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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
IJCMAS is now DOI (CrossRef) registered Research Journal. The DOIs are assigned to all published IJCMAS Articles.
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National Academy of Agricultural Sciences (NAAS)
NAAS Score: *5.38 (2020)
[Effective from January 1, 2020]
For more details click here

ICV 2018: 95.39
Index Copernicus ICI Journals Master List 2018 - IJCMAS--ICV 2018: 95.39
For more details click here

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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 2018: 95.39
NAAS RATING 2020: 5.38

Int.J.Curr.Microbiol.App.Sci.2017.6(7): 2327-2335
DOI: https://doi.org/10.20546/ijcmas.2017.607.275


Rice Acreage Estimation in Thanjavur, Tamil Nadu Using Lands at 8 OLIIMAGES and GIS Techniques
K. Ajith1*, V. Geethalakshmi2, K.P. Ragunath3, S. Pazhanivelan3 and S. Panneerselvam1
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:

Rice acreage estimation prior to harvest is very essential in predicting agricultural production for devising policies to face contingencies. The present study emphasizes the application of Remote Sensing (RS) and Geographical Information System (GIS) for acreage estimation of rice in Thanjavur district of Tamil Nadu. Mono temporal cloud free Landsat 8 OLIimageries at a spatial resolution of 30 m obtained during reproductive stage of the crop was used for this research. The administrative boundaries of the district were superimposed over the image to facilitate easy classification. ArcGIS 10.1 software was used for data processing and analysis. Estimation of area under rice during the Samba season and other formsof land cover in the study area were delineated following digital unsupervised classification using False Colour Composite (FCC) of the Bands 3, 4, and 5 of the Landsat 8 OLI. The classification accuracy was assessed by identifying a total of 53 validation points with 28 rice and 25 non rice points across the district. The overall classification accuracy was 87% with a Kappa coefficient of 0.74. Large homogenous rice areas and small fragmented heterogeneous rice areas were classified equally well.


Keywords: Rice, Remote sensing, Acreage estimation, Lands at 8 OLI images.
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How to cite this article:

Ajith, K., V. Geethalakshmi, K.P. Ragunath, S. Pazhanivelan and Panneerselvam, S. 2017. Rice Acreage Estimation in Thanjavur, Tamil Nadu Using Lands at 8 OLIIMAGES and GIS Techniques.Int.J.Curr.Microbiol.App.Sci. 6(7): 2327-2335. doi: https://doi.org/10.20546/ijcmas.2017.607.275