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Ndvi Based Crop Response with Lst and Spi for Vegetation Quality Analysis
Nedun. R1, Sivakumar. R2, Hariharan. B3

1Nedun.R., Department of Civil Engineering, Srm Institute Of Science And Technology, Kattankulathur-603203 (Tamil Nadu), India.
2R. Sivakumar, Department of Civil Engineering, Srm Institute Of Science And Technology, Kattankulathur-603203 (Tamil Nadu), India.
3Hariharan. B., Department of Civil Engineering, Srm Institute Of Science And Technology, Kattankulathur-603203 (Tamil Nadu), India.

Manuscript received on 23 March 2019 | Revised Manuscript received on 30 March 2019 | Manuscript published on 30 March 2019 | PP: 906-910 | Volume-7 Issue-6, March 2019 | Retrieval Number: F25103037619/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Drought, the influencing phenomenon which affects the overall environment in every aspect. It is classified into various types since it is applied to a various sector like agricultural, meteorological and hydrological sectors. Agricultural drought monitoring has a huge impact in the field of agriculture and it helps to better decision-making, which results in an increase in yield and prevents from losses. In this study, Standard Precipitation Index (SPI) and Land Surface Temperature (LST) has been analyzed for the Gingee river basin and their influence on different crop heath (by Normalized Difference Vegetation Index) has been identified by Correlation and regression for Pre-monsoon.
Keywords: Drought, Crop health, LST, SPI, and NDVI.

Scope of the Article: Mobile Applications and Services for IoT