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[1]CHEN Xuexiong,CHANG Qingrui,BI Rutian,et al.Comparison Study on the Best Statistical Unit Algorithms of Relief Amplitude[J].Research of Soil and Water Conservation,2018,25(01):52-56.

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Comparison Study on the Best Statistical Unit Algorithms of Relief Amplitude

Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume: 25 Number of periods: 2018 01 Page number: 52-56 Column: Public date: 2018-02-28

Title:: Comparison Study on the Best Statistical Unit Algorithms of Relief Amplitude

Author(s):: CHEN Xuexiong¹, CHANG Qingrui², BI Rutian¹, LIU Zhengchun¹, ZHANG Xiaojun³; 1. College of Resources and Environment, Shanxi Agricultural University, Taigu, Shanxi 030801, China;
2. College of Natural Resources and Environment, Northwest A & F University, Yangling, Shaanxi 712100, China;
3. College of Horticulture, Shanxi Agricultural University, Taigu, Shanxi 030801, China

Keywords:: digital elevation model; relief amplitude; best statistical unit; algorithm comparison; Shanxi Province

CLC:: S157;P237

DOI:: -

Abstract:: Based on the 90-m resolution SRTM DEM data, the relief amplitude of Shanxi Province was extracted with the neighborhood analysis method at different neighborhood windows(2×2, 3×3, 4×4, …, 30×30), the best statistical unit was calculated by using the artificial drawing method, maximum elevation difference method, fuzzy mathematics method, mean change-point analysis method and cumulative sum analysis method, the accuracy and applicability of statistical unit calculation methods was analyzed, and the best statistical unit of relief amplitude in Shanxi Province was determined. The results indicate that the mean change-point analysis method and cumulative sum analysis method are more effective than the artificial drawing method, maximum elevation difference method and fuzzy mathematics method, the best statistical units of the mean change-point analysis method and cumulative sum analysis method are 11×11 (0.980 1 km²) and 14×14 (1.587 6 km²), respectively. The mean change-point analysis method is one of the best ideal methods to calculate the best statistical unit. The best statistical unit is different between different DEM data types and different resolution DEM for the same area.

References:: [1] 刘育成,赵廷宁.基于变点分析法提取废弃采石场地形起伏度的方法[J].水土保持研究,2016,23(3):269-273.
[2] 涂汉明,刘振东.中国地势起伏度研究[J].测绘学报,1991,20(4):311-319.
[3] 刘新华,杨勤科,汤国安.中国地形起伏度的提取及在水土流失定量评价中的应用[J].水土保持通报,2001,21(1):57-59,62.
[4] 马晓微,杨勤科,刘宝元.基于GIS的中国潜在水土流失评价研究[J].水土保持学报,2002,16(4):49-53.
[5] 闫满存,李华梅,王光谦.广东沿海陆地地质环境质量定量评价研究[J].工程地质学报,2000,8(4):416-425.
[6] 祁元,刘勇,杨正华,等.基于GIS的兰州滑坡与泥石流灾害危险性分析[J].冰川冻土,2012,34(1):96-104.
[7] 刘康,欧阳志云,王效科,等.甘肃省生态环境敏感性评价及其空间分布[J].生态学报,2003,23(12):2711-2718.
[8] 凡非得,王克林,熊鹰,等.西南喀斯特区域水土流失敏感性评价及其空间分异特征[J].生态学报,2011,31(21):6353-6362.
[9] 徐天献,王玉宽,傅斌.汶川地震重灾区土壤侵蚀敏感性评价[J].中国水土保持,2011,18(1):39-42.
[10] 赵斌滨,程永锋,丁士君,等.基于SRTM-DEM的我国地势起伏度统计单元研究[J].水利学报,2015,46(S1):284-290.
[11] 陈学兄,常庆瑞,郭碧云,等.基于SRTM DEM数据的中国地形起伏度分析研究[J].应用基础与工程科学学报,2013,21(4):670-678.
[12] 王志恒,胡卓玮,赵文吉,等.应用累积和分析算法的地形起伏度最佳统计单元确定[J].测绘科学,2014,39(6):59-64.
[13] 陈学兄,毕如田,刘正春,等.基于ASTER GDEM数据的山西地形起伏度分析研究[J].山西农业大学学报:自然科学版,2016,36(6):417-421.
[14] 中国科学院地理研究所.中国1:1000000地貌图制图规范(试行)[M].北京:科学出版社,1987:33-34.
[15] 李炳元,潘保田,韩嘉福.中国陆地基本地貌类型及其划分指标探讨[J].第四纪研究,2008,28(4):535-543.

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