A5025965072- Remote Sensing in Agriculture
- Plant Water Relations and Carbon Dynamics
- Greenhouse Technology and Climate Control
- Leaf Properties and Growth Measurement
- Climate change impacts on agriculture
- Hydrology and Watershed Management Studies
- Meteorological Phenomena and Simulations
- Rice Cultivation and Yield Improvement
- Soil and Unsaturated Flow
- Effects of Environmental Stressors on Livestock
China Institute of Water Resources and Hydropower Research
2023-2024
National Engineering Research Center for Information Technology in Agriculture
2023
Field surface temperature are essential input of an evapotranspiration (ET) model. Crop canopy and soil temperatures (Tc Ts, respectively) often mixed in the field at early stages, due to changes crop growth, row plant spacing. To ensure accuracy ET estimation, Tc Ts actual positions included should be verified optimized. In this study, underlying data were determined from thermal infrared sensors through automatic monitoring system. These screened partitioned into with algorithm based on...
Early forecasting of crop yield from field to region is important for stabilizing markets and safeguarding food security. Producing a precise result with fewer inputs an ongoing goal the large-area evaluation. We present one approach prediction maize that was explored by incorporating remote-sensing-derived land surface temperature (LST) in-season data into series logistic models only few parameters. Continuous observation were utilized calibrate validate corresponding regional biomass...
Abstract Increased frequency and severity of chilling damage events pose potential risks to crop performance productivity due climate change. Accurate real‐time access is important for growth yield stability based on field's actual environment. To precisely identify regional evaluate the impacts crops, this study presents a model estimate field air temperature in view situations. Land surface temperature, enhanced vegetation index, solar‐induced chlorophyll fluorescence solar declination...
Field surface temperature is an essential input of evapotranspiration (ET) model. To ensure the accuracy ET estimating, field temperatures at their actual position should be verified and optimized as much possible. In this study, underlying monitored from thermal infrared sensors were screened partitioned into crop canopy (Tc) soil (Ts), with help algorithm compiled based on maize growth conditions. Among them, Tc replaces average applied in Seguin-Itier (S-I) model, unified air...