Research on Precise Management Zoning at Field Scale in Typical Black Soil Water Erosion Areas

doi:10.15933/j.cnki.1004-3268.2025.05.017

Abstract

Abstract: In order to achieve precise management zoning of black soil water erosion areas，the field blocks of Heshan Farm in Heihe City，Heilongjiang Province（typical black soil water erosion areas）were taken as the research object. Precise management zoning was carried out based on their water erosion degree.Sentinel‐2 bare soil images and digital elevation model（DEM）data from different periods were combined，and object‐oriented segmentation methods were used to accurately manage the field blocks.Then，normalized vegetation index（NDVI）was extracted from multi‐year crop growth period images to evaluate the zoning results under different input quantities.Soil characteristics with different degrees of water erosion were explored based on optimal partitioning results，and the impact of different degrees of water erosion on cultivated land was clarified.The results showed that the more severe the water erosion inside the field，the higher the spectral reflectance，and the spectral reflectance of severe water erosion was significantly higher than that of mild water erosion；The optimal input for precise management zoning of soil water erosion was May remote sensing images and DEM data（with a ratio of interval coefficient of variation to intra area coefficient of variation of 2.11），and the addition of April and October remote sensing images reduced accuracy during zoning；Based on precise management zoning results and soil structure stability index（St），it was found that the higher the degree of water erosion，the lower the content of soil organic matter and available nitrogen.The above shows that choosing the appropriate input volume is the key to improve the accuracy of field‐scale precision management zoning of soil water erosion in the black soil area.

Key words: Black soil water erosion region, Remote sensing, Precision management zoning, Object‐oriented segmentation

摘要： 为实现黑土水蚀区精准管理分区，以黑龙江省黑河市鹤山农场的田块（典型黑土水蚀区田块）为研究对象，根据其水蚀程度进行精准管理分区，分别使用不同期Sentinel-2裸土影像与数字高程模型（DEM）数据进行组合，采用面向对象分割方法对田块进行精准管理分区，然后利用多年作物生长期影像提取归一化植被指数（NDVI），对不同输入量下的分区结果进行评价；基于最优分区结果探究不同水蚀程度土壤特征，明确土壤不同水蚀程度对耕地的影响。结果表明，田块内部水蚀程度越严重，光谱反射率越高，重度水蚀光谱反射率明显高于轻度水蚀光谱反射率；面向土壤水蚀的精准管理分区效果最优输入量为5月遥感影像与DEM数据（区间变异系数与区内变异系数的比值为2.11），分区时加入4月、10月遥感影像精度降低；基于精准管理分区结果，依据土壤结构稳定性指数（St）确定水蚀程度发现，水蚀程度越高，土壤有机质与速效氮含量越低。以上表明，选择合适的输入量是提高黑土区土壤水蚀田块尺度精准管理分区精度的关键。

关键词: 黑土水蚀区, 遥感, 精准管理分区, 面向对象分割

CLC Number:

S127

MA Yuxin, LI Chenxi, MA Shinai, WANG Yiang, LIU Huanjun, BAO Shuai. Research on Precise Management Zoning at Field Scale in Typical Black Soil Water Erosion Areas[J]. Journal of Henan Agricultural Sciences, 2025, 54(5): 149-158.

马雨欣, 李晨曦, 马士耐, 王轶昂, 刘焕军, 暴帅. 典型黑土水蚀区田块尺度精准管理分区研究[J]. 河南农业科学, 2025, 54(5): 149-158.

Figures/Tables 10

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