坡度分级方法对坡度制图的影响

朱奇峰; 杨勤科; 师动; 王春梅

doi:10.13961/j.cnki.stbctb.2017.03.054

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坡度分级方法对坡度制图的影响

实验研究

- 坡度分级方法对坡度制图的影响
- Influence of Slope Classification Method on Slope Mapping
- 水土保持通报 2017年37卷第3期页码：314-320
- 作者机构：
  
  西北大学城市与环境学院,陕西,西安,710127
- 作者简介：
- 基金信息：
  
  国家自然科学基金项目“地表坡度的统计分布理论模型研究”（41371274），“黄土丘陵沟壑区侵蚀地形空间频率层次性研究”（41301284）
- DOI：10.13961/j.cnki.stbctb.2017.03.054
  中图分类号：
- 纸质出版：2017
- 稿件说明：
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朱奇峰, 杨勤科, 师动, 等. 坡度分级方法对坡度制图的影响[J]. 水土保持通报, 2017,37(3):314-320.

ZHU Qifeng, YANG Qinke, SHI Dong, et al. Influence of Slope Classification Method on Slope Mapping[J]. Bulletin of Soiland Water Conservation, 2017, 37(3): 314-320.
朱奇峰, 杨勤科, 师动, 等. 坡度分级方法对坡度制图的影响[J]. 水土保持通报, 2017,37(3):314-320. DOI： 10.13961/j.cnki.stbctb.2017.03.054.

ZHU Qifeng, YANG Qinke, SHI Dong, et al. Influence of Slope Classification Method on Slope Mapping[J]. Bulletin of Soiland Water Conservation, 2017, 37(3): 314-320. DOI： 10.13961/j.cnki.stbctb.2017.03.054.

摘要

[目的] 利用多种分级方法进行坡度制图，探究不同分级方法对坡度制图带来的影响。[方法] 选取陕西省绥德县，陕西省眉县境内的秦岭山区，黑龙江拜泉县的3个样区，用多种分级法对坡度进行分级，利用量化指标分析坡度分级对坡度格局和统计分布的影响。[结果] （1）就一个样区而言，分位数或Evans分级法比较好；不同地区比较，选用统一分级方案较好；（2）分级后的坡度空间变异急剧减少；（3）所有分级都使坡度信息有所损失；（4）所有分级均难以准确表现坡度的统计分布规律。[结论] （1）坡度表面和自然断点分级方法效果较好。（2）随着分级间距的增加，坡度信息量快速减少。（3）坡度统计分布的分析须用坡度表面和自然断点分级进行制图。

Abstract

[Objective] A variety of slope classification methods was applied for slope mapping to explore the influence of different methods on them.[Methods] We selected three sites that are in Suide County of Shaanxi Province

Qinling Mountains in Meixian County of Shaanxi Province and Baiquan County of Heilongjiang Province as the case study areas. A variety of slope classification methods were applied to classify slope. Using the quantitative indicators

we analyzed the spatial pattern and statistical distribution characteristics of slope map.[Results] (1) For specific site mapping

quantile or Evans classification method is better; while for comparison of different sites

unified classification scheme is better; (2) Spatial variation decreased dramatically after slope was classified; (3) All slope classification methods lose some slope information; (4) All slope classification schemes were difficult to represent statistical distribution law of slope accurately.[Conclusion] (1) The slope surface and natural breakpoint methods are better; (2) With the increase of grading space

slope information declines rapidly in a power function; (3) Statistical distribution of slope is better to be mapped with slope surface and natural breakpoint methods.

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