Modelling soil carbon stocks using legacy site data, in the Mid North region of South Australia

C. Liddicoat; D. Maschmedt; D. B. Kidd; R. Searle

doi:10.1201/b16500

Modelling soil carbon stocks using legacy site data, in the Mid North region of South Australia

C. Liddicoat, D. Maschmedt, D. B. Kidd, R. Searle

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Citations (Scopus)

Abstract

Preliminary spatial predictive modelling of 0-30 cm Soil Organic Carbon (SOC) stocks has been undertaken using legacy site data, across a 1 million hectare study area (>10 million cells) in the Mid North region of South Australia. SOC stock estimation required the development of a bulk density pedotransfer function, incorporation of key soil parameters (available at the horizon level), and application of depth-smoothing splines to evaluate stocks over a consistent depth range. Data analysis and spatial modelling has been performed within the R software environment, including use of the raster package to apply predictive models block by block (in order to overcome inherent memory limitations). A preliminary combined linear and regression tree model has performed well at training sites but lacks predictive ability at independently collected validation sites. Key limitations in the legacy site data have been identified which will guide future potential improvements in mapping of SOC stocks.

Original language	English
Title of host publication	GlobalSoilMap
Subtitle of host publication	Basis of the Global Spatial Soil Information System
Editors	Dominique Arrouays, Neil McKenzie, John Hempel, Anne C. Richer de Forges, Alex McBratney
Place of Publication	Boca Raton, FL
Publisher	CRC Press
Pages	253-259
Number of pages	7
ISBN (Electronic)	9781315775586, 9780429227417
ISBN (Print)	9781138001190
DOIs	https://doi.org/10.1201/b16500
Publication status	Published - 2014
Externally published	Yes
Event	1st GlobalSoilMap Conference: Basis of the Global Spatial Soil Information System - Orleans, France Duration: 7 Oct 2013 → 9 Oct 2013

Conference

Conference	1st GlobalSoilMap Conference: Basis of the Global Spatial Soil Information System
Country/Territory	France
City	Orleans
Period	7/10/13 → 9/10/13

Keywords

GIS
Soil Science
Soil Sciences
Remote sensing and cartography
Geology - Earth scinences
Digital soil mapping

Access to Document

10.1201/b16500Licence: In Copyright

Cite this

Liddicoat, C., Maschmedt, D., Kidd, D. B., & Searle, R. (2014). Modelling soil carbon stocks using legacy site data, in the Mid North region of South Australia. In D. Arrouays, N. McKenzie, J. Hempel, A. C. Richer de Forges, & A. McBratney (Eds.), GlobalSoilMap: Basis of the Global Spatial Soil Information System (pp. 253-259). CRC Press. https://doi.org/10.1201/b16500

@inproceedings{1650649aff1440d885b0d0a66612c80a,

title = "Modelling soil carbon stocks using legacy site data, in the Mid North region of South Australia",

abstract = "Preliminary spatial predictive modelling of 0-30 cm Soil Organic Carbon (SOC) stocks has been undertaken using legacy site data, across a 1 million hectare study area (>10 million cells) in the Mid North region of South Australia. SOC stock estimation required the development of a bulk density pedotransfer function, incorporation of key soil parameters (available at the horizon level), and application of depth-smoothing splines to evaluate stocks over a consistent depth range. Data analysis and spatial modelling has been performed within the R software environment, including use of the raster package to apply predictive models block by block (in order to overcome inherent memory limitations). A preliminary combined linear and regression tree model has performed well at training sites but lacks predictive ability at independently collected validation sites. Key limitations in the legacy site data have been identified which will guide future potential improvements in mapping of SOC stocks.",

keywords = "GIS, Soil Science, Soil Sciences, Remote sensing and cartography, Geology - Earth scinences, Digital soil mapping",

author = "C. Liddicoat and D. Maschmedt and Kidd, {D. B.} and R. Searle",

year = "2014",

doi = "10.1201/b16500",

language = "English",

isbn = "9781138001190",

pages = "253--259",

editor = "Dominique Arrouays and Neil McKenzie and John Hempel and {Richer de Forges}, {Anne C.} and Alex McBratney",

booktitle = "GlobalSoilMap",

publisher = "CRC Press",

address = "United Kingdom",

note = "1st GlobalSoilMap Conference: Basis of the Global Spatial Soil Information System ; Conference date: 07-10-2013 Through 09-10-2013",

}

Liddicoat, C, Maschmedt, D, Kidd, DB & Searle, R 2014, Modelling soil carbon stocks using legacy site data, in the Mid North region of South Australia. in D Arrouays, N McKenzie, J Hempel, AC Richer de Forges & A McBratney (eds), GlobalSoilMap: Basis of the Global Spatial Soil Information System. CRC Press, Boca Raton, FL, pp. 253-259, 1st GlobalSoilMap Conference: Basis of the Global Spatial Soil Information System, Orleans, France, 7/10/13. https://doi.org/10.1201/b16500

Modelling soil carbon stocks using legacy site data, in the Mid North region of South Australia. / Liddicoat, C.; Maschmedt, D.; Kidd, D. B. et al.
GlobalSoilMap: Basis of the Global Spatial Soil Information System. ed. / Dominique Arrouays; Neil McKenzie; John Hempel; Anne C. Richer de Forges; Alex McBratney. Boca Raton, FL: CRC Press, 2014. p. 253-259.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Modelling soil carbon stocks using legacy site data, in the Mid North region of South Australia

AU - Liddicoat, C.

AU - Maschmedt, D.

AU - Kidd, D. B.

AU - Searle, R.

PY - 2014

Y1 - 2014

N2 - Preliminary spatial predictive modelling of 0-30 cm Soil Organic Carbon (SOC) stocks has been undertaken using legacy site data, across a 1 million hectare study area (>10 million cells) in the Mid North region of South Australia. SOC stock estimation required the development of a bulk density pedotransfer function, incorporation of key soil parameters (available at the horizon level), and application of depth-smoothing splines to evaluate stocks over a consistent depth range. Data analysis and spatial modelling has been performed within the R software environment, including use of the raster package to apply predictive models block by block (in order to overcome inherent memory limitations). A preliminary combined linear and regression tree model has performed well at training sites but lacks predictive ability at independently collected validation sites. Key limitations in the legacy site data have been identified which will guide future potential improvements in mapping of SOC stocks.

AB - Preliminary spatial predictive modelling of 0-30 cm Soil Organic Carbon (SOC) stocks has been undertaken using legacy site data, across a 1 million hectare study area (>10 million cells) in the Mid North region of South Australia. SOC stock estimation required the development of a bulk density pedotransfer function, incorporation of key soil parameters (available at the horizon level), and application of depth-smoothing splines to evaluate stocks over a consistent depth range. Data analysis and spatial modelling has been performed within the R software environment, including use of the raster package to apply predictive models block by block (in order to overcome inherent memory limitations). A preliminary combined linear and regression tree model has performed well at training sites but lacks predictive ability at independently collected validation sites. Key limitations in the legacy site data have been identified which will guide future potential improvements in mapping of SOC stocks.

KW - GIS

KW - Soil Science

KW - Soil Sciences

KW - Remote sensing and cartography

KW - Geology - Earth scinences

KW - Digital soil mapping

UR - http://www.scopus.com/inward/record.url?scp=84893661127&partnerID=8YFLogxK

U2 - 10.1201/b16500

DO - 10.1201/b16500

M3 - Conference contribution

AN - SCOPUS:84893661127

SN - 9781138001190

SP - 253

EP - 259

BT - GlobalSoilMap

A2 - Arrouays, Dominique

A2 - McKenzie, Neil

A2 - Hempel, John

A2 - Richer de Forges, Anne C.

A2 - McBratney, Alex

PB - CRC Press

CY - Boca Raton, FL

T2 - 1st GlobalSoilMap Conference: Basis of the Global Spatial Soil Information System

Y2 - 7 October 2013 through 9 October 2013

ER -

Modelling soil carbon stocks using legacy site data, in the Mid North region of South Australia

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this