A sequential model for disaggregating near-surface soil moisture observations using multi-resolution thermal sensors - IRD - Institut de recherche pour le développement Accéder directement au contenu
Article Dans Une Revue Remote Sensing of Environment Année : 2009

A sequential model for disaggregating near-surface soil moisture observations using multi-resolution thermal sensors

Résumé

A sequential model is developed to disaggregate microwave-derived soil moisture from 40 km to 4 km resolution using MODIS (Moderate Imaging Spectroradiometer) data and subsequently from 4 km to 500 m resolution using ASTER (Advanced Scanning Thermal Emission and Reflection Radiometer) data. The 1 km resolution airborne data collected during the three-week National Airborne Field Experiment 2006 (NAFE'06) are used to simulate the 40 km pixels, and a thermal-based disaggregation algorithm is applied using 1 km resolution MODIS and 100 m resolution ASTER data. The downscaled soil moisture data are subsequently evaluated using a combination of airborne and in situ soil moisture measurements. A key step in the procedure is to identify an optimal downscaling resolution in terms of disaggregation accuracy and sub-pixel soil moisture variability. Very consistent optimal downscaling resolutions are obtained for MODIS aboard Terra, MODIS aboard Aqua and ASTER, which are 4 to 5 times the thermal sensor resolution. The root mean square error between the 500 m resolution sequentially disaggregated and ground-measured soil moisture is 0.^062 vol./vol. with a bias of −0.045^ vol./vol. and values ranging from 0.08 to 0.40^ vol./vol.

Domaines

Ecosystèmes
Fichier principal
Vignette du fichier
RSE_7453OlivierMerlin.pdf (731.74 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

ird-00403130 , version 1 (09-07-2009)

Identifiants

Citer

Olivier Merlin, Al Bitar Ahmad, J P. Walker, Yann H. Kerr. A sequential model for disaggregating near-surface soil moisture observations using multi-resolution thermal sensors. Remote Sensing of Environment, 2009, pp.RSE-07453; No of Pages 10. ⟨10.1016/j.rse.2009.06.012⟩. ⟨ird-00403130⟩
159 Consultations
640 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More