基于环境变量辅助的不同地形单元土壤类型数字制图研究
作者:
作者单位:

作者简介:

通讯作者:

中图分类号:

基金项目:

第三次新疆综合科学考察项目(2022xjkk1100)、北京市第三次土壤普查土壤类型名称与边界校正项目(1191/69193030)和中国科学院青年创新促进会会员项目(2021119)


Digital Mapping of Soil Types in Different Topographical UnitsAssisted by Environmental Variables
Author:
Affiliation:

Fund Project:

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    摘要:

    土壤类型图反映了不同土壤类型的地理分布及其特征,为土壤资源利用、保护和管理提供了科学基础。基于土壤-环境关系的数字土壤制图方法是快速获取高精度、高分辨率土壤空间分布信息的重要手段,但针对不同地形单元的适用性及制度精度仍需进一步探讨。本文以北京市平谷区为研究区,将其划分为山地丘陵区和平原区2个地形单元,基于土壤调查点和随机森林算法,构建土壤-环境变量关系模型,进行不同地形单元的土壤类型数字制图。结果表明,山地丘陵区土类、亚类、土属和土种数字制图总体精度(Overall accuracy,OA)分别为100%、93.1%、89.7%和75.9%;而平原区土类、亚类、土属和土种数字制图OA分别为73.7%、55.3%、52.6%和23.7%。这表明在山地丘陵区,环境变量辅助的土壤类型数字制图具有较好的精度,而在平原区,这种精度会显著降低。随着土壤类型分类单元从土类到土种的精细化,环境变量辅助的土壤类型制图精度也逐渐下降。建议在资源有限的情况下,对于山地丘陵区,可以充分利用易获取的环境变量数据来提升土壤类型制图精度;而对于平原区,则需适当增加土壤类型剖面数量以提高制图精度。研究结果为其他地区土壤类型数字化制图提供了实践案例和技术支持。

    Abstract:

    Soil type mapping reveals the geographical distribution and characteristics of soils and provides a scientific basis for the use, protection and management of soil resources. The digital soil mapping method based on the soil-environment relationship is an important means for quickly acquiring high-precision and high-resolution soil spatial distribution information. However, its applicability and mapping accuracy for different topographical units require further investigation. Taking Pinggu District of Beijing, China as the research area, and dividing it into two terrain units: mountainous and hilly regions and plain regions. The random forest algorithm was used to establish a model linking soil types to environmental variables, upon which digital mapping of soil types was conducted for both terrain units, with mapping accuracy being compared subsequently. The results showed that the overall accuracy (OA) of digital mapping for soil group, subgroup, soil genus and soil species in mountainous and hilly regions was 100%, 93.1%, 89.7% and 75.9%, respectively, whereas the OA of soil group, subgroup, soil genus and soil species in plain regions was 73.7%, 55.3%, 52.6% and 23.7%, respectively. These results indicated that digital mapping of soil types using environmental variables performed well in mountainous and hilly regions, but its efficacy noticeably diminished in plain regions. As the classification units of soil types became more granular, transitioning from soil groups to soil species, the accuracy of soil type mapping supported by environmental variables was gradually decreased. It was recommended to make full use of readily available environmental variable data to enhance the accuracy of soil type mapping in mountainous and hilly regions. In plain regions, it was necessary to appropriately increase the number of soil type profiles to improve mapping accuracy. The research result can provide practical examples and technical support for digital soil type mapping in other regions.

    参考文献
    相似文献
    引证文献
引用本文

叶回春,聂超甲,张越,周艳兵,王红叶,黄元仿.基于环境变量辅助的不同地形单元土壤类型数字制图研究[J].农业机械学报,2024,55(10):371-378. YE Huichun, NIE Chaojia, ZHANG Yue, ZHOU Yanbing, WANG Hongye, HUANG Yuanfang. Digital Mapping of Soil Types in Different Topographical UnitsAssisted by Environmental Variables[J]. Transactions of the Chinese Society for Agricultural Machinery,2024,55(10):371-378.

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2024-06-25
  • 最后修改日期:
  • 录用日期:
  • 在线发布日期: 2024-10-10
  • 出版日期:
文章二维码