| 基于多特征指标和层次聚类分析的河源区范围自动划分方法研究 |
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| 引用本文： | 邓雅文,侯鹏,蒋卫国,彭凯锋,荔琢,邓越.基于多特征指标和层次聚类分析的河源区范围自动划分方法研究[J].地球信息科学,2022,24(3):469-482. |
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| 作者姓名： | 邓雅文 侯鹏 蒋卫国 彭凯锋 荔琢 邓越 |
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| 作者单位： | 1.北京师范大学地理科学学部 遥感科学国家重点实验室,北京 1008752.北京师范大学地理科学学部 环境遥感与数字城市北京市重点实验室,北京 1008753.生态环境部卫星环境应用中心,北京 100094 |
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| 基金项目： | 国家自然科学基金;国家重点研发计划 |
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| 摘 要： | 河源区边界是重要的国家基础地理信息之一,但除长江、黄河等大江大河外的我国大部分其他中小流域仍缺乏确切的河源区边界信息,需要科学划定河源区边界以支持流域水生态保护相关政策的规划与实施。对此,本文在确立河源区划分原则、明确划分依据的基础上,提出了基于多特征指标和层次聚类分析法的河源区边界划定方法。以沁河流域为研究案例,首先利用均值变点分析法计算沁河流域子流域提取的最佳汇流累积量分位数阈值为0.15%,再基于子流域的多特征指标运用层次聚类分析法最终确定河源区范围边界,并将该方法应用于长江、黄河流域进行验证分析。结果表明：① 基于多特征指标和层次聚类分析提取的沁河流域河源区范围处于河底比降法、水文站点方法得到的源区范围面积之间;② 该方法在长江、黄河流域河源区划分结果的交并比分别达到85.40%和79.99%,侧面验证了本文方法进行河源区边界划分的合理性与适用性。基于多特征指标和层次聚类分析的河源区边界自动划分方法可以简捷高效地识别缺乏明确河源区边界信息的流域河源区范围,为我国河源区生态安全屏障识别、水资源保护相关政策的规划和实施提供科学支撑。
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| 关 键 词： | 河源区边界 多特征指标 层次聚类分析 均值变点分析 子流域提取 多源数据 范围识别 多要素综合 |
| 收稿时间： | 2021-06-14 |
Automatic Extraction of River Source Region Boundary based on Multi-Characteristic Indexes and Hierarchical Cluster Analysis |
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| DENG Yawen,HOU Peng,JIANG Weiguo,PENG Kaifeng,LI Zhuo,DENG Yue.Automatic Extraction of River Source Region Boundary based on Multi-Characteristic Indexes and Hierarchical Cluster Analysis[J].Geo-information Science,2022,24(3):469-482. |
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| Authors: | DENG Yawen HOU Peng JIANG Weiguo PENG Kaifeng LI Zhuo DENG Yue |
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| Institution: | 1. State Key Laboratory of Remote Sensing Science, Faculty of Geographical Science, Beijing Normal University,Beijing 100875, China2. Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China3. Satellite Environment Centre, Ministry of Ecology and Environment, Beijing 100094, China |
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| Abstract: | The boundary of river source region is a kind of important and fundamental national geographical information. Apart from the available river source region boundary information for major rivers such as the Yangtze river and the Yellow River, many middle and small-sized river basins in China still lack explicit and detailed river source region boundary information at present. Thus, it is necessary to scientifically and reasonably delineate the river source region boundary to support the implementation of water-related ecological protection and compensation policy. In this paper, based on established principles for identifying river source region, we proposed a method for river source region boundary demarcation based on multi-characteristic indexes and hierarchical clustering analysis. The Qinhe River Basin was taken as a case study area. Firstly, we utilized mean change point analysis to determine the optimal quantile threshold (0.15%) of flow accumulation to extract sub-catchments units of Qinhe River Basin. Then, the boundary of its river source region was determined by hierarchical clustering analysis based on the multi-characteristic indexes of sub-catchments. The method was also applied to the Yangtze River and Yellow River basins for verification analysis. The results are as follows: (1) The area of the source area of Qinhe River basin based on multi-characteristic indexes and hierarchical cluster analysis was between that obtained by the slope inflection point and hydrological station method; (2) In the Yangtze river basin and the Yellow River basin, the IoU (Intersection over Union) results of this method reached 85.40% and 79.99%, respectively, which indicates that this method is applicable to the extraction of source regions. To summarize, the automatic extraction method for river source region boundary information we proposed could simply and efficiently identify large, middle, and small river source regions’ boundary, which provides scientific support for the identification of ecological security barriers and the implementation of water resources protection policies in China's river source regions. |
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| Keywords: | boundary of river source region multi-characteristic indexes hierarchical cluster analysis mean change-point analysis sub-catchments extraction multi-source data extent identification multi-factor synthesis |
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