1Department of Remote Sensing and Geographic Information Systems, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India
2Center for Water and Geospatial Studies, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India
3Department of Physical Sciences and Information Technology, Tamil Nadu Agricultural University, Coimbatore-641003, Tamil Nadu, India
4Agro Climate Research Center, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India
*Corresponding Author: R. Jagadeeswaran, Department of Remote Sensing and Geographic Information Systems, Tamil Nadu Agricultural University, Coimbatore-641 003, Tamil Nadu, India, Email: jagawaran@tnau.ac.in
Online Published on 23 June, 2025.
The Agricultural drought during kharif seasons of the year 2019 to 2023 in Tamil Nadu state in India was analyzed in using the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS). Monthly precipitation data from 1991 to 2023 were obtained for the study, with the main objective of evaluating the duration, spatial extent, severity and lag time of meteorological and agricultural drought in the study area.
The Enhanced Vegetation Index (EVI) was generated by the Moderate Resolution Imaging Spectroradiometer (MODIS) data. The pixel reliability layer was introduced based on the calculation of the cloud coverage at the moment of image acquisition. The Standardized Precipitation Index SPI in one month time scale plays very significant role in any vulnerability studies for accurate prediction of any events.
In the present study, the EVI for Kharif season was considered for five years i.e., 2019-2023 and it was correlated with the SPI at various time scales. The correlation coefficient of SPI was 0.39 with 0.1% level of significance, in other words, EVI 2022 was well correlated with SPI-6. Also, the relation between EVI and precipitation with 9 months interval was also tested. The 12 months interval of precipitation have more stress on vegetation and it can negatively impact the agriculture activities leading to crop failures.
Agricultural drought, CHIRPS, EVI, MODIS data, SPI
