基于Landsat8数据的水体指数模型研究

Study on Water Index Construction Based on Landsat8 Data

为寻找一种环境适应能力强、提取效果稳定的水体指数模型,本文根据可见光到近红外波段水体与常见噪声的光谱差异,构建水体指数GRN-WI。为验证模型的有效性,选取3幅不同环境下的landsat8数据中4个区域进行实验,实验采用K均值聚类法代替手动调节阈值提取水体,将实验结果与5种不同的水体指数进行对比分析。结果表明,GRN-WI能有效提取水体,总体精度优于96.21%,kappa系数优于92.35%,总体误差小于8.15%,总体优于其它指数;模型在含有大量山体阴影、大量薄云和冰雪的环境下较其它指数精度明显提高。

In order to find a water index model with strong environmental adaptability and stable extraction effect, based on the spectral difference between water and common noise in visible to near-infrared bands, this paper constructs water index GRN-WI. In order to verify the validity of the model, four regions in three Landsat8 data under different environments were selected for experiments. K-means clustering method was used in the experiment to extract water instead of manually ad-justing the threshold value, and the experimental results were compared with five different water indexes. The results show that: GRN-WI can effectively extract water;the overall accuracy is better than 96.21%;the Kappa coefficient is better than 92.35%;the overall error is less than 8.15%;the overall is better than other indexes. The model is more accurate than other indexes in the envi-ronment with a lot of mountain shadow, a lot of thin cloud and ice and snow.