水稻地上鲜生物量的高光谱遥感估算模型研究

不同氮素营养水平的水稻田间试验,采用单变量线性与非线性拟合模型和逐步回归分析,用1999年试验数据为训练样本,建立水稻鲜生物量的高光谱遥感估算模型,用2000年试验数据作为测试样本数据,对其精度进行评价和验证.结果表明,高光谱变量与地上鲜生物量之间的线性与非线性拟合分析中,一些高光谱特征值如红边波长(λr)、绿峰最大

Study on Hyperspectral Remote Sensing Estimation Models for the Ground Fresh Biomass of Rice

This study was based on the rank difference of the nitrogenous nutrition level by the man-made style through two years rice farm experiment about the difference of the nitrogenous nutrition level. Using linear and non-linear and stepwise multiple regression methods, whose precision had been evaluated and tested on the basis of the experiment data in 2000 acted as train sample, the estimate models for ground fresh biomass of rice was built on the basis of the experiment data in 1999 acted as train sample and evaluated and validated. The results showed that there were some relationships between the characteristic variables of hyperspectra (such as the green peak or red valley of reflectivity or red edge position or sum of 1 st derivative value within red edge ( SD r) and the blue edge ( SD b) or their vegetation indices) and about ground fresh biomass. Based on the results of precision analysis, the model in which the ratio vegetation indices consisted of sum of 1 st derivative value within red edge ( SD r) and the blue edge ( SD b) as variables was the best one of estimating about ground fresh biomass of rice by hyperspectra.