Slope Gradient Conversion Model Based on Different DEM Resolutions in Rolling Hilly Region of the Chinese Mollisol Region
Author:
Affiliation:

1.College of Soil and Water Conservation Science and Engineering, Northwest A&2.F University;3.The Research Center of Soil and Water Conservation and Ecological Environment, Chinese Academy of Sciences and Ministry of Education

Clc Number:

S157.1

Fund Project:

Sub- project of National Key R&D Program of China (2022YFD1500102); The Sub-topics of Class A Strategic Priority Science and Technology Project of Chinese Academy of Sciences “Composite erosion process and key technology of resistance control driven by wind-water-freeze-thaw in typical black soil area” (XDA28010201).

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    Abstract:

    [Objective] Accurately obtaining slope gradient data of the rolling hilly region in the Chinese Mollisol area is crucial for the quantitative evaluation of soil erosion. [Methods] This study aimed to address the issue of slope gradient reduction when extracting farmland slope gradient in the rolling hilly region in the Chinese Mollisol area using the currently available 30 m resolution Digital Elevation Model (DEM). To achieve this, a 5 cm resolution DEM was generated based on drone survey images and resampled to obtain 1 m, 5 m, and 12.5 m DEM-resolutions. Combined with the free downloaded 30 m resolution DEM, five groups of different DEM-resolutions were obtained. A comparative study was conducted to analyze the difference between the slope gradient information extracted by different DEM-resolutions and 5 cm resolution DEM to determine the best resolution of DEM for extracting slope gradient in the study area. Based on the histogram matching algorithm, a slope gradient conversion model between 30 m and the best resolution DEM was fitted for each slope gradient segment. [Results] (1) The slope gradient information extracted by the five groups of DEM resolutions showed that the frequency distribution of slopes gradient extracted by 1 m and 5 m DEMs have strong similarity with those extracted by 5 cm resolution DEM. Considering that the resolution of 5 m DEM corresponds to that of a 1:10000 scale topographic map, 5 m was determined as the best DEM resolution for building the slope gradient conversion model. (2) Based on the histogram matching method, a univariate linear model and a univariate quadratic non-linear model of slope gradient conversion between 30 m and 5 m resolution DEMs were constructed for each slope gradient segment. It was appropriate to select the linear slope gradient conversion model when the ground slope gradient was less than 7°, while it was appropriate to select the non-linear slope gradient conversion model when the ground slope gradient was greater than 7°. (3) After optimization by linear and non-linear slope gradient conversion models, the frequency distribution of slope gradients was basically similar to that of 5 m resolution, and the covariance and correlation coefficient were greatly improved. This indicated that the slope gradient information extracted by 30 m resolution DEM could truly reflect the ground undulation features after model conversion, and the optimization effect of the non-linear slope gradient conversion model was better. [Conclusion] The constructed low-high resolution slope gradient conversion model provides method support for obtaining the real slope gradient of the ground in the study area.

    Reference
    [1] 中国科学院.东北黑土地白皮书(2020) [EB/OL]. https://www.cas.cn/ yw/202107/t20210709_4797892.shtml, 2021-07-09/2022-09-24.
    [2] Lu Shaojuan, Liu Baoyuan, Hu Yaxian, et al. Soil erosion topographic factor (LS): Accuracy calculated from different data sources[J]. CATENA, 2020, 187: 104334.
    [3] 杨维鸽, 郑粉莉, 王占礼, 等. 地形对黑土区典型坡面侵蚀—沉积空间分布特征的影响[J]. 土壤学报, 2016, 53(03): 572-581.
    [4] An Juan, Zheng Fenli, Wang Bin. Using 137Cs technique to investigate the spatial distribution of erosion and deposition regimes for a small catchment in the black soil region, Northeast China[J]. CATENA, 2014, 123: 243-251.
    [5] 张晓平, 梁爱珍, 申艳, 等. 东北黑土水土流失特点[J]. 地理科学, 2006, 26(6): 687-692.
    [6] 蔡清华, 杨勤科. SRTM与地形图生成DEM的地形表达能力对比[J]. 水土保持通报, 2009, 29(03): 183-187.
    [7] 土祥, 王春梅, 庞国伟, 等. 黄土丘陵沟壑区坡度尺度效应空间分异分析[J]. 山地学报, 2018, 36(06): 964-972.
    [8] Carlos H. Grohmann. Effects of spatial resolution on slope and aspect derivation for regional-scale analysis[J], Computers & Geosciences, 2015, 77: 111-117,
    [9] 罗为东, 甘淑, 袁希平, 等. 基于UAV高分辨率DEM的复杂微地貌形态特征分析——以恐龙谷南缘山区为例[J]. 中国水土保持科学, 2022, 20(05): 109-117.
    [10] Arif Oguz Altunel, Chukwuma John Okolie & Adem Kurtipek. Capturing the level of progress in vertical accuracy achieved by ASTER GDEM since the beginning: Turkish and Nigerian examples[J]. Geocarto International. 2022, 37(26): 12073-12095
    [11] Munoth Pramitra., Goyal Rohit. Effects of DEM Source, Spatial Resolution and Drainage Area Threshold Values on Hydrological Modeling[J].?Water Resources Management. 2019.?33(9): 3303–3319.
    [12] 汤国安, 杨勤科, 张勇, 等. 不同比例尺DEM提取地面坡度的精度研究——以在黄土丘陵沟壑区的试验为例[J]. 水土保持通报, 2001, (01): 53-56.
    [13] 刘飞, 范建容, 崔兆岩等. 基于DEM分形特征的坡度尺度变换模型[J]. 山地学报, 2019. 37(01): 129-136.
    [14] Zhang Xiaoyang, Drake Nick A, Wainwright John, et al. Comparison of slope estimates from low resolution DEMs: scaling issues and a fractal method for their resolution[J]. Earth Surface Processes and Landforms, 1999, (24): 763-779.
    [15] Jou Fandi, Fan Kuochin, Chang Yanglang. Efficient matching of large-size histograms[J]. Pattern Recognition Letters, 2004, 25(3): 277-286.
    [16] Wang Chunmei, Shan Linxin, Liu Xin, et al. Impacts of horizontal resolution and downscaling on the USLE LS factor for different terrains[J]. International Soil and Water Conservation Research, 2020, 8(4): 363-372.
    [17] Toure Sory I, Stow Douglas A, Weeks John R, et al. Histogram Curve Matching Approaches for Object-based Image Classification of Land Cover and Land Use [J]. Photogrammetric Engineering & Remote Sensing, 2013, 79(5): 433-440.
    [18] 张荞, 张艳梅, 蒙印. 基于直方图匹配的多源遥感影像匀色研究[J]. 地理空间信息, 2020, 18(12): 54-57.
    [19] 卢华兴, 刘学军, 王永君, 等. 插值条件下格网DEM坡度计算模型的噪声误差分析[J]. 测绘学报, 2012, 41(06): 926-932.
    [20] 王琦, 杨勤科, 任宗萍. 中尺度流域NDVI尺度转换研究[J]. 水土保持通报, 2010, 30(03): 96-99.
    [21] 中华人民共和国水利部, 黑土区水土流失综合防治技术标准: SL444-2009[S]. 北京: 中国水利水电出版社, 2009: 5-6.
    [22] 师动, 朱奇峰, 杨勤科, 等. DEM分辨率对坡度算法选择影响的分析[J]. 山地学报, 2020, 38(06): 935-944.
    [23] 杨颖楠, 李子夫, 刘梦云等. 基于不同分辨率DEM的永寿县地形信息差异分析[J]. 水土保持研究, 2018, 25(06): 131-136.
    [24] 陈楠. DEM分辨率与平均坡度的关系分析[J]. 地球信息科学学报, 2014, 16(04):524-530.
    [25] Chen Xue, Chen Guokun, Feng Junxin, et al. Slope Scaling Effect and Slope-Conversion-Atlas for Typical Water Erosion Regions in China[J]. Sustainability, 2023, 15(4): 3789.
    [26] 张永红, 黄付强, 程华, 等. 两种分辨率DEM在不同空间尺度下的差异—以黄土高原丘陵区为例[J]. 西部林业科学, 2020, 49(04): 54-59+67.
    [27] 汤国安, 赵牡丹, 李天文, 等. DEM提取黄土高原地面坡度的不确定性[J]. 地理学报, 2003, (06): 824-830.
    [28] Wang Suyuan, Zhu Xiaoli, Zhang Wenbo, et al. Effect of different topographic data sources on soil loss estimation for a mountainous watershed in Northern China[J]. Environmental Earth Sciences, 2016, 75(20): 1382.
    [29] 胡云华, 贺秀斌, 毕景芝. 直方图匹配算法进行坡度变换的精度评价[J]. 水土保持研究, 2013, 20(06): 97-101.
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History
  • Received:June 01,2024
  • Revised:September 02,2024
  • Adopted:September 05,2024