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Articles | Volume XL-8
https://doi.org/10.5194/isprsarchives-XL-8-561-2014
https://doi.org/10.5194/isprsarchives-XL-8-561-2014
28 Nov 2014
 | 28 Nov 2014

Assessment of net primary productivity over India using Indian geostationary satellite (INSAT-3A) data

S. K. Goroshi, R. P. Singh, R. Pradhan, and J. S. Parihar

Keywords: INSAT-3A, NPP, Productivity, CASA, Ecosystem

Abstract. Polar orbiting satellites (MODIS and SPOT) have been commonly used to measure terrestrial Net Primary Productivity (NPP) at regional/global scale. Charge Coupled Device (CCD) instrument on geostationary INSAT-3A platform provides a unique opportunity for continuous monitoring of ecosystem pattern and process study. An improved Carnegie-Ames-Stanford Approach (iCASA) model is one of the most expedient and precise ecosystem models to estimate terrestrial NPP. In this paper, an assessment of terrestrial NPP over India was carried out using the iCASA ecosystem model based on the INSAT CCD derived Normalized Difference Vegetation Index (NDVI) with multisource meteorological data for the year 2009. NPP estimated from the INSAT CCD followed the characteristic growth profile of most of the vegetation types in the country. NPP attained maximum during August and September, while minimum in April. Annual NPP for different vegetation types varied from 1104.55 gC m−2 year−1 (evergreen broadleaf forest) to 231.9 gC m−2 year−1 (grassland) with an average NPP of 590 gC m−2 year−1. We estimated 1.9 PgC of net carbon fixation over Indian landmass in 2009. Biome level comparison between INSAT derived NPP and MODIS NPP indicated a good agreement with the Willmott’s index of agreement (d) ranging from 0.61 (Mixed forest) to 0.99 (Open Shrubland). Our findings are consistent with the earlier NPP studies in India and indicate that INSAT derived NPP has the capability to detect spatial and temporal variability of terrestrial NPP over a wide range of terrestrial ecosystems in India. Thus INSAT-3A data can be used as one of the potential satellite data source for accurate biome level carbon estimation in India.