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Estimating Potential Yield of Wheat Production in China Based on Cross-scale Data-model Fusion

机译:基于跨尺度数据模型融合估算中国小麦产量的潜在产量

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The response of the agro-ecological system to the environment includes the response of individual crop's physiological process and the adaption of the crop community to the environment and its change. Observation and simulation at the single scale level cannot fully explain the above process. It is necessary to develop cross-scale agro-ecological models and study the interaction of agro-ecological processes across different scales. Two typical agro-ecological models (DSSAT and AEZ) are employed in this study and a framework for effective cross-scale data-model and model-model fusion is proposed and illustrated based on the application of DSSAT and AEZ models. The site-specific crop model is up-scaled by using this data-model fusion method, observed data from 36 different agricultural observation stations nationwide and historical weather stations observations (1962-1990) are employed and average crop productivity are estimated. Comparison of the estimation results shows the major consistency across the two models and also indicates specific directions for further improvement. This would help the future efforts in cross-scale crop model fusion.
机译:农业生态系统对环境的响应包括对个体作物的生理过程的响应以及作物界的适应环境及其变革。单个比例级别的观察和仿真无法完全解释上述过程。有必要开发跨规模农业生态模型,研究农业生态过程跨越不同尺度的互动。本研究采用了两个典型的农业生态模型(DSSAT和AEZ),并提出了一种基于DSSAT和AEZ模型的应用和示出了有效跨尺度数据模型和模型模型融合的框架。通过使用这种数据模型融合方法,使用该数据模型融合方法升高了特定于特定的作物模型,从全国范围内的36种不同的农业观察站观察到的数据和历史气象站观测(1962-1990),估计平均作物生产率。估计结果的比较显示了两种模型的主要一致性,并且还指示了进一步改进的具体方向。这将有助于未来跨尺度作物模型融合的努力。

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