Conference Agenda

Using the soil evapotranspiration model based on the improved Priestley Taylor (PT) method, combined with fAPAR data and surface reflectance (albedo) data from the MODIS, monthly soil evapotranspiration with 5 km spatial resolution in typical agricultural areas in China and Europe from 2017 to 2021 was estimated. Moreover, the analysis of the spatial and temporal variation characteristics of evapotranspiration were carried out. The model result was validated using field data obtained from farming observation stations in North China, and RMSE and R² were calculated. It showed that the soil evapotranspiration estimation model achieved good results in the farmland area, where the RMSE was around 1 mm and R² was around 0.8, indicating that the model can well simulate the spatial and temporal variation of soil evapotranspiration in the farmland and is suitable for further analysis of key evapotranspiration variables on spatial and temporal bases covering typical farming areas.

The easy access to the high-resolution satellite data at 10-to-30-meter resolution makes the agricultural remote sensing technology develop even faster. Under the support of the Dragon program, the sentinel series satellite in Europe and GF series satellite in China are providing the data options for agricultural monitoring as well as enhancing the capability of agricultural monitoring in general. Because of the diversified cultivation patterns in China, there are existing the big fields with one crop type and the small fields with the mosaic of various crop types. This fact is limited the application of satellite data in agricultural monitoring in China, therefore, the users have to make a compromise between the spatial resolution and the size of study area. In general, it had better use even higher resolution satellite image for crop monitoring in order to adapt to the crop cultivation situation in China. This project has made the great progress since the inception of this project. Two types of study areas were selected. The first one is with big fields and good at the development of modern agriculture that is comparable with the European agricultural farms. Another one is the typic northern Chine fields with the conventional agricultural development that is challenging for the agricultural monitoring with remote sensing data. The crop types in the study areas are winter wheat, crop, rice, and vegetable, representing the irrigation agriculture and rain fed agriculture in northern China. The project used the Chinese and European satellite data and the third partner satellite data to retrieve the crop growth and crop management information at field level in order to provide timely information to improve agricultural management. Through this joint project and the heavy involvement of young scientists from Europe and China, the satellite data finely processing and information retrieval algorithm is being exchanged and it is expected to bring a step forwards to support agricultural monitoring at fine scale.