A5086450404- Remote Sensing in Agriculture
- Plant Water Relations and Carbon Dynamics
- Remote Sensing and LiDAR Applications
- Leaf Properties and Growth Measurement
- Hydrology and Watershed Management Studies
- Smart Agriculture and AI
- Soil Moisture and Remote Sensing
- Hydrology and Drought Analysis
- Crop Yield and Soil Fertility
- Urban Heat Island Mitigation
- Solar Radiation and Photovoltaics
- Spectroscopy and Chemometric Analyses
- Irrigation Practices and Water Management
- Greenhouse Technology and Climate Control
- Land Use and Ecosystem Services
- Climate variability and models
- Soil Geostatistics and Mapping
- Air Quality Monitoring and Forecasting
- Remote Sensing and Land Use
- Water resources management and optimization
- Climate change and permafrost
- Landslides and related hazards
- Climate change impacts on agriculture
- Identification and Quantification in Food
- Hydrological Forecasting Using AI
Yangzhou University
2022-2025
Chinese Academy of Agricultural Sciences
2020-2023
Institute of Crop Sciences
2020-2023
Sanya University
2022-2023
Hohai University
2020-2022
Institute of Agricultural Resources and Regional Planning
2022
State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering
2020-2021
Beijing Water Science and Technology Institute
2021
Measuring leaf area index (LAI) is essential for evaluating crop growth and estimating yield, thereby facilitating high-throughput phenotyping of maize (Zea mays). LAI estimation models use multi-source data from unmanned aerial vehicles (UAVs), but using multimodal to estimate LAI, the effect tassels soil background, remain understudied. Our research aims (1) determine how contribute propose a framework based on remote-sensing data, (2) evaluate robustness adaptability an model that uses...
Abstract. Satellite observations of evapotranspiration (ET) have been widely used for water resources management in China. An accurate ET product with a high spatiotemporal resolution is required research on drought stress and management. However, such currently lacking. Moreover, the performances different estimation algorithms China not clearly studied, especially under environmental conditions. Therefore, aims this study were as follows: (1) to use multisource images generate...
Abstract Accurate and high-resolution crop yield water productivity (CWP) datasets are required to understand predict spatiotemporal variation in agricultural production capacity; however, for maize wheat, two key staple dryland crops China, currently lacking. In this study, we generated evaluated a long-term data series, at 1-km resolution of CWP wheat across based on the multiple remotely sensed indicators random forest algorithm. Results showed that MOD16 products an accurate alternative...
The high proportion of soil background pixels in UAV remote sensing images is an important reason for the uncertainty high-precision leaf area index (LAI) estimation at early growth stages crops. Although traditional method removing from based on canopy coverage (CC) eliminates pure pixels, it can cause spectral saturation and therefore affect accuracy LAI estimation. In this study, a new called reduced contribution (CS) was constructed to improve This be improved by introducing quantitative...
Accurately monitoring the crop water conditions (CWC) is vital for agricultural management. Traditional in situ measurements are limited by inefficiency and lack of spatial information. However, development unmanned aerial vehicle (UAV) applications agriculture now provides a high throughput cost-effective method to obtain field growth Unfortunately, current UAV-based drought indices do not capture time series information, or accuracy limited. This study uses multispectral thermal...
Evapotranspiration (ET) plays a crucial role in the surface water cycle and energy balance, accurate ET estimation is essential for study various domains, including agricultural irrigation, drought monitoring, resource management. Remote sensing (RS) technology presents an efficient approach estimating at regional scales; however, existing RS retrieval algorithms are intricate necessitate multitude of parameters. The land temperature–vegetation index (LST-VI) space method statistical...
Effective estimation of crop yields at a regional scale holds significant importance in facilitating decision-making within the agricultural sector, thereby ensuring grain security. However, traditional ground-based measurement techniques suffer from inefficiencies, and there exists need for reliable, precise, effective method estimating rice yields. In this study, we employed four machine-learning techniques: partial least squares regression (PLSR), support vector (SVR), random forest...
Photosynthesis is the key physiological activity in process of crop growth and plays an irreplaceable role carbon assimilation yield formation. This study extracted rice (Oryza sativa L.) canopy reflectance based on UAV multispectral images analyzed correlation between 25 vegetation indices (VIs), three textural (TIs), net photosynthetic rate (Pn) at different stages. Linear regression (LR), support vector (SVR), gradient boosting decision tree (GBDT), random forest (RF), multilayer...
Understanding the water and carbon cycles within terrestrial ecosystems is crucial for effective monitoring management of regional resources ecological environment. However, physical models like SEB- LUE-based ones can be complex demand extensive input data. In our study, we leveraged multiple variables (vegetation growth, surface moisture, radiative energy, other relative variables) as inputs various regression algorithms, including Multiple Linear Regression (MLR), Random Forest (RFR),...
The accurate estimation of regional crop yields holds significant importance for optimizing subsequent resource allocation and maximizing economic returns in agriculture. Crop yield can be effectively estimated by assessing the overall growth status through long-term remote sensing observations. However, most previous studies have relied on data from one or a few periods estimation, thus lacking comprehensive description entire growth. Furthermore, past algorithms not considered their...
Accurate evapotranspiration (ET) monitoring is important for making scientific irrigation decisions. Unmanned aerial vehicle (UAV) remote sensing platforms allow the flexible and efficient acquisition of field data, providing a valuable approach large-scale ET monitoring. This study aims to enhance accuracy reliability estimation in rice paddies through two synergistic approaches: (1) integrating energy flux diurnal variations into Two-Source Energy Balance (TSEB) model, which considers...
Maize (Zea mays L.), one of the most important agricultural crops in world, which can be devastated by lodging, strike maize during its growing season. lodging affects not only yield but also quality kernels. The identification is helpful to evaluate losses due natural disasters, screen lodging-resistant crop varieties, and optimize field-management strategies. accurate detection inseparable from determination degree helps improve field management crop-production process. An approach was...
Maize is among the most important grain crops. Aboveground biomass (AGB) a key agroecological indicator for crop yield prediction and growth status monitoring, etc. In this study, we propose two new methods, improved algorithm (iCBA) iCBA with piecewise function (iCBA-PF), to estimate maize AGB. Multispectral (MS) images, visible-band (RGB) light detection ranging (LiDAR) data were collected using unmanned aerial vehicles (UAVs). Vegetation indices (VIs) VI-weighted canopy volume model...
Accurate description of surface soil moisture (SSM) in vegetation-covered areas is great significance to water resource management and drought monitoring. To remove the effect vegetation on SSM estimation, index obtained from Sentinel-2 (S2) was applied for content (VWC) estimation. The VWC model substituted into cloud (WCM), thus, estimation developed based WCM. methodology tested at Daxing, Beijing, Gu’an, Hebei, which training validation data were acquired by situ measurements. results...