Wheat Crop Acreage Estimation Based on Remote Sensing and GIS in Jabalpur (Madhya Pradesh, India)

Main Article Content

Umakant Rawat
Ankit Yadav
P.S. Pawar
Aniket Rajput
Devendra Vasht
S. Nema

Abstract

Mapping and classification crop by using satellite images is a challenging task that can minimize the complexities of field visits. The recently launched Sentinel-2 satellite has thirteen spectral bands, short revisit time and determination at three different resolutions (10 m, 20 m and 60 m), besides that, the free availability of the images makes it a good choice for vegetation mapping. This study aims to classify crop, using single date Sentinel-2 imagery within the Jabalpur, state of Madhya Pradesh, India. The classification was performed by using Unsupervised Classification. In this study, four spectral bands, i.e., Near Infrared, Red, Green, and Blue of Sentinel-2 were stacked for the classification. The results show that the area of wheat crop corresponds to 83.07%; Gram/ Pulses, 14.64%; and other crop, 2.28%. The overall accuracy and overall Kappa Statistics of the classification using Sentinel-2 imagery are 85.71% and 0.819%, respectively. Therefore, this study has found that Sentinel-2 presented great potential in the mapping of the agriculture areas of Jabalpur by remote sensing.

Keywords:
Sentinel-2, unsupervised classification, spectral bands, crop

Article Details

How to Cite
Rawat, U., Yadav, A., Pawar, P., Rajput, A., Vasht, D., & Nema, S. (2021). Wheat Crop Acreage Estimation Based on Remote Sensing and GIS in Jabalpur (Madhya Pradesh, India). Asian Journal of Agricultural Extension, Economics & Sociology, 39(2), 88-94. https://doi.org/10.9734/ajaees/2021/v39i230533
Section
Original Research Article

References

Dadhawal VK, Parihar JS. Estimation of 1983-84. Wheat acreage of Karnal district (Haryana) using Landsat MSS digital data. Scientific Note: IRS-UP/SAC/ CPF/SN/09/85. Space Applications Centre, Ahmedabad; 1985.

Kingra PK, Majumder D, Singh SP. Application of remote sensing and GIS in agriculture and natural resource management under changing climatic Agric Res J. 2016;53(3):295-302.

Hayes MJ, Decker WL. Using NOAA AVHRR data to estimate maize production in the United States Corn Belt. Int. J. Remote Sens. 1996;17:3189–3200.

Prasad AK, Chai L, Singh RP, et al. Crop yield estimation model for Iowa using remote sensing and surface parameters. International Journal of Applied Earth Observation and Geoinformation. 2006; 8(1):26-33.

Sahai B, Dadhwal VK. Remote sensing in agriculture. In: Technology bunding and agrarian prosparity (eds: J.P. Verma and A. Verma), Malhotra Publishing House, New Delhi. 1990;83-98.

Acharya SM, Pawar SS, Wable NB. Application of remote sensing & gis in agriculture. International Journal of Advanced Engineering Research and Science. 2018;5(4).

Bairagi GD, Zia-ul Hassan. Wheat crop production estimation using satellite data. Journal of the Indian Society of Remote Sensing. 2002;30(4):213-219.

Panigrahy S, Ray SS. Remote sensing. In: Environment and Agriculture. (Eds. K. L. Chadha & M. S. Swaminathan). Malhotra Publishing House, New Delhi. 2006;361-375.

Navalgund RR, Jayaraman V, Roy PS. Remote sensing applications: An overview. Current Science. 2007;93(12):1747-1766.

Campbell NA, De Boer ES, Hick PT. Some observations on crop profile modeling. International Journal of Remote Sensing. 1987;8:193-201.

Saini R, Ghosh SK. Crop classification on single date sentinel-2 imagery using random forest and suppor vector machine, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-5; 2018.

Segarra J, Buchaillot ML, Araus JL, Shawn C. Remote sensing for precision agriculture: Sentinel-2 improved features and applications MDPI; 2020.

Foody GM. Status of land cover classification accuracy assessment, Remote Sens. Environ. 2002;80:185–201.