GEOSCAN, résultats de la recherche


TitreALOS PALSAR L-band polarimetric SAR data and in-situ measurements for leaf area index assessment
AuteurCanisius, F; Fernandes, R
SourceCanadian Journal of Remote Sensing vol. 3, (2012), no. 3, 2011 p. 221-229,
Séries alt.Secteur des sciences de la Terre, Contribution externe 20110318
ÉditeurTaylor and Francis Group
Documentpublication en série
Mediapapier; en ligne; numérique
Lat/Long OENS -76.0000 -75.5000 45.5000 45.2500
Sujetstélédétection; imagerie par satellite; végétation; imagerie radar; méthodes radar; humidité du sol; sols; levés à l'infrarouge
Illustrationssatellite images; location maps; bar graphs; graphs
ProgrammeAquifer Assessment & support to mapping, Géoscience des eaux souterraines
Résumé(disponible en anglais seulement)
Leaf Area Index (LAI), a key parameter controlling crop growth and yield models, has been widely estimated using optical satellite measurements. The estimation of LAI from high resolution optical satellite data is limited by cloudy conditions especially when systematic monitoring during the growing season is required. Synthetic Aperture Radar (SAR) data are less susceptible to atmospheric effects than optical data and L-Band SAR data has been related to standing biomass over a number of landscapes. Here we quantify the relationship between LAI and both ALOS PALSAR L-band data and ENVISAT ASAR data under relatively uniform soil moisture conditions. In-situ LAI values of large corn, soybean and pasture fields and forest plots were estimated using digital hemispherical photography, processed using the CANEYE software, between July 4th and 21st, 2006. PALSAR L band polarimetric radar backscatter of crop (corn and soybean) fields and forest plots were in good agreement with measured LAI values but the C-Band ASAR imagery showed weak relationships. The study shows that PALSAR L band polarimetric data has the potential to provide useful estimates of LAI, especially in the case of loss of optical data due to cloud. However, additional work is required to characterize the temporal variability of the relationship between PALSAR backscatter and LAI over varying soil moisture and soil surface conditions.