Tsmax Tsmin were usually determined an empirical way which is not conducive a wider range applications or globally downscaling. In addition Ts-based...