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Vegetation Cover Estimation Using Sentinel-2 Multispectral Data

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Proceedings on International Conference on Data Analytics and Computing (ICDAC 2022)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 175))

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Abstract

In this paper, the vegetation cover of Prayagraj, Uttar Pradesh, for the year 2016 to the year 2020 has been estimated. This study area has an approximate spatial extent of 3506 km\(^2\). For the classification Sentinel-2, multispectral data on 10 m resolution is utilized, and for winter wheat harvest detection and data selection, MODIS 250 m NDVI time series is used. Each pair of the selected image is classified using a pixel-based Random Forest classifier, which gives an accuracy of about 98.84%. The classified image pair is used for change detection over the year and using this metric area estimation of vegetation cover and crop contribution to vegetation is estimated. As the produced results suggest, the perennial vegetation has been increased from 9.51% in 2016 to 13.07% in 2020 with minor fluctuations in the course of study; also, the crop contribution data fluctuates from a minimum of 75.08% in 2017 to a maximum of 87.98% in 2016.

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Acknowledgements

Author 1 is very thankful to the Ministry of Education, India, for the financial support to carry out this research work.

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Authors and Affiliations

  1. Indian Institute of Information Technology Allahabad, Allahabad, India

    Harsh Srivastava & Triloki Pant

Authors
  1. Harsh Srivastava
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  2. Triloki Pant
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Corresponding author

Correspondence to Harsh Srivastava .

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Editors and Affiliations

  1. Department of Mathematics, DR BR Ambedkar NIT Jalandhar, Jalandhar, India

    Anupam Yadav

  2. School of Mathematical Sciences, College of Science and Technology, Wenzhou Kean University, Wenzhou, China

    Gaurav Gupta

  3. School of Mathematical Sciences, College of Science and Technology, Wenzhou Kean University, Wenzhou, China

    Puneet Rana

  4. School of Civil, Environmental and Architectural Engineering, Korea University, Seoul, Korea (Republic of)

    Joong Hoon Kim

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Srivastava, H., Pant, T. (2023). Vegetation Cover Estimation Using Sentinel-2 Multispectral Data. In: Yadav, A., Gupta, G., Rana, P., Kim, J.H. (eds) Proceedings on International Conference on Data Analytics and Computing. ICDAC 2022. Lecture Notes on Data Engineering and Communications Technologies, vol 175. Springer, Singapore. https://doi.org/10.1007/978-981-99-3432-4_8

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