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基于不同下垫面的农业干旱遥感监测方法与发展前景
引用本文:张瑶瑶,崔霞,宋清洁,朱高峰.基于不同下垫面的农业干旱遥感监测方法与发展前景[J].草业科学,2017,34(12):2416-2427.
作者姓名:张瑶瑶  崔霞  宋清洁  朱高峰
作者单位:兰州大学资源环境学院 西部环境教育部重点实验室,甘肃 兰州,730000;兰州大学资源环境学院 西部环境教育部重点实验室,甘肃 兰州,730000;兰州大学资源环境学院 西部环境教育部重点实验室,甘肃 兰州,730000;兰州大学资源环境学院 西部环境教育部重点实验室,甘肃 兰州,730000
基金项目:国家自然科学基金项目,高分辨率对地观测系统重大专项
摘    要:干旱是我国农业面临的主要自然灾害之一。利用遥感手段监测农业干旱,针对作物生长发育过程中不同下垫面状况选取适用的监测指标,可以及时、有效地评估干旱对作物生长的影响,从而为各级政府部门制定防灾减灾政策提供重要的依据。本文总结了目前广泛应用的基于不同下垫面状况的农业干旱遥感监测方法,并将这些方法分为适用于裸露地表与低植被覆盖条件的监测方法、适用于中高植被覆盖条件的监测方法及适用于各种下垫面状况的综合监测方法。在此基础上,对未来农业干旱遥感监测发展方向进行了研究与探讨:1)监测数据源由单一数据源向多源数据转变;2)监测指标由单一的气象监测指标向气象、卫星遥感与作物生理物理特征相结合的综合监测指标转变;3)逐步实现"3S"技术集成与数据共享。

关 键 词:农业干旱  下垫面  遥感监测  归一化植被指数

The agricultural drought remote sensing monitoring methods and prospects based on different underlying surface conditions
Abstract:Drought is one of the maj or natural disasters for China's agricultural industry.By selecting asuitable monitoring index based on land surface conditionsduring different growth periods of crops,remote sensing mo-nitoring ofagricultural drought can timely and effectively evaluate the effect of drought on crop growth and pro-vide animportant source for decisions to be made by thegovernment.The present study summarized the widely used agricultural remote sensing monitoring methods,which were based on different land surface conditions. These methods weredivided into three classes:monitoring methods based on bare surface or low vegetation cov-er,monitoring methods based on high vegetation cover,and integrated monitoring methods based on all land cover conditions.In addition,the future development directions of agricultural remote sensing drought monito-ring werestudied and discussed,and included:1)monitoring data beingtransformedfrom asingle data source to multi-source data;2 )monitoring indicatorschangingfrom single meteorological monitoring indicators to acom-prehensive monitoring index,which integratesmeteorological,satellite remote sensing with crop physiological and physical characteristics;3)the 3S technology integration and data sharing.
Keywords:agricultural drought  land surface  remote sensing monitoring  monitoring methods  normalized difference vegetation index
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