Articles | Volume 1, issue 1
SOIL, 1, 217–233, 2015
https://doi.org/10.5194/soil-1-217-2015
SOIL, 1, 217–233, 2015
https://doi.org/10.5194/soil-1-217-2015
Original research article
04 Mar 2015
Original research article | 04 Mar 2015

Comparison of spatial association approaches for landscape mapping of soil organic carbon stocks

B. A. Miller et al.

Related authors

Pan-Arctic soil element availability estimations
Peter Stimmler, Mathias Goeckede, Bo Elberling, Susan Natali, Peter Kuhry, Nia Perron, Fabrice Lacroix, Gustaf Hugelius, Oliver Sonnentag, Jens Strauss, Christina Minions, Michael Sommer, and Jörg Schaller
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-123,https://doi.org/10.5194/essd-2022-123, 2022
Preprint under review for ESSD
Short summary
Spatial patterns of aboveground phytogenic Si stocks in a grass-dominated catchment – results from UAS-based high-resolution remote sensing
Marc Wehrhan, Daniel Puppe, Danuta Kaczorek, and Michael Sommer
Biogeosciences, 18, 5163–5183, https://doi.org/10.5194/bg-18-5163-2021,https://doi.org/10.5194/bg-18-5163-2021, 2021
Short summary
Silicon uptake and isotope fractionation dynamics by crop species
Daniel A. Frick, Rainer Remus, Michael Sommer, Jürgen Augustin, Danuta Kaczorek, and Friedhelm von Blanckenburg
Biogeosciences, 17, 6475–6490, https://doi.org/10.5194/bg-17-6475-2020,https://doi.org/10.5194/bg-17-6475-2020, 2020
Short summary
Understanding the role of water and tillage erosion from 239+240Pu tracer measurements using inverse modelling
Florian Wilken, Michael Ketterer, Sylvia Koszinski, Michael Sommer, and Peter Fiener
SOIL, 6, 549–564, https://doi.org/10.5194/soil-6-549-2020,https://doi.org/10.5194/soil-6-549-2020, 2020
Short summary
Modeling soil and landscape evolution – the effect of rainfall and land-use change on soil and landscape patterns
W. Marijn van der Meij, Arnaud J. A. M. Temme, Jakob Wallinga, and Michael Sommer
SOIL, 6, 337–358, https://doi.org/10.5194/soil-6-337-2020,https://doi.org/10.5194/soil-6-337-2020, 2020
Short summary

Related subject area

Soil and methods
Estimating soil fungal abundance and diversity at a macroecological scale with deep learning spectrotransfer functions
Yuanyuan Yang, Zefang Shen, Andrew Bissett, and Raphael A. Viscarra Rossel
SOIL, 8, 223–235, https://doi.org/10.5194/soil-8-223-2022,https://doi.org/10.5194/soil-8-223-2022, 2022
Short summary
Thermal signature and quantification of charcoal in soil by differential scanning calorimetry and BPCA markers
Brieuc Hardy, Nils Borchard, and Jens Leifeld
SOIL Discuss., https://doi.org/10.5194/soil-2021-146,https://doi.org/10.5194/soil-2021-146, 2022
Revised manuscript accepted for SOIL
Short summary
An underground, wireless, open-source, low-cost system for monitoring oxygen, temperature, and soil moisture
Elad Levintal, Yonatan Ganot, Gail Taylor, Peter Freer-Smith, Kosana Suvocarev, and Helen E. Dahlke
SOIL, 8, 85–97, https://doi.org/10.5194/soil-8-85-2022,https://doi.org/10.5194/soil-8-85-2022, 2022
Short summary
Performance of three machine learning algorithms for predicting soil organic carbon in German agricultural soil
Ali Sakhaee, Anika Gebauer, Mareike Ließ, and Axel Don
SOIL Discuss., https://doi.org/10.5194/soil-2021-107,https://doi.org/10.5194/soil-2021-107, 2021
Revised manuscript under review for SOIL
Short summary
Estimation of soil properties with mid-infrared soil spectroscopy across yam production landscapes in West Africa
Philipp Baumann, Juhwan Lee, Emmanuel Frossard, Laurie Paule Schönholzer, Lucien Diby, Valérie Kouamé Hgaza, Delwende Innocent Kiba, Andrew Sila, Keith Sheperd, and Johan Six
SOIL, 7, 717–731, https://doi.org/10.5194/soil-7-717-2021,https://doi.org/10.5194/soil-7-717-2021, 2021
Short summary

Cited articles

Adhikari, K., Kheir, R. B., Greve, M. B., and Greve, M. H.: Comparing kriging and regression approaches for mapping soil clay content in a diverse Danish landscape, Soil Sci., 178, 505–517, https://doi.org/10.1097/SS.0000000000000013, 2013.
Almond, P. C. and Tonkin, P. J.: Pedogenesis by upbuilding in an extreme leaching and weathering environment, and slow loess accretion, south Westland, New Zealand, Geoderma, 92, 1–36, https://doi.org/10.1016/S0016-7061(99)00016-6, 1999.
Angers, D. A. and Carter, M. R.: Aggregation and organic matter storage in cool, humid agricultural soils, in: Structure and Organic Matter Storage in Agricultural Soils, edited by: Carter, M. R. and Stewart, B. A., CRC Press, Boca Raton, 193–211, 1996.
Ashley, M. D. and Rea, J.: Seasonal vegetation differences from ERTS imagery, Journal of American Society of Photogrammetry, 41, 713–719, 1975.
Bannari, A., Morin, D., Bonn, F., and Huete, A. R.: A review of vegetation indices, Remote Sensing Reviews, 13, 95–120, https://doi.org/10.1080/02757259509532298, 1995.
Download
Short summary
There are many different strategies for mapping SOC, among which is to model the variables needed to calculate the SOC stock indirectly or to model the SOC stock directly. The purpose of this research was to compare these two approaches for mapping SOC stocks from multiple linear regression models applied at the landscape scale via spatial association. Although the indirect approach had greater spatial variation and higher R2 values, the direct approach had a lower total estimated error.