Skip to Main content Skip to Navigation
Conference papers

Topsoil organic carbon prediction using vis-nir-swir reflectance spectra at lab, field and satellite levels over a periurban region

Abstract : Within the framework of the French Gessol3 Programme (Prostock project), this study aims at comparing various observation scales for predicting topsoil organic carbon (SOC) content using Vis - NIR - SWIR reflectance spectra successively collected at the lab, i n bare agricultural fields or extracted from atmospherically corrected multispectral SPOT images of very high (2.5 m) and medium low (20 m) spatial resolutions. The spatial coverage is that of a large periurban area (221 km²) characterized by cereal croppi ng systems and contrasting soil types. Considering either regional (entire periurban area) or local (a 6 ha - experimental field) scales, a series of 500 - 1000 bootstrapped datasets of calibration/validation samples were generated amongst a total of 165 sampl ed sites and used to predict SOC contents. At the regional scale, Partial Least Squares Regression (PLSR) lab and field - based SOC models resulted in median validation Root Mean Square Errors (RMSE) values of ~3 g.kg - 1 and ~4 g.kg - 1 respectively (=0.95 g.kg - 1 locally for lab - based models), while multiple linear (ML) image - based SOC models resulted in median validation RMSE values between ~4 - 6.6 g.kg - 1. Using an additional independent set of pixels with bare soils, ML models applied to the SPOT images were ‘p ost - validated’ resulting in validation RMSE values of ~4 - 5 g.kg - 1 at the regional scale and ~3 g.kg - 1 locally. Image - based models thus resulted in acceptable validation errors, in possible agreement with the need to spatially monitor SOC contents of region al territories. However, having higher validation bias and error uncertainty than lab or field - based models, they should be considered with caution.
Document type :
Conference papers
Complete list of metadata

https://hal.archives-ouvertes.fr/hal-01628864
Contributor : Archive Ouverte Prodinra Connect in order to contact the contributor
Submitted on : Saturday, November 4, 2017 - 8:26:17 PM
Last modification on : Tuesday, June 15, 2021 - 2:57:21 PM

Identifiers

  • HAL Id : hal-01628864, version 1
  • PRODINRA : 411189
`

Citation

Emmanuelle Vaudour, Jean-Marc Gilliot, Alexis de Junet, Joël Michelin, Dalila Hadjar, et al.. Topsoil organic carbon prediction using vis-nir-swir reflectance spectra at lab, field and satellite levels over a periurban region. Eurosoil 2012, Soil science for the benefit of mankind and environment, 4th International Congress of ECSSS, Jul 2012, Bari, Italie. 2696 p. ⟨hal-01628864⟩

Share

Metrics

Record views

96