摘要
雷达遥感可以在极端天气条件下进行对地探测,其主动探测方式对作物长势全天候监测具有重要意义。本文利用2013-2014年陕西杨凌区地面同步测量的43组冬小麦生物量、8组裸土土壤含水量和Radarsat-2全极化雷达数据,对冬小麦生物量进行了估算。利用冬小麦返青期、拔节期、抽穗期和灌浆期生物量和雷达植被指数数据进行回归,并分析了不同作物冠层覆盖条件和土壤含水量对雷达植被指数与作物生物量相关性的影响。结果表明:低冠层覆盖条件下雷达植被指数和冬小麦生物量相关关系较差,其受土壤含水量的影响严重;高冠层覆盖条件下其具有较好的相关关系,回归建模的决定系数(R~2)为0.51,均方根误差为267.61g/m~2。
The active detection of radar remote sensing using microwave bands is the most important means of remote sensing in the extreme weather conditions,it can monitor crop growth at any time. Application of 2013- 14 in the Radarsat-2 data of Yangling area of Shaanxi and the ground synchronous measurement data of SAR,the radar vegetation index in winter wheat crop parameter estimation is studied by 43 winter wheat covered and 8 bare soil experimental sections. In order to analyze the effects of different coverage and soil moisture on the radar vegetation index and crop biomass,the winter wheat in low coverage( green period),high coverage( top stage,heading and filling stage) ground synchronous measurement data and SAR data were analyzed and compared. In the area,the radar vegetation index of the bare soil with different soil moisture and different canopy cover is compared. The results show that the radar vegetation index is influenced by the canopy cover and the soil moisture. The crop biomass is positively related to the crop biomass. Therefore,radar vegetation index is high correlation between the crop parameters,but it should be considered in effect of canopy coverand soil moisture content. In our study,R~2 of the remote sensing retrieval model was 0. 51,the root mean square error was 267. 61 g/m~2.
引文
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