మా గ్రూప్ ప్రతి సంవత్సరం USA, యూరప్ & ఆసియా అంతటా 3000+ గ్లోబల్ కాన్ఫరెన్స్ ఈవెంట్లను నిర్వహిస్తుంది మరియు 1000 కంటే ఎక్కువ సైంటిఫిక్ సొసైటీల మద్దతుతో 700+ ఓపెన్ యాక్సెస్ జర్నల్లను ప్రచురిస్తుంది , ఇందులో 50000 మంది ప్రముఖ వ్యక్తులు, ప్రఖ్యాత శాస్త్రవేత్తలు ఎడిటోరియల్ బోర్డ్ సభ్యులుగా ఉన్నారు.
ఎక్కువ మంది పాఠకులు మరియు అనులేఖనాలను పొందే ఓపెన్ యాక్సెస్ జర్నల్స్
700 జర్నల్స్ మరియు 15,000,000 రీడర్లు ప్రతి జర్నల్ 25,000+ రీడర్లను పొందుతున్నారు
Kannan R, Ramanamurthy MV and Kanungo A*
The shoreline is one of the most important features on earth’s surface. They are highly dynamic and ever changing. Changes are over time scales including minutes, hours, decades and Centuries. Spatial scales vary from local to regional to worldwide. Although change is continuously occurring, it doesn’t occur in a constant manner. Many factors influence these changes including the type of shoreline (rocky, sandy), wave activity, tidal variations, storms and human impacts. The shoreline change study is necessary for updating the shoreline change maps and management of natural resources. Shorelines are the key element in coastal GIS and provide the most information on coastal landform dynamics. The frequently monitoring coast only to accesses variation of shoreline changes. In this paper investigate the shoreline changes of Nellore district in Andhra Pradesh coast, as well as find the quantity of the erosion and accretion rate. Using multi-temporal resolution satellite data (TM & LISS III, IV) and Geographic information system (GIS) for past 25 years period i.e., from 1989 to 2015. Nellore having length of coast line is 167 km for this study used. The resultant coastal maps were used to estimate the geomorphologic changes and shifting of the shoreline position. This integrated study is found useful for exploring accretion and erosion processes in the region. About 87.6 km of coastline was found to be accreting nature with average of +1.40 m/yr followed by 38.4 km of coastal line eroding with average of -1.36 m/yr and stable coastline of 41.4 km was found. This study demonstrates that combined use of satellite imagery and statistical method such as linear regression for shoreline change analysis are helpful for erosion monitoring and preventive measure.