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Integration of wireless sensor network and remote sensing for monitoring and determining irrigation demand in Cyprus

机译:无线传感器网络的集成以及监测和确定塞浦路斯灌溉需求的遥感

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This paper aims to highlight the benefits from the integration of wireless sensor network / meteorological data and remote sensing for monitoring and determine irrigation demand in Cyprus. Estimating evapotranspiration in Cyprus will help, in taking measures for an effective irrigation water management in the future in the island. For this purpose both multi-spectral satellite images (Landsat 7 ETM+ and ASTER) and hydro-meteorological data from wireless sensors and automatic meteorological stations have been used. The wireless sensor network, which consist approximately twenty wireless nodes, was placed in our case study. The wireless sensor network acts as a wide area distributed data collection system deployed to collect and reliably transmit soiland air environmental data to a remote base-station hosted at Cyprus University of Technology. Furthermore auxiliary meteorological field data, from an automatic meteorological station, nearby our case study, where used such as solar radiation, air temperature, air humidity and wind speed. These data were used in conjunction with remote sensing results. Satellite images where used in ERDAS Imagine Software after the necessary processing: geometric rectification, radiometric calibration and atmosphericcorrections. The satellite images were atmospheric corrected and calibrated using spectro-radiometers and sun-photometers measurements taken in situ, in an agricultural area, south-west of the island of Cyprus. Evapotranspiration is difficult to determine since it combines various meteorological and field parameters while in literature quite many different models for estimating ET are indicated. For estimating evapotranspiration from satellite images and the hydro-meteorological data different methods have been evaluated such as FAO Penman-Monteith, Carlson-Buffum and Granger methods. These results have been compared with E-pan methods. Finally a water management irrigation schedule has been applied. The final results are presented and compared with some conclusion remarks.
机译:本文旨在突出无线传感器网络/气象数据的集成和遥感,以监测和确定塞浦路斯灌溉需求的益处。估计塞浦路斯的蒸散将有所帮助,在岛上未来采取有效灌溉水管理的措施。为此目的,已经使用了来自无线传感器和自动气象站的多光谱卫星图像(Landsat 7 Etm +和Aster)和水流气象数据。在我们的案例研究中放置了大约20个无线节点的无线传感器网络。无线传感器网络充当围场分布式数据收集系统,部署以收集和可靠地将土壤和空气环境数据传送到塞浦路斯理工大学托管的远程基站。此外,来自自动气象站的辅助气象现场数据,附近我们的案例研究,其中诸如太阳辐射,空气温度,空气湿度和风速等。这些数据与遥感结果结合使用。在ERDAS中使用的卫星图像在必要的处理后想象软件:几何整流,辐射校准和大气矫正。使用光谱辐射仪和塞浦路斯岛南部,在塞浦路斯岛南的农业区,卫星图像是大气校正和校准的校正和校准。蒸散蒸腾难以确定,因为它结合了各种气象和场参数,而在文献中的相当多的估计ET模型中被指示。为了估算卫星图像的蒸散和水力气象数据不同的方法,例如粮农组织博士 - 蒙特思,卡尔森 - 奶粉和格兰杰方法。将这些结果与E-PAN方法进行了比较。最后,应用了水管理灌溉计划。与一些结论备注进行了最终结果并进行了比较。

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