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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 2018: 95.39
Index Copernicus ICI Journals Master List 2017 - 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 2017: 100.00
NAAS RATING 2018: 5.38

Int.J.Curr.Microbiol.App.Sci.2018.7(4): 2593-2599
DOI: https://doi.org/10.20546/ijcmas.2018.704.295


Rice Acreage Estimation Using Sentinel-1A Dual Polarised SAR Data in Udham Singh Nagar (Uttarakhand)
Chetan Kumar Bhatt and A.S. Nain
Department of Agrometeorology, College of Agriculture, G.B. Pant University of Agriculture and Technology, Pantnagar- 263145 (Dist. Udham Singh Nagar, Uttarakhand), India
*Corresponding author
Abstract:

Udham Singh Nagar is one of major rice producing area of Uttarakhand state, and it falls in Tarai region. The soils of the region are considered as most fertile land in India and aptly support rice production. Rice is a mainly grown in the rainy season which results in a limited number of cloud-free optical remote sensing images for estimation of rice acreage and its monitoring. Sentinel-1A is a European radar imaging satellite launched in 2014. Sentinel-1A satellite launched as a part of the European Union's Copernicus program which provide Synthetic aperture radar (SAR) data i.e. potentially well suited for rice crop monitoring. It allows observations of different features of earth which are independent of weather conditions and solar illumination. The basic goal behind this study was to apply new generation Sentinel-1A data with dual polarization (VH and VV) to rice cropping system mapping and monitoring. SAR data provides an advantage in Land use–land cover (LULC) classification task because these images are not influenced by cloud and leads to increase in mapping accuracy. In the present paper the potential of SAR application for measuring rice acreage during persistent cloud cover has been demonstrated using Sentinel-1A data of European Space Agency. Data were pre-processed by applying European Space Agency’s Sentinel Application Platform (SNAP). The SAR dataset classified with a Support Vector Machine (SVM) algorithm provided in ENVI- 5.1 produced the accurate LULC map, which shows that Udham Singh Nagar covers rice area (108,095 Hectares), followed by forest (140,220 Hectares), water body (15,976 Hectares) and fallow land (5060 Hectares) and lastly built up area (2,586 Hectares) with an overall classification accuracy of 92.88% and a Kappa coefficient of 0.89. This mapping approach provides an advantage of all-weather mapping capability of the radar sensor with the short revisit period of Sentinel-1A satellite. The mapping results represent an important step toward future tasks of retrieval of crop biophysical parameters using SAR data.


Keywords: ENVI, Remote sensing, SAR, Sentinel-1A, SNAP, SVM
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How to cite this article:

Chetan Kumar Bhatt and Nain, A.S. 2018. Rice Acreage Estimation Using Sentinel-1A Dual Polarised SAR Data in Udham Singh Nagar (Uttarakhand).Int.J.Curr.Microbiol.App.Sci. 7(4): 2593-2599. doi: https://doi.org/10.20546/ijcmas.2018.704.295