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—Leaf area index (LAI) is one of the most important Earth surface parameters in modeling ecosystems and their interaction with climate. Based on a geometrical optical model (Four-Scale) and LAI algorithms previously derived for Canada-wide applications, this paper presents a new algorithm for the global retrieval of LAI where the bidirectional reflectance(More)
A new set of recently developed leaf area index (LAI) algorithms has been employed for producing a global LAI dataset at 1 km resolution and in time-steps of 10 days, using data from the Satellite pour l'observation de la terre (SPOT) VEGETATION (VGT) sensor. In this paper, this new LAI product is compared with the global MODIS Collection 4 LAI product over(More)
—Forest background, consisting of understory, moss, litter, and soil, contributes significantly to optical remote sensing signals from forests in the boreal region. In this paper, we present results of background reflectance retrieval from multiangle high-resolution Compact Airborne Spectrographic Imager sensor data over a boreal forest area near Sudbury,(More)
—Measurements at more than one angle capture the directional anisotropy of solar radiance reflected from vegetated surfaces. According to our recent research, we propose that the best two view angles for vegetation structural mapping are the following: 1) the hotspot, where the Sun and view directions coincide, and 2) the darkspot, where the sensor sees the(More)
Foliage clumping can be estimated from logarithm averaging method in LAI-2000. The spatial scaling of clumping effects considered by the instrument is dependent on the sensor’s azimuthal view. Accurate estimates of foliage clumping index (Ω) are required to improve the retrieval of leaf area index (L) from optical instruments like LAI-2000/2200 Plant Canopy(More)