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Analysis of vegetation response to rainfall with satellite images in Bikaner district, Rajasthan (India): a geo-spatial approach
... For identifying and monitoring the long-term changes in vegetated areas, optical remote sensing has been popularly used since the early 1980s. The relationship between rainfall and vegetation response has been observed very robust way by various satellites in different spatial and temporal resolutions (Wang et al. 2003;Mendez-Barroso et al. 2009;Dutta et al. 2013;Kundu et al. 2015a). ...
Vegetation cover is an important natural resource of the terrestrial ecosystem, and it has significant role in preserving the ecological balance in an area. Analyzing the dynamic pattern of vegetation cover and its trend can be a key to explain any unusual condition of the environment. Bundelkhand, located at the central part of India, has experienced recurrent drought events in last decade, and considering the devastating effects of drought in that region, the present study aims to explore the long-term trend of vegetation using geo-spatial technology. The remote sensing-based SPOT-VGT NDVI data were used to identify the changes in vegetation with time. The normalized difference vegetation index (NDVI) has proven to be a very powerful indicator of global vegetation productivity. In this study, we used linear regression model for evaluating the long-term trend of vegetation considering NDVI as dependable and time as independent variable. Our results showed that there is a varying pattern of vegetation trend and its response to rainfall.
... In addition, it can be used for monitoring the continental land use and land cover, classification of vegetation and its phenology (Tucker et al., 1982;Tarpley et al., 1984;Justice et al., 1985). It is also effective for monitoring desertification (Kundu and Dutta, 2011;Kundu et al., 2015b, drought (Kundu et al., 2015aDutta et al., 2013Dutta et al., , 2015aPatel and Yadav, 2015), estimating net primary production of vegetation, crop growth conditions, yields, detecting weather impacts etc. (Kogan 1987;Dabrowska-Zielinska et al., 2002;Kundu et al., 2014Kundu et al., , 2015c. ...
Climate change has become a serious concern worldwide owing to its multifaceted impact upon the physical as well as socio-economic environment (IPCC, 2013). Vulnerability to climate change is much higher in the developing countries like India, where the economy is mainly agro-based and productivity from the agricultural sector is dependent upon summer monsoon rainfall. Hence, assessing the quantitative relationship between vegetation patterns and climatic influence has become an increasingly important study conducted on regional and global scales. As vegetation cover plays a key role in conserving the natural environment, studying the spatio-temporal trend of vegetation is crucial in identifying changes in the natural environment. We analysed the spatial responses of SPOT-VGT NDVI to TRMM based rainfall during a sixteen year period (1998–2013) in the Bundelkhand region of Central India. The Normalized Difference Vegetation Index (NDVI) has proven to be a strong indicator of global vegetation productivity. Among climatic factors, rainfall robustly influences both spatial and temporal outline of NDVI. In this study, we used linear regression for analysing the statistical relationship among NDVI and rainfall and their trends. The study reveals a varying pattern of vegetation dynamics in response to rainfall over the area.
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