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 proceedingConference contributionpeer-review

2 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 languageEnglish
Title of host publicationGlobalSoilMap
Subtitle of host publicationBasis of the Global Spatial Soil Information System
EditorsDominique Arrouays, Neil McKenzie, John Hempel, Anne C. Richer de Forges, Alex McBratney
Place of PublicationBoca Raton, FL
PublisherCRC Press, Taylor & Francis
Pages253-259
Number of pages7
ISBN (Electronic)9781315775586, 9780429227417
ISBN (Print)9781138001190
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event1st GlobalSoilMap Conference: Basis of the Global Spatial Soil Information System - Orleans, France
Duration: 7 Oct 20139 Oct 2013

Conference

Conference1st GlobalSoilMap Conference: Basis of the Global Spatial Soil Information System
CountryFrance
CityOrleans
Period7/10/139/10/13

Keywords

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

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