基于数字土壤制图技术的土壤有机碳储量估算

doi:10.13287/j.1001-9332.202102.014

应用生态学报 ›› 2021, Vol. 32 ›› Issue (2): 591-600.doi: 10.13287/j.1001-9332.202102.014

基于数字土壤制图技术的土壤有机碳储量估算

何林倩¹, 刘倩², 王德彩^1*, 张志华¹, 徐畅¹, 施梦月¹

¹河南农业大学林学院, 郑州 450002;
²河南农业大学信息与管理科学学院, 郑州 450002

收稿日期:2020-08-25 接受日期:2020-11-25 出版日期:2021-02-15 发布日期:2021-08-15
通讯作者: ^*E-mail: lvluuo@126.com
作者简介:何林倩, 女, 1994年生, 硕士研究生。主要从事资源环境监测与评价研究。E-mail: hlinqian@163.com
基金资助:
国家自然科学基金项目(41201210)和河南省科技攻关计划项目(172102110056)资助

Estimation of soil organic carbon storage based on digital soil mapping technique

HE Lin-qian¹, LIU Qian², WANG De-cai^1*, ZHANG Zhi-hua¹, XU Chang¹, SHI Meng-yue¹

¹College of Forestry, Henan Agricultural University, Zhengzhou 450002, China;
²College of Information and Management Sciences, Henan Agricultural University, Zhengzhou 450002, China

Received:2020-08-25 Accepted:2020-11-25 Online:2021-02-15 Published:2021-08-15
Contact: ^*E-mail: lvluuo@126.com
Supported by:
Natural Science Foundation of China (41201210) and the Programs for Science and Technology Development of Henan (172102110056)

摘要/Abstract

摘要： 精准的土壤属性空间分布信息有助于提升土壤有机碳储量估算的精度。本研究以河南省济源市南山林场为研究区,以地形因子为预测因子,利用模糊C均值(FCM)聚类方法对土壤有机碳含量、土壤容重、土壤厚度和土壤砾石含量进行数字土壤预测制图,基于数字制图结果实现土壤有机碳密度预测制图和土壤有机碳储量估算。结果表明: 基于数字土壤制图方法得到的研究区土壤有机碳密度平均值为4.24 kg·m^-2,其预测图的平均误差(ME)为0.08 kg·m^-2,平均绝对误差(MAE)为2.80 kg·m^-2,均方根误差(RMSE)为5.03 kg·m^-2,与传统类型方法相比,预测结果的精度和稳定性更高,具有较高的可信度,最终估算得到研究区土壤有机碳储量为3.08×10⁸ kg。基于数字土壤制图技术仅采用少量土壤样点即可实现较高精度的土壤有机碳密度制图和储量估算,且能表征土壤有机碳密度空间分布特征。本研究为土壤有机碳储量估算提供了新途径,有助于提升土壤有机碳储量估算的精度和效率。

关键词: 有机碳密度, 碳储量, 数字土壤制图, 模糊C均值聚类

Abstract: Accurate spatial distribution information of soil properties would be helpful for improving the accuracy of soil organic carbon storage estimation. In this study, terrain factors were used as predictors, and the fuzzy C-means (FCM) clustering method was used to make digital soil prediction mapping for soil organic carbon content, soil bulk density, soil depth, and soil gravel content in Nanshan forest farm in Jiyuan City of Henan Province. Based on the digital mapping results, the prediction mapping of soil organic carbon density and the estimation of soil organic carbon storage were realized. The results showed that the average soil organic carbon density in the study area based on the digital soil mapping method was 4.24 kg·m^-2, the mean error (ME), mean absolute error (MAE) and root mean square error (RMSE) of the prediction map were 0.08, 2.80 and 5.03 kg·m^-2, respectively. The accuracy, stability and reliability of the prediction results were higher than the tradiation methods. The soil organic carbon storage in the study area was estimated to be 3.08×10⁸ kg. Based on the digital soil mapping technology, only a small number of soil samples could be used to map and estimate the soil organic carbon density with high accuracy, which could characterize the spatial distribution characteristics of soil organic carbon density. This study provided a new way to estimate soil organic carbon storage, which would help to improve the accuracy and efficiency of soil organic carbon storage estimation.

Key words: organic carbon density, carbon storage, digital soil mapping, fuzzy C-means clustering

何林倩, 刘倩, 王德彩, 张志华, 徐畅, 施梦月. 基于数字土壤制图技术的土壤有机碳储量估算[J]. 应用生态学报, 2021, 32(2): 591-600.

HE Lin-qian, LIU Qian, WANG De-cai, ZHANG Zhi-hua, XU Chang, SHI Meng-yue. Estimation of soil organic carbon storage based on digital soil mapping technique[J]. Chinese Journal of Applied Ecology, 2021, 32(2): 591-600.

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基于数字土壤制图技术的土壤有机碳储量估算

Estimation of soil organic carbon storage based on digital soil mapping technique

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