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Deriving Phenological Metrics from Landsat-OLI for Sugarcane Crop Type Mapping: A Case Study in North India

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Abstract

The crop detection and classification using satellite imagery can be helpful in crop management. Therefore, it is needed to be explored for effective crop detection and classification. In this study, the phenological metrics derived from dense Landsat Normalized Difference Vegetation Index (NDVI) time-series from January 2017 to June 2018 were used to classify sugarcane crop type. The Savitzkey–Golay method was employed as curve fitting method for smoothening and filtering of the pre-processed NDVI time-series data. Thereafter, the phenological metrics extracted from TIMESAT were used to classify planted and ratoon sugarcane using the decision-tree approach. The overall accuracy was 84.5%, and the kappa coefficient was 0.7. The results showed that the classification method was consistent and robust which has the potential to increase the classification accuracy by the use of better resolution satellite imagery time-series. Moreover, the phenological metrics have the potential to explain the spatial distribution of agricultural pattern, use of crop varieties and management practices that can be useful in better understanding of agricultural practices in the region along with crop diversification and crop yield modelling.

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Acknowledgements

This research work carried out as part of pilot project for Department of food & public distribution, Ministry of Consumer Affairs, Food and Public Distribution, Govt. of India. The authors wish to thank Director, IIRS for providing necessary facilities and support to carry out this study. The authors are thankful to anonymous reviewers and Chief Editor of the Journal of the Indian Society of Remote Sensing for their valuable remarks in improving the manuscript.

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  1. Agriculture and Soils Department, Indian Institute of Remote Sensing (IIRS), Dehradun, India

    Ranjeet Singh, N. R. Patel & Abhishek Danodia

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  1. Ranjeet Singh
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Singh, R., Patel, N.R. & Danodia, A. Deriving Phenological Metrics from Landsat-OLI for Sugarcane Crop Type Mapping: A Case Study in North India. J Indian Soc Remote Sens 50, 1021–1030 (2022). https://doi.org/10.1007/s12524-022-01515-w

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