2018
DOI: 10.1016/j.geoderma.2017.10.060
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Bulk-density modelling using optimal power-transformation of measured physical and chemical soil parameters

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Cited by 12 publications
(7 citation statements)
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“…However, this study has shown that urban vegetated areas can be sealed, reducing their potential for providing ecosystem services to cities. Our results presented higher values of density than those observed in other studies [65][66][67][68][69]. Nevertheless, there are few studies of bulk density in urban areas, since forest or rural soils used for agriculture and pasture are more explored [70][71][72][73][74].…”
Section: Discussioncontrasting
confidence: 71%
“…However, this study has shown that urban vegetated areas can be sealed, reducing their potential for providing ecosystem services to cities. Our results presented higher values of density than those observed in other studies [65][66][67][68][69]. Nevertheless, there are few studies of bulk density in urban areas, since forest or rural soils used for agriculture and pasture are more explored [70][71][72][73][74].…”
Section: Discussioncontrasting
confidence: 71%
“…As such, it is commonly considered as a suitable trait for efficient measurement of soil carbon and nutrient stocks (Bondi et al, 2018). There is only little knowledge about bulk density, since the measurement of this parameter is demanding, as it is pointed out in the work by Premrov et al (2017).…”
Section: Resultsmentioning
confidence: 99%
“…Bondi et al, (2018) estimated BD for peat soils using soil visual assessment, and decision trees achieving similar performances, with around 0.6 explained variance. Premrov et al, (2018) achieved similar performances (R 2 from 0.4 to 0.6) using optimal power-transformation of measured physical and chemical soil parameters. Chen et al (2018) formalized an analytical protocol to test the PTF prediction at regional scales in France by building a Boosted Regression Tree (BRT) model to obtain reliable predictions (R 2 0.7) , and also applied the advanced deep learning modelling framework for the evaluation of in situ spectral measurement of SOC with in situ vis-NIR spectroscopy in southeastern Tibet (Chen et al, 2020) achieving (R 2 = 0.92).…”
Section: Introductionmentioning
confidence: 82%