“珠海一号”高光谱数据城市不透水面提取研究

Study on extraction of urban impervious surface from "Zhuhai No.1" hyperspectral data

摘要:

不透水面是评估城市化进程和评价城市环境的重要参考指标，研究城市不透水面的空间覆盖程度对城市生态环境保护、宜居城市建设具有重要意义。本文以“珠海一号”高光谱影像为数据源、珠海市陆域为研究区域，选取支持向量机和随机森林机器学习算法，结合光谱特征，实现城市不透水面信息提取。结果表明：使用“珠海一号”高光谱数据提取不透水面可行性较强，且支持向量机算法更适用于“珠海一号”不透水面提取，总体精度和Kappa系数分别达到92.4%、0.78；基于“珠海一号”高光谱数据进行城市不透水面提取，可为城市规划建设、分析城市土地扩张、评估城市灾害风险提供可靠理论依据和数据支撑。

Abstract:

The impervious surface is an important reference index for evaluating the urbanization process and the urban environment. Studying the spatial coverage of urban impervious surface is of great significance for urban ecological environment protection and livable city construction. In this paper, the hyperspectral image of "Zhuhai No.1" is used as the data source, and the land area of Zhuhai City is used as the research area. Support vector machine and random forest machine learning algorithm are selected to combine spectral features to achieve the extraction of urban impervious surface information. The results show that using the hyperspectral data of "Zhuhai 1" to extract the impermeable surface is feasible, and the support vector machine algorithm is more suitable for the extraction of "Zhuhai 1" impermeable surface, with the overall accuracy and Kappa coefficient reaching 92.4% and 0.78; The extraction of urban impervious surface based on "Zhuhai No.1" hyperspectral data can provide reliable theoretical basis and data support for urban planning and construction, analysis of urban land expansion, and assessment of urban disaster risk.