Proceedings Article | 15 August 2007
KEYWORDS: Reflectivity, Vegetation, Data acquisition, Absorbance, Absorption, Databases, Ecosystems, Biological research, Atmospheric modeling, Remote sensing
In this paper, the goal is to found indices best for Cab estimation with leaves and heperion pixels. There are several indices chosen, which showed best results for Cab estimation at both leaf and canopy levels in other studies. Forty-eight typical leaves were sampled in middle and lower reach of the Tarim River, Xinjiang, China. Leaf reflectance and Chlorophyll of leaves collected. Result demonstrated that Indices such as red edge and derivative indices R750/R710, R740/R720, (R734-R747)/(R715+R720), Blog(1/R737), D715/D705,(R734-R747)/(R715+R726), (R694-R680)/(R732-R760) were shown to be the good indicators for Cab estimation at leaf. Hyperion data were acquired for Aqike section in the middle reaches of the Tarim River in Nine 28, 2006. Field data were collected at same day to coincide with the Hyperion, including Chlorophyll of each tree, LAI, green vegetation cover. LAI derived from scanopy 2006. Inventory field plots were 120m×120m quadrants, and Chlorophyll of pixel is deduced from field data of 360 trees. Generally good results are found for Cab estimation at pixel level with indices such as, (R734-R747)/(R715+R726), Blog(1/R737), (R694-R680)/(R732-R760), TCARI, TCARI/OSAVI, MCARI/OSAVI and so on. It was found that (R734-R747)/(R715+R720), Blog(1/R737), D715/D705, (R734-R747)/(R715+R726), (R694-R680)/(R732-R760),R740/R720 were successfully test on leaves and piexls. On the other hand, the "modified" indices (TCARI, MCAVI, TCARI/OSAVI, MCARI/OSAVI) already give good results at the piexl level.
