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Research proved the superiority of Vegetation Index based on the Universal Pattern Decomposition Method (VIUPD) over other Vegetation indices for both Hyperspectral and Multispectral data

Recent study published in International Journal of Remote Sensing by Chen et al., 2013 proved the superiority of VIUPD over 12 other famous indices for Hyperion and Chris data. It is worth mentioning here that VIUPD was a brain child of the Prof. Lifu Zhang, Head of the Hyperspectral Remote Sensing Laboratory, IRSA which he introduced in 2005 for Multispectral data.

 

Table: Chen et al., 2013 proved the superiority of VIUPD over 12 other indices for Hyperion and Chris data

 

Unlike other VIs, VIUPD is a sensor-independent index. VIUPD was proved to be more sensitive in reflecting vegetation activity than the normalized difference vegetation index (NDVI) and the enhanced vegetation index (EVI), using ground data (Zhang et al. 2007b).

 

 

Figure: Sensor Independence of VIUPD over NDVI and EVI (Results are chosen from Prof. Zhang Lifu Doctoral thesis, 2005).

 

Important references published by the scientists of HRSL, IRSA related to this research are as under:

1. Xiaoping Chen , Lifu Zhang , Xia Zhang & Bo Liu (2013): Comparison of the sensor dependence of vegetation indices based on Hyperion and CHRIS hyperspectral data, International Journal of Remote Sensing, 34:6, 2200-2215
2. Zhang, L., S. Furumi, K. Murumatsu, N. Fujiwara, M. Daigo, and L. Zhang. 2003. Universality of Modified Pattern Decomposition Method for Satellite Sensors. In Asia GIS Conference, October 8–11, 2003, Wuhan. Accessed April 8, 2005.  
3. Zhang, L., S. Furumi, K. Murumatsu, N. Fujiwara, M. Daigo, and L. Zhang. 2006a. “Sensor-Independent Analysis Method for Hyperspectral Data Based on the Pattern Decomposition Method.” International Journal of Remote Sensing 27: 4899–910.
4. Zhang, L., N. Fujiwara, S. Furumi, K. Muramatsu, M. Daigo, and L. Zhang. 2007a. “Assessment of the Universal Pattern Decomposition Method Using MODIS and ETM+ Data.” International Journal of Remote Sensing 28: 125–42.
5. Zhang, L., S. Furumi, K. Murumatsu, N. Fujiwara, M. Daigo, and L. Zhang. 2007b. “A New Vegetation Index Based on the Universal Pattern Decomposition Method.” International Journal of Remote Sensing 28: 107–24.
6. Zhang, L., B. Liu, B. Zhang, and Q. Tong. 2010. “An Evaluation of the Effect of the Spectral Response Function of Satellite Sensors on the Precision of the Universal Pattern Decomposition Method.” International Journal of Remote Sensing 31: 2083–90.