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http://dx.doi.org/10.7780/kjrs.2017.33.5.1.5

Evaluating Applicability of Photochemical Reflectance Index using Airborne-Based Hyperspectral Image: With Shadow Effect and Spectral Bands Characteristics  

Ryu, Jae-Hyun (Department of Applied Plant Science, Chonnam National University)
Shin, Jung Il (Research of Technology, GEOSTORY. Co., Ltd)
Lee, Chang Suk (National Meteorological Satellite Center, Korea Meteorological Administration)
Hong, Sungwook (Department of Environment, Energy, and Geoinfomatics, Sejong University)
Lee, Yang-Won (Department of Spatial information Engineering, Pukyong National University)
Cho, Jaeil (Department of Applied Plant Science, Chonnam National University)
Publication Information
Korean Journal of Remote Sensing / v.33, no.5_1, 2017 , pp. 507-519 More about this Journal
Abstract
The applications of NDVI (Normalized Difference Vegetation Index) as a vegetation index has been widely used to understand vegetation biomass and physiological activities. However, NDVI is not suitable way for monitoring vegetation stress because it is less sensitive to change in physiological state than biomass. PRI (Photochemical Reflectance Index) is well developed to present physiological activities of vegetation, particularly high-light-stress condition, and it has been adopted in several satellites to be launched in the future. Thus, the understanding of PRI performance and the development of analysis method will be necessary. This study aims to interpret the characteristics of light-stress-sensitive PRI in shadow areas and to evaluate the PRI calculated by other wavelengths (i.e., 488.9 nm, 553.6 nm, 646.9 nm, and 668.4 nm) instead of 570 nm that used in original PRI. Using airborne-based hyperspectral image, we found that PRI values were increased in shadow detection due to the reduction of high light induced physiological stress. However, the qualities of both PRI and NDVI data were dramatically decreased when the shadow index (SI) exceeded the threshold (SI<25). In addition, the PRI calculated using by 553.6 nm had best correlation with original PRI. This relationship was improved by multiple regression analysis including reflectances of RED and NIR. These results will be helpful to the understanding of physiological meaning on the application of PRI.
Keywords
Photochemical Reflectance Index; Shadow effect; Hyperspectral Image;
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