| 摘要: |
| 城市不透水面是评估城市生态环境和社会经济的关键指示性因子，对于城市规划和资源管理有着重要意义。本研究以长春市为例，使用2014年Landsat 8影像，基于“植被-不透水面-土壤”理论模型，采用多端元优化的提取方法，依据研究区实际土地覆被特点，选取了高反照度、低反照度、植被、裸土、耕地等五个端元，利用线性光谱模型求算长春市不透水面,利用高分辨率遥感影像高分一号对估算结果进行验证，并对其空间分布格局进行分析。结果表明：基于几何顶点的端元提取方法得到的城市不透水面比例的RMSE为0.126，误差范围在−0.366 — 0.387，而基于多端元优化提取方法获取结果的RMSE为0.079，误差范围在−0.319 — 0.265，且超过80%样本的绝对误差小于0.1，精度有显著提升；长春市绕城高速范围内平均城市不透水面比例为47.4%，整体分布呈现“三角形”特征，南部不透水面分布面积明显高于北部区域。从城市外环到内部一环，城市不透水面比例有明显的递增趋势，三环内比例超过66.7%，不透水面分布密集。总体来说，在城市区域尺度上，采用多端元优化提取方法，利用中等空间分辨率多光谱遥感数据提取城市不透水面精度令人满意。 |
| 关键词: 不透水面 线性光谱模型 多端元优化 Landsat 8 长春 |
| DOI：10.7515/JEE201601009 |
| CSTR：32259.14.JEE201601009 |
| 分类号: |
| 基金项目:国家自然科学基金项目（41301466） |
| 英文基金项目:National Natural Science Foundation of China (41301466) |
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| Estimation of urban impervious surfaces by linear spectral mixture analysis |
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YANG Chaobin, HE Xingyuan, ZHANG Shuwen, TANG Junmei,
BU Kun, YU Lingxue, YAN Fengqin1,2,3
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1. Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China;2. University of Chinese Academy of Sciences, Beijing 100049, China;3. Center for Spatial Information Science and Systems George Mason University, VA 22030, USA
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| Abstract: |
| Background, aim, and scope Urban impervious surface, defined as any surface that can prevent water from infiltrating into the soil, such as roads, parking lots, rooftops, is one of the most important indicators to characterize the degree of urbanization and environmental quality, and is playing an important role in urban planning and resource management. With rapid urbanization, increasing proportions of landscapes have been converted into urban impervious surface. In addition, the expansion of urban impervious surface have great effects of urban thermal environment, urban hydrology and many other fields. However, accurate impervious surface estimation remains challenging due to the complicated urban environment. With the rapid development of remote sensing technology, remote sensing of impervious surfaces in the urban areas has become a hot research topic. Materials and methods In this paper, the urban impervious surfaces of Changchun city is estimated using Landsat8 data in 2014 as a case study. Based on the “vegetation-impervious surface-soil” (V-I-S) model and the features of land cover, an improved method is proposed to extract and synthesize the “most representative” endmembers which are high albedo, low albedo, vegetation, soil and farmland , which is different from the traditional method based on the feature spaces between the three components. Then, after removing water information using Modified Normalized Difference Water Index (MNDWI), linear spectral mixture analysis is applied to estimate the impervious surface due to its simple structure and clear physical meaning. High spatial resolution image GF-1 data (2 m) is used to assess the quality of the impervious surface image. Pearson correlation and linear regression analysis are used to explore the relationship between impervious surfaces based on remote sensing and true values. All of the statistical analyses were carried out with the help of SPSS 19.0. Results The results show that (1) the integration of fraction images based on improved endmembers selection method can provide improved impervious surface image. Accuracy assessment indicates that the root-mean-square error (RMSE) yields 7.95% and 12.6% for impervious surface image based on the improved method and traditional method based on scatterplots. The error of the improved method is between −0.319 and 0.267, and more than 80% of the samples’ absolute error is less than 0.1. In contrast, error of the traditional method is between −0.366 and 0.387, and less than 63% of the samples’ absolute error is less than 0.1. (2) The correlation coefficient of impervious surface based on improved method and true values is 0.967, while the correlation coefficient is 0.939 for traditional method and true values. Both of the results are significant at the 0.05 confidence level. (3)The average impervious surface of the out ring traffic is 47.4% in Changchun city, and the distribution is like a “triangle” indicating that the south area has higher impervious surface areas. From outer to inner ring, there is an obvious increase in the impervious surface area, and the proportion can be as high as 66.7% within the third ring road, meaning less distribution of vegetation and water. Discussion The results also show that the fraction images of low albedo endmembers based on different endmember extraction methods have big differences. While the fraction images of low albedo plays an important role to the accuracy of the result of urban impervious surface based on the linear spectral mixture analysis, indicating that the number and quality of selected endmembers do make differences. So, it is essential to remove non-impervious information from the fraction images of low albedo and high albedo. Conclusions Overall, based on the improved endmember extraction method, Landsat remote sensing data with medium resolution like Landsat OLI can be used to retrieve urban impervious surfaces with promising accuracy. Recommendations and perspectives The improved endmember extraction method proposed in this paper will improve the accuracy of the retrieved urban impervious surface, enrich the theory and case study on urban sustainable development. |
| Key words: impervious surface linear spectral mixture analysis end-member Landsat 8 Changchun |
