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Scrutinising MODIS and GIMMS Vegetation Indices for Extracting Growth Rhythm of Natural Vegetation in India

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Abstract

Satellite derived vegetation vigour has been successfully used for various environmental modeling since 1972. However, extraction of reliable annual growth information about natural vegetation (i.e., phenology) has been of recent interest due to their important role in many global models and free availability of time-series satellite data. In this study, usability of Moderate Resolution Imaging Spectro-radiometer (MODIS) and Global Inventory Modelling and Mapping Studies (GIMMS) based products in extracting phenology information about evergreen, semi-evergreen, moist deciduous and dry deciduous vegetation in India was explored. The MODIS NDVI and EVI time-series data (MOD13C1: 5.6 km spatial resolution with 16 day temporal resolution—2001 to 2010) and GIMMS NDVI time-series data(8 km spatial resolution with 15 day temporal resolution—2000 to 2006) were used. These three differently derived vegetation indices were analysed to extract and understand the vegetative growth rhythm over different regions of India. Algorithm was developed to derive onset of greenness and end of senescence automatically. The comparative analysis about differences in the results from these products was carried out. Due to dominant noise in the values of NDVI from GIMMS and MODIS during monsoon period the phenology rhythm were wrongly depicted, especially for evergreen and semi-evergreen vegetation in India. Hence, care is needed before using these data sets for understanding vegetative dynamics, biomass cestimation and carbon studies. MODIS EVI based results were truthful and comparable to ground reality. The study reveals spatio-temporal patterns of phenology, rate of greening, rate of senescence, and differences in results from these three products.

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Acknowledgments

Thanks are due to NASA and GIMMS team for providing the processed AVHRR GIMMS NDVI data and MODIS data and making it freely available to global researchers. Thanks are also due to the reviewer for constructive comments which helped in improving the usability of the work.

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  1. Department of Remote Sensing, Birla Institute of Technology (BIT), Mesra, Ranchi, 835215, Jharkhand, India

    C. Jeganathan & Nilay Nishant

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  1. C. Jeganathan
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  2. Nilay Nishant
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Correspondence to C. Jeganathan.

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Jeganathan, C., Nishant, N. Scrutinising MODIS and GIMMS Vegetation Indices for Extracting Growth Rhythm of Natural Vegetation in India. J Indian Soc Remote Sens 42, 397–408 (2014). https://doi.org/10.1007/s12524-013-0337-5

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  • DOI: https://doi.org/10.1007/s12524-013-0337-5

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