干旱区生态环境知识资源中心(Arid): Comparing three approaches of spatial disaggregation of legacy soil maps based on the Disaggregation and Harmonisation of Soil Map Units Through Resampled Classification Trees (DSMART) algorithm

Arid

DOI	10.5194/soil-6-371-2020
	Comparing three approaches of spatial disaggregation of legacy soil maps based on the Disaggregation and Harmonisation of Soil Map Units Through Resampled Classification Trees (DSMART) algorithm
	Ellili-Bargaoui, Yosra; Malone, Brendan Philip; Michot, Didier; Minasny, Budiman; Vincent, Sebastien; Walter, Christian; Lemercier, Blandine
通讯作者	Ellili-Bargaoui, Y
来源期刊	SOIL
ISSN	2199-3971
EISSN	2199-398X
出版年	2020
卷号	6 期号:2 页码:371-388
英文摘要	Enhancing the spatial resolution of pedological information is a great challenge in the field of digital soil mapping (DSM). Several techniques have emerged to disaggregate conventional soil maps initially and are available at a coarser spatial resolution than required for solving environmental and agricultural issues. At the regional level, polygon maps represent soil cover as a tessellation of polygons defining soil map units (SMUs), where each SMU can include one or several soil type units (STUs) with given proportions derived from expert knowledge. Such polygon maps can be disaggregated at a finer spatial resolution by machine-learning algorithms, using the Disaggregation and Harmonisation of Soil Map Units Through Resampled Classification Trees (DSMART) algorithm. This study aimed to compare three approaches of the spatial disaggregation of legacy soil maps based on DSMART decision trees to test the hypothesis that the disaggregation of soil landscape distribution rules may improve the accuracy of the resulting soil maps. Overall, two modified DSMART algorithms (DSMART with extra soil profiles; DSMART with soil landscape relationships) and the original DSMART algorithm were tested. The quality of disaggregated soil maps at a 50 m resolution was assessed over a large study area (6775 km(2)) using an external validation based on 135 independent soil profiles selected by probability sampling, 755 legacy soil profiles and existing detailed 1 : 25 000 soil maps. Pairwise comparisons were also performed, using the Shannon entropy measure, to spatially locate the differences between disaggregated maps. The main results show that adding soil landscape relationships to the disaggregation process enhances the performance of the prediction of soil type distribution. Considering the three most probable STUs and using 135 independent soil profiles, the overall accuracy measures (the percentage of soil profiles where predictions meet observations) are 19.8 % for DSMART with expert rules against 18.1 % for the original DSMART and 16.9 % for DSMART with extra soil profiles. These measures were almost 2 times higher when validated using 3 x 3 windows. They achieved 28.5 % for DSMART with soil landscape relationships and 25.3 % and 21 % for original DSMART and DSMART with extra soil observations, respectively. In general, adding soil landscape relationships and extra soil observations constraints allow the model to predict a specific STU that can occur in specific environmental conditions. Thus, including global soil landscape expert rules in the DSMART algorithm is crucial for obtaining consistent soil maps with a clear internal disaggregation of SMUs across the landscape.
类型	Article
语种	英语
开放获取类型	DOAJ Gold
收录类别	SCI-E
WOS记录号	WOS:000562951800001
WOS关键词	SEMIAUTOMATED DISAGGREGATION ; REGIONAL-SCALE ; KNOWLEDGE ; LANDSCAPE ; PREDICTION ; DESERT
WOS类目	Soil Science
WOS研究方向	Agriculture
来源机构	Commonwealth Scientific and Industrial Research Organisation
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/325839
作者单位	[Ellili-Bargaoui, Yosra; Michot, Didier; Vincent, Sebastien; Walter, Christian; Lemercier, Blandine] Inst Agro, UMR SAS, INRAE, Rennes, France; [Ellili-Bargaoui, Yosra] UniLaSalle, INTERACT, Beauvais, France; [Malone, Brendan Philip] CSIRO, Agr & Food, Canberra, ACT, Australia; [Minasny, Budiman] Univ Sydney, Sch Life & Environm Sci, Sydney Inst Agr, Sydney, NSW, Australia
推荐引用方式 GB/T 7714	Ellili-Bargaoui, Yosra,Malone, Brendan Philip,Michot, Didier,et al. Comparing three approaches of spatial disaggregation of legacy soil maps based on the Disaggregation and Harmonisation of Soil Map Units Through Resampled Classification Trees (DSMART) algorithm[J]. Commonwealth Scientific and Industrial Research Organisation,2020,6(2):371-388.
APA	Ellili-Bargaoui, Yosra.,Malone, Brendan Philip.,Michot, Didier.,Minasny, Budiman.,Vincent, Sebastien.,...&Lemercier, Blandine.(2020).Comparing three approaches of spatial disaggregation of legacy soil maps based on the Disaggregation and Harmonisation of Soil Map Units Through Resampled Classification Trees (DSMART) algorithm.SOIL,6(2),371-388.
MLA	Ellili-Bargaoui, Yosra,et al."Comparing three approaches of spatial disaggregation of legacy soil maps based on the Disaggregation and Harmonisation of Soil Map Units Through Resampled Classification Trees (DSMART) algorithm".SOIL 6.2(2020):371-388.