Abstract
Data acquired with Advanced Land Imager (ALI), Hyperspectral Imager (Hyperion) and Airborne Visible/Infrared Imaging Spectrometer (AVIRIS), were used to estimate and map forest LAI. Analysis methods include 1) simulating the total at-sensor radiances using MODTRAN4, 2) modifying retrieved surface reflectance with ground spectroradiometric measurements, 3) constructing 6-term LAI prediction models to predict pixel-based LAI, and 4) mapping LAI. The experimental results indicate that the retrieval of surface reflectance is the most successful with AVIRIS, followed by Hyperion and ALI. AVIRIS data can produce more reasonable LAI map than the other two sensors. The results also indicate that Hyperion data have potentially extensive application values in bio-parameter extraction at varied scales.
Published Version
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