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[IEEE 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Munich, Germany (2019.6.23-2019.6.27)] 2019 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC) - Ultra-Stable Optical Oscillator Transfer to the UV for Primary Thermometry
摘要： To improve the performance of crop models for regional crop yield estimates, a particle filter (PF) was introduced to develop a data assimilation strategy using the Crop Environment Resource Synthesis (CERES)—Wheat model. Two experiments involving winter wheat yield estimations were conducted at a field plot and on a regional scale to test the feasibility of the PF-based data assimilation strategy and to analyze the effects of the PF parameters and spatio-temporal scales of assimilating observations on the performance of the crop model data assimilation. The significant improvements in the yield estimation suggest that PF-based crop model data assimilation is feasible. Winter wheat yields from the field plots were forecasted with a determination coefficient (R2) of 0.87, a root-mean-square error (RMSE) of 251 kg/ha, and a relative error (RE) of 2.95%. An acceptable yield at the county scale was estimated with a R2 of 0.998, a RMSE of 9734 t, and a RE of 4.29%. The optimal yield estimates may be highly dependent on the reasonable spatiotemporal resolution of assimilating observations. A configuration using a particle size of 50, LAI maps with a moderate spatial resolution (e.g., 1 km), and an assimilation interval of 20 d results in a reasonable tradeoff between accuracy and effectiveness in regional applications.
关键词： particle filter (PF),yield estimation,data assimilation,Crop model,leaf area index,remote sensing
更新于2025-09-19 17:13:59
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Solar light distribution inside a greenhouse with the roof area entirely covered with photovoltaic panels
摘要： Most photovoltaic (PV) greenhouses in Europe have maximised the energy production without considering the requirements of the crops, by applying PV panels on most part of the roof area. The aim of this work is to calculate the solar light distribution in a photovoltaic (PV) greenhouse where the entire roof area is covered with PV panels (100% cover ratio). The calculation of the incident global was estimated with clear sky conditions on several observation points located inside the greenhouse at 1.5 m from the ground level. The validation of the simulated data was conducted through measurements inside a PV greenhouse complex located in Florinas, Italy (40°38’38”N; 8°39’31”E), composed by 24 single-span greenhouse modules of 837 m2 each and total area of 2.2 ha. The roof area of each module was completely covered with a monocrystalline PV array with slope of 20° and a rated power of 22 kWp. The results were shown through a map of light distribution on the greenhouse area, which highlighted the most penalised zones and the percentage of available global radiation, compared to the same greenhouse without PV array. Good agreement was shown by the simulated data, compared to measurements (mean R2=0.78). The global radiation on the greenhouse area was 33% on yearly basis, compared to the potential value with no PV panels on the roof. The zones close to the gable walls and the south side wall suffered less shading compared to the central portion of the greenhouse area. The map of cumulated light distribution can support the growers to increase the agronomic sustainability of the PV greenhouse, since it will allow in perspective the identification of species and crop management practices for a profitable cultivation.
关键词： agricultural sustainability,PV greenhouse,crop,model,solar radiation,energy
更新于2025-09-11 14:15:04
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Combination of Crop Growth Model and Radiation Transfer Model with Remote Sensing Data Assimilation for Fapar Estimation
摘要： Accurate assessment of Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) in large scale is significant for crop productivity estimation and climate change analysis. The object of study is to simulate FAPAR in the rice growth period for exploring photosynthetic capacity of rice in large-scale. The daily FAPAR is calculated based on a coupled model consisting of the leaf-canopy radiative transfer model (PROSAIL) and the World Food Study Model (WOFOST). Due to the limitation of the PROSAIL and WOFOST model, we introduced the remote sensing data assimilation method, which assimilated the Normalized Difference Vegetation Index (NDVI) into the coupled model, to improve the prediction accuracy and carry out the large-scale application. The results show high correlation between the simulated FAPAR and the measured data, with the determinate coefficient (??2) of 0.75 in the study area. The spatial distribution of FAPAR is uniform in flat area, which indicates that the rice in the whole study area has well growth condition and photosynthetic capacity. This study suggest that the coupled model (PROSAIL + WOFOST) assimilated with remote sensing data could accurately simulate daily FAPAR during the crop growth period.
关键词： crop model,assimilation,FAPAR,coupled model,PROSAIL
更新于2025-09-10 09:29:36