摘要
本文介绍了采用更系统的生物学方法,根据水稻在整个生长期的叶面积指数轨线,按叶面积指数的一次测量值,结合气象和光谱数据及陆地卫星MSS图像,估算大面积水稻产量的方法。 在产量与总截获的关系中,叶面积指数是最重要的参量之一。文中重点分析了由水稻在MSS波段内的光谱数据构成的绿度指数和Suits模式估算叶面积指数的结果。表明,用Suits模式计算的叶面积指数有较高的相关系数和较低的剩余标准差。并用这个方法计算了不同田块的叶面积指数,再根据这些数据和MSS图像建立关系。本文比较了卫星数据和多种绿度指数的关系,认为垂直植被指数(PVI)是估算叶面积指数的最好参量,因为它消除了土壤背景的影响,并用它求出了大面积水稻的叶面积指数分布。再根据已建立的叶面积指数轨线和作物截获的有效光合辐射(TIPAR)关系,计算了TIPAR,编制了产置分布图。文章分析了计算结果,并以1983年的例子进一步讨论了该方法的适用性。结果表明,预测的水稻产量和实测产量间的相关系数为0.9左右。
The purpose of this study is to present a method of estimating rice yield from remotely sensed data, which offers a biological based. The principle and technique of the method were described in the former paper (No. 4, Vol. 3, 1988. 'Remote sensing of Environment CHINA'). The technique of estimating rice yield with Landsat images is presented here. Firstly, the vajues of leaf area index (LAI) at ten sites in each experimental field are estimated with the data of MSS spectral reflectance using the Suits method, and the mean value of leaf area index (LAI) of each field (about 20-40 ha.) is obtained. Secondly, a relationship between PV1 obtained from Landsat images and LAI is derived. The leaf area index (LAI) of each field in whole study region is estimated using this relation. Thirdly, the rice yield can be estimated from the LAI of each field using the method presented in the former paper. At the end, some aspects of effecting the accuracy of the estimated yield from this method are discussed.
出处
《环境遥感》
CSCD
1989年第1期73-80,共8页
关键词
水稻
产量
光谱模型
卫星图像
Estimation of rice yield by remote sensing Leaf area index Spectral model
