利用非线性NDSI模型进行积雪覆盖率反演研究
Estimating Fractional Snow Cover Based on Nonlinear NDSI Model
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摘要: 基于统计回归的积雪覆盖率反演方法适合提取大范围区域的积雪覆盖率,提出了基于归一化积雪指数(NDSI)的非线性积雪覆盖率回归模型,利用阿拉斯加、西伯利亚和内蒙古地区的样本数据进行回归分析,估计模型参数,并利用建立的回归模型提取天山地区和祁连山地区的积雪覆盖率进行了验证。结果显示,基于NDSI的非线性积雪覆盖率回归模型对样本数据的拟合度和利用模型提取的积雪覆盖率精度相对于线性模型均有一定的提高。Abstract: We propose a non-linear regression model based on normalized snow index(NDSI).The sample data obtained in Alaska,Siberia and Inner Mongolia were used for regression analysis and model parameters estimation.The accuracy of the non-linear regression model was verified and compared with the linear model using the experimental data extract in the Tianshan mountains and Qilianshan mountains.The results show that the proposed model gives a better fit to the sample datas and the ccuracy of the non-linear regression model is higher than the linear model.