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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
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National Academy of Agricultural Sciences (NAAS)
NAAS Score: *5.38 (2019)
[Effective from January 1, 2019]
For more details click here

ICV 2017: 100.00
Index Copernicus ICI Journals Master List 2017 - IJCMAS--ICV 2017: 100.00
For more details click here

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Original Research Articles

PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : editorijcmas@gmail.com / submit@ijcmas.com
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2017: 100.00
NAAS RATING 2018: 5.38

Int.J.Curr.Microbiol.App.Sci.2017.6(12): 2277-2293
DOI: https://doi.org/10.20546/ijcmas.2017.612.263


Rice Yield Prediction Using MODIS - NDVI (MOD13Q1) and Land Based Observations
K. Ajith1*, V. Geethalakshmi2, K.P. Ragunath3, S. Pazhanivelan3 and Ga. Dheebakaran1
1Agro Climate Research Centre, TNAU, Coimbatore, Tamil Nadu, India
2Department of Agronomy, AC & RI, Madurai, Tamil Nadu, India
3Department of Remote Sensing & GIS, TNAU, Coimbatore, Tamil Nadu, India
*Corresponding author
Abstract:

Reliable yield forecasting within the growing season would enable better planning and more efficient management of grain production, handling and marketing. Remote sensing provides essential technologies for monitoring and observing rice fields over large areas at repeated time intervals. In this study MODIS- NDVI (MOD13Q1) 16 day composite with a spatial resolution of 250m was used for establishing a relationship with rice yield by empirical method. The analysis was conducted for two seasons viz. Samba rice season of 2015-16 and 2016-17 of Thanjavur district. Multi-temporal MODIS- NDVI images in these two seasons were downloaded and pre-processed including re-projection, file type conversion, extraction etc. The result revealed that best relationship form between NDVI and rice age by fitting a quadratic equation. Out of the 28 locations under study, in 24 locations the R2 values for these equations showed fairly higher values ranging from 0.724 to 0.968. Among the three parameters evaluated in this study, summation of the rice NDVI during observation (∑NDVI) showed the highest exponential relationship with the rice yield. Rice yield prediction for Samba rice during 2016- 2017 was done based on the relationship developed between yield and ΣNDVI, derived during 2015-16, i.e. y = 1903.6e0.0201x (R2 = 0.7495). The predicted Samba rice yield during 2016-17 was compared with the actual yields obtained through crop cutting experiments and out of the ten blocks under study 5 blocks had PBIAS values less than ±10 which indicated the good agreement between actual and predicted yield.


Keywords: Rice, Yield, Land based on observations.
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How to cite this article:

Ajith, K., V. Geethalakshmi, K.P. Ragunath, S. Pazhanivelan and Dheebakaran Ga. 2017. Rice Yield Prediction Using MODIS - NDVI (MOD13Q1) and Land Based Observations.Int.J.Curr.Microbiol.App.Sci. 6(12): 2277-2293. doi: https://doi.org/10.20546/ijcmas.2017.612.263