| 基于均值变点法提取地形起伏度的影响因素分析——以黄河流域(山西段)为例 |
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| 引用本文： | 宁婷,崔伟,马晓勇. 基于均值变点法提取地形起伏度的影响因素分析——以黄河流域(山西段)为例[J]. 测绘通报, 2022, 0(2): 159-163. DOI: 10.13474/j.cnki.11-2246.2022.0063 |
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| 作者姓名： | 宁婷 崔伟 马晓勇 |
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| 作者单位： | 山西省生态环境监测和应急保障中心(山西省生态环境科学研究院), 山西 太原 030027 |
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| 基金项目： | 山西省省属科研条件质量提升专项（山西能源基地生态环境遥感实验室） |
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| 摘 要： | 地形起伏度因子在宏观尺度生态评估中具有重要作用。均值变点法是确定地形起伏度最佳分析窗口的常用方法，但其影响因素尚缺乏研究。本文以黄河流域(山西段)为例，基于DEM数据和均值变点法提取了研究区地形起伏度，并探讨了分析窗口样本数量、DEM分辨率和地貌类型3种因素的影响。结果表明：(1)分析窗口样本数量对最佳分析窗口取值有明显影响。随着样本数量的增加，变点所在的最佳分析窗口面积也不断增加。(2)DEM分辨率对最佳分析窗口取值有一定影响。分析窗口面积取值范围一致时，基于30 m ASTER GDEM计算得到的最佳分析窗口面积小于基于90 m SRTM DEM的最佳分析窗口面积。(3)地貌类型对最佳分析窗口取值的影响不大。当分析窗口样本数量一致时，不同地貌类型区及整个研究区最佳分析窗口相同或接近。总体而言，分析窗口样本数量是最关键的影响因素。
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| 关 键 词： | DEM 最佳分析窗口 分析窗口样本数量 空间分辨率 地貌类型 |
| 收稿时间： | 2021-01-11 |
| 修稿时间： | 2021-11-07 |
Analysis of factors affecting the extraction of relief amplitude by mean change-point method: taking the Yellow River Basin in Shanxi as an example |
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| NING Ting,CUI Wei,MA Xiaoyong. Analysis of factors affecting the extraction of relief amplitude by mean change-point method: taking the Yellow River Basin in Shanxi as an example[J]. Bulletin of Surveying and Mapping, 2022, 0(2): 159-163. DOI: 10.13474/j.cnki.11-2246.2022.0063 |
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| Authors: | NING Ting CUI Wei MA Xiaoyong |
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| Affiliation: | Shanxi Eco-Environmental Monitoring and Emergency Support Center (Shanxi Academy of Eco-Environmental Sciences), Taiyuan 030027, China |
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| Abstract: | Relief amplitude factor plays an important role in macro-scale ecological assessments. The mean change-point method is the mainstream method for determining the best fit window (BFW) of relief amplitude, but its influencing factors are still lacking in research. Taking the Yellow River Basin in Shanxi as an example, this paper extracts its relief amplitude based on DEM data and the mean change-point method, and explores the effects of three factors, namely number of analysis window samples, DEM resolution and landform type, respectively. The results show that: ① Number of analysis window samples has an important effect on the value of the best fit window. As the number of samples increases, the area of the best fit window where the change-point located also increases. ② DEM resolution has a certain effect on the best fit window value. When the analysis window area has the same value range, the best fit window area calculated based on 30 m ASTER GDEM is always smaller than the best fit window area based on 90 m SRTM DEM. ③ Landform type has little effect on the value of the best fit window. When the number of analysis window samples is the same, the best fit window for different landform areas and the entire study area is always same or similar. In short, number of analysis window samples is the key influencing factor. |
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| Keywords: | digital elevation model best fit window number of analysis window samples spatial resolution landform type |
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