| 利用国产GF-1卫星数据实现山区细小河流河宽的自动提取 |
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| 引用本文： | 薛源,李丹,吴保生,傅旭东.利用国产GF-1卫星数据实现山区细小河流河宽的自动提取[J].测绘通报,2020,0(3):12-16. |
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| 作者姓名： | 薛源 李丹 吴保生 傅旭东 |
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| 作者单位： | 清华大学水沙科学与水利水电工程国家重点实验室, 北京 100084 |
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| 基金项目： | 国家自然科学基金重点项目（51639005） |
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| 摘 要： | 以国产GF-1卫星影像为数据源，选取皇甫川流域内山区细小河流密集的上游1421 km2作为研究区域，针对因山区河流河道狭窄、形态复杂等导致的河流边界提取难度大、精度差、河宽无法自动提取的难题，首先利用改进的变异系数法筛选水体指数，再采用改进的决策树法结合DEM河网精确获取河流边界，最后通过自动化河宽提取算法实现对山区细小河流及其河宽的自动提取。结果表明，本文方法对山区河流判别的总体精度为89.5%，有效地排除了山体阴影等地物的干扰。对河宽为0~10 m的极细河流，本文方法提取河宽的误差为18.54%；10~30 m的细小河流，提取误差为12.07%。
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| 关 键 词： | GF-1卫星影像 山区细小河流 河宽 自动提取 改进的决策树 |
| 收稿时间： | 2019-08-31 |
| 修稿时间： | 2019-10-31 |
Automatic extraction of small mountain river information and width based on China-made GF-1 satellites remote sensing images |
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| XUE Yuan,LI Dan,WU Baosheng,FU Xudong.Automatic extraction of small mountain river information and width based on China-made GF-1 satellites remote sensing images[J].Bulletin of Surveying and Mapping,2020,0(3):12-16. |
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| Authors: | XUE Yuan LI Dan WU Baosheng FU Xudong |
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| Institution: | State Key Laboratory of Hydroscience and Engineering, Tsinghua University, Beijing 100084, China |
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| Abstract: | Extraction of high-resolution geomorphic information from remote sensing images is a key technology for supporting the research of mountain rivers. In this research, we propose a DEM-aided approach based on object-based image analysis and improved decision tree classification for water information extraction and present a method for automatic extraction of small river width. We used the 1421 km2 area of upstream of Huangfuchuan River Basin on the Loess Plateau, China, as a case study area. The China-made GF-1 satellite images and the DEM data are implemented as the secondary data source. The results show that the proposed method has a total accuracy as 89.5%. For extremely small rivers with width ranging from 0 to 10 meters, the error of river width extraction by our method is 18.54%. The extraction error of small rivers whose width ranging from 10 to 30 meters is 12.07%. |
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| Keywords: | GF-1 satellite images small mountain rivers river width automatic extraction method improved decision tree classification |
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