Changes in variance and correlation of soil properties with scale and location: analysis using an adapted maximal overlap discrete wavelet transform
By R. M. Lark, Richard Webster. 2001
92 citations recorded by the source corpus.
Subfields: Applied Mathematics, Artificial Intelligence, Environmental Engineering
View Paper: https://www.semanticscholar.org/paper/f1afe644db0db499bc2844536f38b2b32847e581
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Applied Mathematics
In Artificial Intelligence
- Thomas Scholten
- Thorsten Behrens
- K. Schmidt
- A-Xing Zhu
- Marie-Josée Fortin
- R. M. Lark
- Stephanie J. Melles
- B. P. Marchant
In Environmental Engineering
- A-Xing Zhu
- Thomas Scholten
- Thorsten Behrens
- K. Schmidt
- Marie-Josée Fortin
- R. M. Lark
- Michael L. Stein
- Budiman Minasny
Citations in the corpus
- Spatial statistics, spatial regression, and graph theory in ecology (2012, methodology): “Wavelet analysis has also been used extensively to determine the spatial patterns and scales of soil properties in one and two dimensions (e.g., Lark and Webster, 2001; Hassler et al., 2011).”
- Kriging a soil variable with a simple nonstationary variance model (2009, methodology): “For example, Lark and Webster (2001) used a wavelet transform to detect change in the variance of soil properties on a transect across contrasting strata in central England, and showed that the changes provided evidence against an assumption of intrinsic stationarity.”
- Multi-scale digital terrain analysis and feature selection for digital soil mapping (2010, methodology): “Concerning the influence of scale on the spatial distribution of soils, most authors focus on soil properties (Burrough, 1983; Goovaerts and Webster, 1994; German, 1999; Lark and Webster, 2001; Nemes et al., 2003; Lark, 2005; Zhu et al., 2004; Bartoli et al., 1991, 2005; Zhao et al., 2006).”