Why It Is Important to Follow the Earth

Human development and increasing in population, changing the dimension of the earth's surface. Which in return leads to change in the Land use / Land cover and also we have to increase food production. In India agriculture is mostly dependent on the monsoon. Hydrological cycle (rainfall) is dependent on the earth's surface. To understand the earth as a system why and where the changes are occurring vegetation change is the important parameter. The vital information about the earth’s surface can be extracted from the Remote sensing imaging.

It has the broad range of objective capability and cost effective data collection for regional and large areas. There are several methods used to quantify the vegetation. One of the method is vegetation index differencing which is widely used to extract the information related to vegetation changes.

Vegetation fraction enhance the distinction between vegetation and ground. Influence of illuminate conditions are less effected however it is sensitive for the ground optical properties (Baret and Guyot, 1991).

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Normalized Difference Vegetation Index (NDVI) is one of the important method proposed by Rouse et al. (1974).This index is adaptive to green vegetation (Sellers, 1985); it allows to predict agricultural crops (Tucker and Sellers, 1986; Bullock, 1992) and rainfall in semi-arid regions (Kerr et al., 1989; Nicholson et al., 1990).NDVI can be implemented in the different aspects such as Vegetation dynamics (Wellens, 1997), change detection (Minor et al., 1999) and Land use /Land cover classification (Geerken et al., 2005).

Regardless of the cultivated and physical vegetation the development process is effected by rainfall, temperature etc.., (Li et al.

, 2000; Zhang et al., 2003; Li et al., 2000; Nicholson et al., 1990; Schmidt et al., 2000).One of the study by India Meteorological Department on the impact of the deforestation on simla rainfall revealed that if deforestation increases with decrease in the rainfall. Studying the relationship between the vegetation and rainfall with the spatial variability which enables to forecast the progressive status of the development.

Normalized Difference Vegetation Index (NDVI) data has been collected from the BHUVAN portal. Rainfall in the given study area is highly unpredictable as the different parameters like temperature, wind, pressure etc.., Rainfall data has been collected from the CHRS Portal. NDVI data has been classified using ArcGIS software. Similarly Rainfall data also classified according to the NDVI data using ArcGIS software. The data is collected in word document and analysed using correlation analysis. This analysis is used to predict the vegetation using rainfall and time as a tool. This study shows that both the parameters rainfall and vegetation are inter dependent.