 |
| Titel |
Application of VNIR diffuse reflectance spectroscopy for mapping of organic matter redistribution due to erosion and deposition processes |
| VerfasserIn |
Ales Klement, Lukas Brodsky, Ondrej Jaksik, Miroslav Fer, Radka Kodešová |
| Konferenz |
EGU General Assembly 2014
|
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 16 (2014) |
| Datensatznummer |
250092061
|
| Publikation (Nr.) |
 EGU/EGU2014-6386.pdf |
|
|
|
|
|
| Zusammenfassung |
| Visible and near-infrared (VNIR) diffuse reflectance spectroscopy is cost- and time-effective
and environmentally friendly techniques method used for prediction of soil properties. Study
was performed on the soils from the agricultural land from the municipalities of
Brumovice (209 samples), Sedlcany (67 samples), Vidim (74 samples) and Zelezna
(32 samples). In Brumovice original soil type was Haplic Chernozem on loess,
which was due to erosion changed into Regosol (steep parts) and Colluvial soil
(base slope and the tributary valley). A similar process has been described at other
three locations Sedlcany, Vidim and Zelezna where the original soil types were
Haplic Cambisol on gneiss, Haplic Luvisol on loess and Haplic Cambisol on shales,
respectively.
The goal of the study was to evaluate relationship between soil spectra curves and organic
matter content to provide an efficient tool for mapping of organic matter redistribution (i.e.
soil degradation) due to erosion and deposition processes. Samples were taken from the
topsoil within regular grid covering studied areas. The soil spectra curves (of air
dry soil and sieved using 0.2 mm sieve) were measured in the laboratory using
spectrometer FieldSpec®3 (350 – 2 500 nm). Partial least squares regression (PLSR)
was used for modeling of the relationship between spectra and measured organic
matter content. Prediction ability was evaluated using the R2, root mean square error
(RMSE).
The results showed the best prediction of the organic matter content was obtained for soil
samples from Brumovice (R2 = 0.78, RMSE = 0.15) and decreased as follows: Zelezna (R2 =
0.68, RMSE = 0.23), Sedlcany (R2 = 0.64, RMSE = 0.18) and Vidim (R2 = 0.61, RMSE =
0.12). In general, the results confirmed that the measurement of soil spectral characteristics
is a promising technology for a digital soil mapping and predicting studied soil
properties.
Acknowledgment: Authors acknowledge the financial support of the Ministry of
Agriculture of the Czech Republic (grant No. QJ1230319). |
|
|
|
|
|
|