ASCAT土壤湿度数据在新疆干旱监测中的应用
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摘要
截至目前,欧洲气象卫星组织新一代"Met Op"系列卫星搭载的先进的ASCAT散射仪所观测的土壤湿度数据在我国尚未得到应用。本文拟通过使用NOAA的先进算法处理ASCAT土壤湿度数据,并开发干旱预报系统以用于监测新疆土壤水分来预测其干旱情况。文中首次使用ASCAT土壤湿度数据、前沿人工智能技术在新疆干旱监测中,为干旱监测提供了新的研究思路,开发出新的干旱预报系统对土壤水分等级有一定的预报能力,其中新设计的干旱指数-Met Op卫星反演的土壤湿度距平百分数可以有效提高干旱监测的时间精度,便于更好地开展决策服务。
A new generation of EUMESTAT Metop series of satellites equipped with the advanced ASCAT Scatterometer, but the observed soil moisture data has not yet been applied in China. This paper used an advanced algorithm of NOAA to process ASCAT soil moisture data, and developed a drought forecasting system for monitoring soil moisture in Xinjiang and predicting drought conditions. ASCAT soil moisture data, cutting-edge artificial intelligence techniques were firstly used in Xinjiang drought monitoring, it provides a new research ideas for drought monitoring, the new developed drought forecasting system have some forecasting capability for soil moisture levels,and a new design drought index- Met Op,which is soil moisture anomaly percentage from satellite retrieval,can improve the time accuracy of drought monitoring and better serve for the decision making.
A new generation of EUMESTAT Metop series of satellites equipped with the advanced ASCAT Scatterometer, but the observed soil moisture data has not yet been applied in China. This paper used an advanced algorithm of NOAA to process ASCAT soil moisture data, and developed a drought forecasting system for monitoring soil moisture in Xinjiang and predicting drought conditions. ASCAT soil moisture data, cutting-edge artificial intelligence techniques were firstly used in Xinjiang drought monitoring, it provides a new research ideas for drought monitoring, the new developed drought forecasting system have some forecasting capability for soil moisture levels,and a new design drought index- Met Op,which is soil moisture anomaly percentage from satellite retrieval,can improve the time accuracy of drought monitoring and better serve for the decision making.
引文
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[4]陈书林,刘元波,温作民.卫星遥感反演土壤水分研究综述[J].地球科学进展,2012,27(11):1192-1203.
[5]张霄羽,王娇.风云二号静止气象卫星数据估算土壤表面水分方法研究[J].中国生态农业学报,2012,20(7):882-887.
[6]伍漫春,丁建丽,王高峰.基于地表温度—植被指数特征空间的区域土壤水分反演[J].中国沙漠,2012,32(1):148-154.
[7]Wilhite D A.Planning for drought:A methodology,drought assessment,management and planning;theory and case studies[C]//Wilhite D A.Drought Assessment,Management and Planning Theory and Case Studies,1993:87-109.
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[10]魏立涛,郭树军.CBR在气象服务中的应用[J].安徽农业科学,2007,35(18):5350-5351.
[11]Lu J,Xue S,Zhang X,et al.Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment[J].Atmosphere,2014,5(4):788-805.
[12]刘辉权,肖天贵,邱静雅.气象预报预警系统开发中VB与Gr ADS、FORTRAN混合编程[J].成都信息工程学院学报,2011,26(2):208-214.
[13]杨志华,基于FY3B VIRR数据的新疆沙尘天气遥感监测应用研究[J].沙漠与绿洲气象,2014,8(5):48-52.
[14]赵玲,基于MODIS的天山山区草地类型植被指数变化特征及其与气候因子的关系[J].沙漠与绿洲气象,2015,9(2):57-62.
[2]李得勤,段云霞,张述文.土壤湿度观测、模拟和估算研究[J].地球科学进展,2012,27(4):424-434.
[3]师春香,谢正辉,钱辉,等.基于卫星遥感资料的中国区域土壤湿度En KF数据同化[J].中国科学·地球科学,2001,41(3):375-385.
[4]陈书林,刘元波,温作民.卫星遥感反演土壤水分研究综述[J].地球科学进展,2012,27(11):1192-1203.
[5]张霄羽,王娇.风云二号静止气象卫星数据估算土壤表面水分方法研究[J].中国生态农业学报,2012,20(7):882-887.
[6]伍漫春,丁建丽,王高峰.基于地表温度—植被指数特征空间的区域土壤水分反演[J].中国沙漠,2012,32(1):148-154.
[7]Wilhite D A.Planning for drought:A methodology,drought assessment,management and planning;theory and case studies[C]//Wilhite D A.Drought Assessment,Management and Planning Theory and Case Studies,1993:87-109.
[8]TUCKER,CHOUDHURY B J.Satellite remote sensing of drought conditions[J].Remote Sens.Environ,1987,23:243-251.
[9]Kouan F N.NOAA plays leadership role in developing satellite technology for drought watch[J].Earth Obs Mag,1994:18-21.
[10]魏立涛,郭树军.CBR在气象服务中的应用[J].安徽农业科学,2007,35(18):5350-5351.
[11]Lu J,Xue S,Zhang X,et al.Neural Fuzzy Inference System-Based Weather Prediction Model and Its Precipitation Predicting Experiment[J].Atmosphere,2014,5(4):788-805.
[12]刘辉权,肖天贵,邱静雅.气象预报预警系统开发中VB与Gr ADS、FORTRAN混合编程[J].成都信息工程学院学报,2011,26(2):208-214.
[13]杨志华,基于FY3B VIRR数据的新疆沙尘天气遥感监测应用研究[J].沙漠与绿洲气象,2014,8(5):48-52.
[14]赵玲,基于MODIS的天山山区草地类型植被指数变化特征及其与气候因子的关系[J].沙漠与绿洲气象,2015,9(2):57-62.