Purushothama et al., (2005) analysed physico -chemical characteristics of the Keladi tank water at sagar taluk in Shimoga district, Karnataka, India, were studied from January to December 2004. The water temperature recorded ranged between 25-30 0 C, the minimum temperature was encountered in September and maximum in March. The pH of the water was slightly acidic to alkaline, ranging from 6.5 to 8.5. The electrical conductivity was observed approximately 57 to 138 micro mhos/cm. Singandhupe and Madhulika (2005) conducted experiment on estimation of reference evapotranspiration and crop coefficient in
NRSC-CN for surface runoff estimation is one of the most widely used methods. GIS and remote sensing techniques facilitate accurate estimation of surface runoff from an area. Water availability estimation can be understand by rainfall and runoff is essential. Runoff generated by rainfall is not only dependent on the intensity, duration and the distribution of rainfall, but also soil type, vegetation, and land-use types have significant effects on the runoff pattern. The present study aims to estimate runoff in a study area. The study was carried out in Godavari Eastern Delta in Andhra Pradesh, India. The land use/land cover map, soil map was prepared. The soil and land use map has been prepared by the information available at Andhra Pradesh space application centre. For the rectification of reference, soil and land use map of the study area ERDAS IMAGINE-8.4 software was used. For 30 years surface runoff was estimated, as the runoff value depends on the rainfall, trend of runoff was found to be highly dependable on the quantity of rainfall received within the entire study area. The yearly trend of rainfall during 1987 was 8.97 it’s but the other years, and therefore the runoff was also found to follow an equivalent trend. Similarly, for the year 1995, the runoff was recorded as high, which was also having the highest rainfall.
Spatial variability in land use changes creates a need for a wide range of applications, including landslide, erosion, land planning, global warming etc. This study presents the analysis of satellite image based on Normalized Difference Vegetation Index (NDVI) in Godavari eastern delta. Four spectral indices were investigated in this study. These indices were NIR (red and near infrared) based NDVI, green and NIR based GVI (Green Vegetation Index), red and NIR based soil adjusted vegetation index (SAVI), and red and NIR based perpendicular vegetation index (PVI). These four indices were investigated for 2011-12 kharif, rabi and 2016-17 kharif, rabi of Godavari eastern delta. Different threshold values of NDVI are used for generating the false colour composite of the classified objects. For this purpose, supervised classification is applied to Landsat images acquired in 2011-12 and 2016-17. Image classification of six reflective bands of two Landsat images is carried out by using maximum likelihood method with the aid of ground truth data obtained from satellite images of 2011-12 and 2016-17. There was 11% and 30% increase in vegetation during kharif and rabi seasons from 2011-12 to 2016-17. The vegetation analysis can be used to provide humanitarian aid, damage assessment in case of unfortunate natural disasters and furthermore to device new protection strategies.
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