Publications des scientifiques de l'IRD

Minu S., Shetty A., Minasny B., Gomez Cécile. (2017). The role of atmospheric correction algorithms in the prediction of soil organic carbon from Hyperion data. International Journal of Remote Sensing, 38 (23), p. 6435-6456. ISSN 0143-1161.

Titre du document
The role of atmospheric correction algorithms in the prediction of soil organic carbon from Hyperion data
Année de publication
2017
Type de document
Article référencé dans le Web of Science WOS:000412545900001
Auteurs
Minu S., Shetty A., Minasny B., Gomez Cécile
Source
International Journal of Remote Sensing, 2017, 38 (23), p. 6435-6456 ISSN 0143-1161
In this study, the role of atmospheric correction algorithm in the prediction of soil organic carbon (SOC) from spaceborne hyperspectral sensor (Hyperion) visible near-infrared (vis-NIR, 400-2500 nm) data was analysed in fields located in two different geographical settings, viz. Karnataka in India and Narrabri in Australia. Atmospheric correction algorithms, (1) ATmospheric CORection (ATCOR), (2) Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH), (3) 6S, and (4) QUick Atmospheric Correction (QUAC), were employed for retrieving spectral reflectance from radiance image. The results showed that ATCOR corrected spectra coupled with partial least square regression prediction model, produced the best SOC prediction performances, irrespective of the study area. Comparing the results across study areas, Karnataka region gave lower prediction accuracy than Narrabri region. This may be explained due to difference in spatial arrangement of field conditions. A spectral similarity comparison of atmospherically corrected Hyperion spectra of soil samples with field-measured vis-NIR spectra was performed. Among the atmospheric correction algorithms, ATCOR corrected spectra found to capture the pattern in soil reflectance curve near 2200 nm. ATCOR's finer spectral sampling distance in shortwave infrared wavelength region compared to other models may be the main reason for its better performance. This work would open up a great scope for accurate SOC mapping when future hyperspectral missions are realized.
Plan de classement
Sciences fondamentales / Techniques d'analyse et de recherche [020] ; Pédologie [068] ; Télédétection [126]
Description Géographique
INDE ; AUSTRALIE
Localisation
Fonds IRD [F B010071235]
Identifiant IRD
fdi:010071235
Contact