Abstract
This paper presents the application of NDVI technique for extracting net sown cropped area of major crops cultivated during the winter season (October–March) and calculation of crop diversity index at Nyaya Panchayat level in Bara Tehsil of Allahabad district. Time series NDVI imagery is generated from the processing of Sentinel-2A MSI L1C product. NDVI composite index that contains intersection of time series NDVI threshold based on crop ground truth data is used to extract pure cropped area. Further, the formula given by Gibbs and Martin (Am Sociol Rev 27, 1962) is used to calculate crop diversity index, which uses only net sown area of crops for measuring diversification of crops at the regional level. Derived net sown area from Sentinel-L2A imagery is simulated with reported data of net sown area compiled by the government at the block level. Further, the net sown area is mapped at village level and result analyzes at Nyaya Panchayat level. The result shows that proportion of cultivated area under each crop is changed at Nyaya Panchayat level with change in topography, soil types, irrigation facilities, and distance from major crop market and smooth road infrastructure under the same geo-climatic and socio-economic conditions.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Bhatia, S. S. (1965). Patterns of crop concentration and diversification in India. Economic Geography, 41, 40–56.
Clerici, N., Calderón, C. A. V., & Posada, J. M. (2017). Fusion of Sentinel-1A and Sentinel-2A data for land cover mapping: a case study in the lower Magdalena region, Colombia. Journal of Maps, 13(2), 718–726.
Congalton, R. G., & Green, K. (2009). Assessing the accuracy of remotely sensed data, principles and practices (2nd ed.). London: CRC Press, Taylor & Francis Group.
Dadhwal, V. K., Singh, R. P., Dutta, S., & Parihar, J. S. (2002). Remote sensing based crop inventory: A review of Indian experience. Tropical Ecology, 43(1), 107–122.
Gautham, A. (2016). Agriculture geography. Allahabad: Sharda Pustak Bhawan Publisher.
Gibbs, J., & Martin, W. (1962). Urbanization, technology, and the division of labor: International patterns. American Sociological Review, 27(5), 667–677. Retrieved from http://www.jstor.org/stable/2089624.
Glenn, E. P., Huete, A. R., Nagler, P. L., & Nelson, S. G. (2008). Relationship between remotely-sensed vegetation indices, canopy attributes and plant physiological processes: What vegetation indices can and cannot tell us about the landscape. Sensors (Basel), 8(4), 2136–2160.
Harrison, E.D.S. et al. (2017). Volume 1B: Data—image interpretation. Australia and New Zealand CRC for Spatial Information Publication, pp. 84–85.
Hussain, M. (1997). Agricultural geography (pp. 178–205). New Delhi: Rawat Publishers.
Kurosaki, T. (2001). Specialization and diversification in agricultural transformation: The case of rural Punjab, c.1900–1995. Institute of Economic Research, Hitotsubashi University, Discussion Paper Series.
Mishra, D., & Singh, B. N. (2017). Classification and assessment of land use land cover in Bara Tahsil of Allahabad district using Sentinel-2 satellite imagery. Conference Paper, 38th Asian Conference on Remote Sensing – Space Applications: Touching Human Lives, ACRS.
Panigrahy, R. K., et al. (2009). Study on the Utility of IRS-P6 AWiFS SWIR Band for Crop Discrimination and Classification. Journal of the Indian Society of Remote Sensing, 37, 325–333.
Ranjana (2013). Trends in crop diversification in Punjab–Haryana plains: 1965–1966 to 2005–2006. http://hdl.handle.net/10603/10376.
Saadat, H., Adamowski, J., Bonnell, R., Sharifi, F., Namdar, M., & Ale-Ebrahim, S. (2011). Land use and land cover classification over a large area in Iran based on single date analysis of satellite imagery. ISPRS Journal of Photogrammetry and Remote Sensing, 66(5), 608–619.
Schmidt, M., Pringle, M., Devadas, R., Denham, R., & Tindall, D. A. (2016). A framework for large-area mapping of past and present cropping activity using seasonal Landsat images and time series metrics. Remote Sensing, 8, 312.
Singh, J. (1976). An agricultural geography of Haryana (pp. 313–320). Kurukshetra: Vishal Publication.
Spoto, F., Sy, O., Laberinti, P., Martiort, P., Fernandez, V.,Colin, O. Meygret, A. (2012). Overview of Sentinel-2. In IEEE International geoscience and remote sensing symposium, Munich, 2012 (pp. 1707–1710).
Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment, 8(2), 127–150.
Usman, M., Liedl, R., Shahid, M. A., & Abbas, A. (2015). Land use/land cover classification and its change detection using multi-temporal MODIS NDVI data. Journal of Geographical Sciences, 25, 1479.
Wardlow, B. D., & Egbert, S. L. (2007). Large-area crop mapping using time-series MODIS 250 m NDVI data: An assessment for the U.S. Central Great Plains. Remote Sensing of Environment, 112(2008), 1096–1116.
Acknowledgement
Author Miss. Deeksha Mishra is indepthly acknowledged University Grant Commission (UGC), New Delhi, for providing financial support through NET-JRF Fellowship scheme; Training Division, National Remote Sensing Centre (NRSC), ISRO, Hyderabad, for giving training opportunity in Geospatial Technologies and its applications; Prof. B.N. Singh for their valuable time and useful and practical suggestions.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Mishra, D., Singh, B.N. Derivation of Magnitude of Crop Diversity Through NDVI Composite Index Using Sentinel-2 Satellite Imagery. J Indian Soc Remote Sens 47, 893–906 (2019). https://doi.org/10.1007/s12524-019-00951-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12524-019-00951-5