Interpreting and evaluating digital soil mapping prediction uncertainty: A case study using texture from SoilGrids

IF 5.6 1区 农林科学 Q1 SOIL SCIENCE Geoderma Pub Date : 2024-10-01 DOI:10.1016/j.geoderma.2024.117052
Linda Lilburne , Anatol Helfenstein , Gerard B.M. Heuvelink , Andre Eger
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Abstract

Soil information is critical for a wide range of land resource and environmental decisions. These decisions will be compromised when the soil information quality is unsatisfactory. Thus, users of soil information need to understand and consider the uncertainty of the available soil information and be able to judge whether it is fit for purpose. The uncertainty information provided with the SoilGrids 2.0 product was examined in a case study. We hypothesised that the soil property predictions for the Netherlands (NL) might be less uncertain than those of New Zealand (NZ) because there were more relevant training data for NL than for NZ. The study objectives were to: 1) understand whether the provided uncertainty information is correct for both countries; 2) explore spatial patterns and relationships in the prediction error and uncertainty information using quantitative tools and new graphical analyses; 3) analyse whether these patterns and relations can be explained; and 4) explore how the uncertainty information and insights derived from graphical analyses might assist an end user to determine whether a map is suitable for their purpose. The study focused on soil texture.
Independent datasets showed that the SoilGrids 2.0 uncertainty information was too optimistic for sand and too pessimistic for clay for both countries. The graphical analyses confirmed the initial assumption that NL predictions were more accurate than those for NZ, but they also indicated that some locations in NL have high uncertainty. The graphical analyses allowed only a limited identification of the four sources of uncertainty in digital soil maps, but were quite insightful in helping us to better understand the reliability of the information. A set of recommendations was developed for both producers and consumers of digital soil mapping (DSM) products. This includes the provision of a summary map of accuracy classes. We suggest that more research and educational effort is needed to ensure that digital soil maps are used appropriately.
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解读和评估数字土壤制图预测的不确定性:使用 SoilGrids 纹理的案例研究
土壤信息对各种土地资源和环境决策至关重要。如果土壤信息的质量不能令人满意,这些决策就会受到影响。因此,土壤信息的用户需要了解和考虑现有土壤信息的不确定性,并能够判断这些信息是否符合目的。SoilGrids 2.0 产品提供的不确定性信息在一项案例研究中得到了检验。我们假设荷兰(NL)土壤属性预测的不确定性可能小于新西兰(NZ),因为荷兰的相关训练数据多于新西兰。研究目标是1)了解为这两个国家提供的不确定性信息是否正确;2)使用定量工具和新的图形分析,探索预测误差和不确定性信息的空间模式和关系;3)分析这些模式和关系是否可以解释;4)探索不确定性信息和图形分析得出的见解如何帮助最终用户确定地图是否适合他们的目的。独立数据集显示,SoilGrids 2.0 的不确定性信息对两个国家的沙地过于乐观,而对粘土则过于悲观。图形分析证实了最初的假设,即北大西洋的预测比新西兰的预测更准确,但也表明北大西洋的某些地点具有较高的不确定性。图形分析只能有限地确定数字土壤地图的四个不确定性来源,但在帮助我们更好地了解信息的可靠性方面却很有见地。我们为数字土壤制图 (DSM) 产品的生产者和消费者提出了一系列建议。其中包括提供一份精度等级汇总图。我们建议需要开展更多的研究和教育工作,以确保数字土壤制图得到合理使用。
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来源期刊
Geoderma
Geoderma 农林科学-土壤科学
CiteScore
11.80
自引率
6.60%
发文量
597
审稿时长
58 days
期刊介绍: Geoderma - the global journal of soil science - welcomes authors, readers and soil research from all parts of the world, encourages worldwide soil studies, and embraces all aspects of soil science and its associated pedagogy. The journal particularly welcomes interdisciplinary work focusing on dynamic soil processes and functions across space and time.
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