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Assessing water-limited crop production with a scatterometer based crop growth monitoring system

机译:使用基于散射仪的作物生长监测系统评估水分受限的作物产量

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Soil moisture is one of the most important parameters influencing crop yield. In current crop growth monitoring systems (CGMS) soil moisture is simulated using water budget models that require as input meteorological observations such as rainfall, temperature, and cloud cover. The collection of the meteorological data is expensive and often the station density is low. This poses a problem because, particularly for rainfall, large errors may occur when interpolating the station data to area means. In this paper a new approach for monitoring water-limited crop production is proposed that combines the advantages of conventional crop growth models and a novel remote sensing technique. The system builds upon a CGMS that has been developed by Alterra (formerly DLO Staring Center) and is used operationally in the MARS Project (Monitoring Agriculture with Remote Sensing) by the Joint Research Center of the European Commission to monitor agricultural production in Europe and adjoining countries. However, instead of using simulated soil moisture data based on rainfall observations, the proposed system uses as input soil moisture data retrieved from ERS Scatterometer data, a low resolution active microwave instrument.
机译:土壤水分是影响农作物产量的最重要参数之一。在当前的作物生长监测系统(CGMS)中,使用水预算模型来模拟土壤湿度,而水预算模型需要输入气象观测数据,例如降雨,温度和云量。气象数据的收集是昂贵的,并且站密度通常很低。这带来了一个问题,因为,尤其是对于降雨,将测站数据内插到面积平均值时可能会出现较大的误差。本文提出了一种监测缺水作物产量的新方法,该方法结合了常规作物生长模型的优点和新颖的遥感技术。该系统基于由Alterra(以前是DLO凝视中心)开发的CGMS,并已由欧盟委员会联合研究中心在MARS项目(遥感农业监测)中使用,可用于监视欧洲及其附近的农业生产国家。但是,该提议的系统不是使用基于降雨观测的模拟土壤水分数据,而是使用从ERS散射仪数据(一种低分辨率有源微波仪器)中检索到的土壤水分数据作为输入。

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