Title :
Retrieval of surface reflectance and LAI mapping with data from ALI, Hyperion and AVIRIS
Author :
Pu, R. ; Gong, P. ; Biging, G. ; Larrieu, M.R.
Author_Institution :
Center for Assessment & Monitoring of Forest & Environ. Resources, California Univ., Berkeley, CA, USA
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.
Keywords :
forestry; geophysical techniques; vegetation mapping; ALI; AVIRIS; Advanced Land Imager; Argentina; Hyperion; Hyperspectral Imager; LAI; MODTRAN4; forest; geophysical measurement technique; hyperspectral remote sensing; leaf area index; multispectral remote sensing; pine trees; surface reflectance; vegetation mapping; Analytical models; Hyperspectral imaging; Hyperspectral sensors; Information retrieval; Infrared imaging; Infrared spectra; Predictive models; Reflectivity; Spectroradiometers; Spectroscopy;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 2002. IGARSS '02. 2002 IEEE International
Print_ISBN :
0-7803-7536-X
DOI :
10.1109/IGARSS.2002.1026133