北京、天津和唐山不透水面遥感估算研究
文献类型：学位论文
| 作者 | 岳玉娟 |
| 学位类别 | 博士后 |
| 答辩日期 | 2014-06 |
| 授予单位 | 中国科学院研究生院 |
| 授予地点 | 北京 |
| 导师 | 欧阳志云，周伟奇 |
| 关键词 | 不透水面 TM 影像 NDISI法 NDVI二元法 LSU法 MESMA法 Impervious surface Remote sensing NDISI NDVI Binary Method LSU MESMA |
| 其他题名 | Remote Sensing of Impervious Surface for the Beijing-Tianjin-Tangshan Urban Agglomeration |
| 学位专业 | 生物学 |
| 中文摘要 | 城市不透水面（Impervious surface Area, ISA）不仅可以作为城市化程度的指标，也是衡量环境质量的重要指标。利用遥感手段准确提取城市不透水面并分析其空间扩张过程，对生态城市建设具有重要意义。以北京、天津和唐山为代表的重点城市人口增长、城市扩张和经济发展很快，京津唐地区面临的生态环境压力越来越大，水资源短缺、沙尘暴、水土流失、城市空气污染、植被退化、湿地减少和生物多样性减少是该地区最为突出的生态环境问题。为了掌握京津冀城市群的三个重点城市北京、天津和唐山不透水面分布格局，本研究基于2010年年度Landsat 5 TM遥感影像采用归一化不透水面指数（Normalized Difference Impervious Surface Index，NDISI），归一化植被指数（Normalized Difference Vegetation Index, NDVI）二元法、线性光谱分解法（Linear spectral unmixing，LSU）和多端元的光谱混合分析法（Multi-endmember Spectral Mixture Analysis, MESMA），进行不透水面信息遥感估算，掌握北京、天津和唐山不透水面分布情况。研究结论如下： （1）采用NDISI法、NDVI二元法、LSU法和MESMA法对北京六环内的Landsat 5 TM影像进行不透水面遥感估算， LSU法获取结果最好，RMSE为9.0%；MESMA法次之；NDVI二元法能满足精度要求。 （2） 采用NDVI二元法和LSU法对北京、天津和唐山研究区的Landsat 5 TM影像进行不透水面遥感估算， LSU法能满足精度要求，RMSE为20.6%。 （3）对研究区不透水率各阈值段像元面积展开了分析，其中0.8-1的阈值段面积约占0.7-1阈值段面积的4/5，0.7-1阈值段面积为4199.3平方公里，约占全区面积的1/7。对三个城市不透水率各阈值段像元面积展开了分析，在值域0.7-1之间，北京、天津和唐山三个城市相比较，北京面积最大，天津次之，唐山最小。在值域0.7-1之间的面积，北京约占全区面积的10.5%，天津约占全区面积的12.4%，唐山约占全区面积的6.9%。 （4）城市中心区不透水面遥感估算要优于城市郊区。LSU法和NDVI二元法应用于不透水面遥感提取具有一定的区域局限性，遥感影像面积增大，不透水面遥感估算精度变差。 V （5）对北京、天津和唐山三个城市分别画四条线进行不透水面分布趋势分析，对比三个城市趋势线上不透水率为0.4的断裂点到城市中心距离所构成的面积，可以看出北京区域最大，且比另外两个城市大出很多，天津次之，唐山最小。 （6）研究三个城市ISA与NPP（Net Primary Productivity，净初级生产力）的相关关系，研究结果显示：在北京区域，当ISA在0-0.4区间时，随着不透水率增大，NPP减小，关系明显；当ISA在0.7-1区间时，不透水率对NPP的影响不明显。在天津和唐山区域，随着ISA增大，NPP减小, 全区间趋势比较一致，且不及北京区域ISA在0-0.4区间的关系明显。 |
| 英文摘要 | Impervious surface areas (ISA) are mainly anthropogenic features such as paved roads, rooftops, driveways, sidewalks, and parking lots that are covered by impenetrable materials. With the urban expansion, vegetation and soils are replaced by impervious surfaces, which become a major ecological and environmental concern. This is because the increase of impervious surfaces generally leads to the decrease in vegetation, wetlands and agricultural lands, and consequently, to a series of environmental problems, such as the decease of groundwater recharge, the increase of surface runoffs and flood frequency and urban heat islands. The study area - Beijing-Tianjin-Tangshan urban agglomeration, is the typical area of impervious surface expansion. The percent cover of impervious surfaces, as well as its spatial pattern, has been widely used as an indicator to quantify the urbanization level and urban environmental quality, and is essential to understand the interactions between human and the environment. Therefore, accurate mapping and estimating impervious surfaces is crucial for environmental and resources management. In this study, we compared and evaluated four methods: the Normalized Difference Impervious Surface Index (NDISI) method, the Normalized Difference Vegetation Index (NDVI) based binary approach, the Linear Spectral Unmixing (LSU) method and the Multi-endmember Spectral Mixture Analysis (MESMA) method. The last three approaches have been frequently used in mapping impervious surfaces. Taking the region within the sixth ring road of Beijing as a case study, this research first compared these four approaches on estimating impervious surfaces. We then further extended our study area into the Beijing-Tianjin-Tangshan urban agglomeration, and compared the NDVI based binary approach and the LSU approach on estimating impervious surfaces. The Beijing-Tianjin-Tangshan urban agglomeration includes Beijing City, Tianjin City, Tangshan City and Sanhe City, a region with more than 40 000 square kilometers. Landsat 5 TM image data acquired in 2010 were used for mapping and estimating the impervious surfaces. A layer of impervious surfaces derived from ALOS images with spatial resolution of 2.5 m was used as a reference to evaluate the accuracies of the methods. We found: 1. For the study areas within the sixth ring road of Beijing, the LSU approach achieved best results, with a RMSE of 9.0%, followed by the MESMA approach with a RMSE of 9.5%, and the NDVI based binary approach with a RMSE of 13.5%. The NDISI approach had a root-mean-square error (RMSE) of 34.4%. 2. For the Beijing-Tianjin-Tangshan urban agglomeration, the NDVI based binary approach had a root-mean-square error (RMSE) of 40.2%. The LSU approach was much better for impervious surfaces estimation than the NDVI based method, resulting in a RMSE of 20.0%. The residuals of the LSU approach ranged from -0.4 to 0.4. This accuracy was comparable to those from previous studies that were mostly conducted at a smaller geographical area, generally several thousand square kilometers. Our research expanded the knowledge of existing studies by proving that the LSU approach could be applied to a large study area for mapping impervious surfaces with acceptable accuracy. 3. We analyzed the total area of impervious surfaces in different ranges of percent cover of impervious surfaces for the urban agglomeration. The total area of impervious surfaces in areas with percent cover of impervious surfaces from 0.8 to 1 was 4/5 of it from 0.7 to 1. The total area of impervious surfaces in areas with percent cover of impervious surfaces from 0.7 to 1 was 4199.3 km2, approximately 1/7 of the entire study area. Then we analyzed the total area of impervious surfaces in different ranges of percent cover of impervious surfaces for Beijing City, Tianjin City and Tangshan City, respectively. Among three cities, in areas with percent cover of impervious surfaces from 0.7 to 1, the total area of impervious surfaces in Beijing City was biggest, approximately 10.5% of the entire city, followed by the total area of impervious surfaces in Tianjin City with 12.4% of the entire city and the total area of impervious surfaces in Tangshan City with 6.9% of the entire city. 4. We obtained higher accuracy of impervious surface estimation in urban areas than suburban areas. This is because additional spectrum mixture occurred in suburban area. Additionally, there were certain limitations for LSU approach and the NDVI based binary approach for remote sensing of impervious surface estimation. The accuracy decreased with the increase of the area covered by the image used for remote sensing of impervious surface. 5. We analyzed and compared the trend of impervious surface distribution in Beijing City, Tianjin City and Tangshan City, using impervious surface coverage of 0.4 as the threshold. The results showed that areas with impervious surface coverage greater than 0.4 were much larger in Beijing City than the other two cities. 6. We analyzed the relationship between impervious surface fraction and net primary productivity (NPP). NPP decreased with the increase of impervious surface when the impervious surface coverage was below 0.4 in Beijing City. But with the impervious surface coverage ranging from 0.7 to 1, the relationship became relatively weak. For Tianjing and Tangshan, however, NPP generally decreased with the increase of impervious surface when the impervious surface coverage was from 0 to 1. |
| 公开日期 | 2015-06-15 |
| 源URL | [http://ir.rcees.ac.cn/handle/311016/13468]  |
| 专题 | 生态环境研究中心_城市与区域生态国家重点实验室 |
| 推荐引用方式 GB/T 7714 | 岳玉娟. 北京、天津和唐山不透水面遥感估算研究[D]. 北京. 中国科学院研究生院. 2014. |
入库方式： OAI收割
来源：生态环境研究中心
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