On digital soil mapping

By Alex B. McBratney, M. L. M. Santos, Budiman Minasny. 2003

708 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Management, Monitoring, Policy and Law

View Paper: https://www.semanticscholar.org/paper/28490fba6c7c8e4061bb03d157cd271738da458c

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In Ecology

In Environmental Engineering

In Management, Monitoring, Policy and Law

Citations in the corpus

Construction of membership functions for predictive soil mapping under fuzzy logic (2010, neutral): “…set theory has been widely used in soil science for soil classification and mapping, land evaluation, fuzzy soil geostatistics, soil quality indices (Chang and Burrough, 1987; Burrough, 1989; Zhu et al., 1996; McBratney and Odeh, 1997; McBratney et al., 2003; Zhang et al., 2004; Lagacherie, 2005).”
A compilation of UAV applications for precision agriculture (2020, neutral): “Understanding the soil variability is one of the oldest challenges faced by farmers and researchers [43–47] .”
Using model averaging to combine soil property rasters from legacy soil maps and from point data (2014, positive): “E corresponds to one type of topographical characteristic of the scorpan digital soil mapping model (McBratney et al., 2003); while UKr is a quantitative proxy for parent materials, and the weathering processes they have undergone (Wilford, 2012).”
Multi-criteria characterization of recent digital soil mapping and modeling approaches (2009, methodology): “A comprehensive review of DSMa was provided in McBratney et al. (2003) and an overview of pedometric techniques used in DSMa by McBratney et al. (2000) and Grunwald (2006).”
Machine learning for digital soil mapping: Applications, challenges and suggested solutions (2020, methodology): “The digital soil mapping (DSM) framework was formalized by the publication of McBratney et al. (2003) which builds on Jenny’s S = clorpt model (Jenny, 1941) of soil formation, where S is the soil and the acronym clorpt stands for climate, organisms, relief, parent material and time, respectively.”
Mapping organic carbon stocks in eucalyptus plantations of the central highlands of Madagascar: A multiple regression approach (2011, methodology): “However, recent advances in statistics applied to ecology associated with increasing computer performance (McBratney et al., 2003) allow a better use of the numerous available spatial datasets to provide accurate estimates in natural ecosystem, even with few data.”
Incorporating taxonomic distance into spatial prediction and digital mapping of soil classes (2007, neutral): “The model for mapping soil classes can be written as follows ( McBratney et al., 2003 ):”