当前位置: X-MOL 学术Geoderma Reg. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Soil sampling strategy in areas of difficult acess using the cLHS method
Geoderma Regional ( IF 3.1 ) Pub Date : 2020-12-17 , DOI: 10.1016/j.geodrs.2020.e00354
Nathalie Cruz Sena , Gustavo Vieira Veloso , Alisson Oliveira Lopes , Marcio Rocha Francelino , Elpídio Inácio Fernandes-Filho , Eduardo Osório Senra , Luiz Aníbal da Silva Filho , Viviane Flaviana Condé , David Lukas de Arruda Silva , Raphael Wakin de Araújo

The cLHS is considered as a robust sampling strategy for the selection of representative samples of the landscape, which uses environmental variables and their multivariate distributions. In this study, we propose a method based on cLHS for selecting soil sampling points in areas of difficult access, with the objective of minimizing inaccessibility problems in field campaigns, considering obtaining alternative samples with a lower cost and time demand. The study aims to analyze, above all, the practical operational performance of the method based on the potential and restrictions for application in digital soil mapping. For this, five predictive models (GBM, RF, SVM, kNN and C5.0) were initially used to select the most important variables to be inserted in the cLHS. The k-means method was applied to select the alternative points closest to the original points of the cLHS. Restrictions such as the euclidean distance from roads and the exclusion of urban and mining areas were incorporated. Approximately 30% of the original sample points of the cLHS could not be accessed in the field, the main operational restriction was due to the lack of access/routes to the selected points. However, the use of alternative sampling points allowed greater flexibility and accessibility in the field, where it was possible to collect 17% of the points and reduce the demand for time and cost. With this, the sampling strategy adopted made it possible to obtain an ideal minimum size of sampling points to be used in predictive models in digital soil mapping studies.



中文翻译:

使用cLHS方法在困难地区进行土壤采样策略

cLHS被认为是用于选择景观代表性样本的可靠采样策略,该样本使用环境变量及其多元分布。在这项研究中,我们提出了一种基于cLHS的方法,用于在难以进入的地区选择土壤采样点,目的是最大程度地减少野战中的难以进入的问题,同时考虑以较低的成本和时间需求获得替代样品。该研究旨在首先基于在数字土壤制图中的应用潜力和局限性来分析该方法的实际操作性能。为此,最初使用五个预测模型(GBM,RF,SVM,kNN和C5.0)来选择要插入cLHS的最重要变量。应用k均值方法选择最接近cLHS原始点的替代点。纳入了限制条件,例如距道路的欧几里得距离以及排除城市和采矿区。大约30%的cLHS原始采样点无法在现场访问,主要的操作限制是由于缺少到所选点的访问/路线。但是,使用替代采样点可以在现场实现更大的灵活性和可访问性,在该位置可以收集17%的采样点,从而减少了对时间和成本的需求。这样,采用的采样策略便有可能获得理想的最小采样点大小,以便在数字土壤制图研究的预测模型中使用。纳入了限制条件,例如距道路的欧几里得距离以及排除城市和采矿区。大约30%的cLHS原始采样点无法在现场访问,主要的操作限制是由于缺少到所选点的访问/路线。但是,使用替代采样点可以在现场实现更大的灵活性和可访问性,在该位置可以收集17%的采样点,从而减少了对时间和成本的需求。这样,采用的采样策略便有可能获得理想的最小采样点大小,以便在数字土壤制图研究的预测模型中使用。纳入了限制条件,例如距道路的欧几里得距离以及排除城市和采矿区。大约30%的cLHS原始采样点无法在现场访问,主要的操作限制是由于缺少到所选点的访问/路线。但是,使用替代采样点可以在现场实现更大的灵活性和可访问性,在该位置可以收集17%的采样点,从而减少了对时间和成本的需求。这样,采用的采样策略便有可能获得理想的最小采样点大小,以便在数字土壤制图研究的预测模型中使用。主要的操作限制是由于缺乏通往选定地点的通道/路线。但是,使用替代采样点可以在现场实现更大的灵活性和可访问性,在该位置可以收集17%的采样点,从而减少了对时间和成本的需求。这样,采用的采样策略便有可能获得理想的最小采样点大小,以便在数字土壤制图研究的预测模型中使用。主要的操作限制是由于缺乏通往选定地点的通道/路线。但是,使用替代采样点可以在现场实现更大的灵活性和可访问性,在该位置可以收集17%的采样点,从而减少了对时间和成本的需求。这样,采用的采样策略便有可能获得理想的最小采样点大小,以便在数字土壤制图研究的预测模型中使用。

更新日期:2021-01-06
down
wechat
bug