Evaluating rice crop phenology and crop yield in hilly region using satellite imagery and Google Earth Engine

Authors

  • SHWETA POKHARIYAL Department of Agrometeorology, Govind Ballabh Pant University of Agriculture & Technology, Pantnagar-263145, Uttarakhand, India Indian Institute of Remote Sensing ISRO, Govt. of India, 4, Kalidas Road Dehradun- 248001, Uttarakhand, India
  • N.R. PATEL Agriculture & Soils Department, Indian Institute of Remote Sensing ISRO, Govt. of India, 4, Kalidas Road Dehradun- 248001, Uttarakhand, India
  • AJEET SINGH NAIN Department of Agrometeorology, Govind Ballabh Pant University of Agriculture & Technology, Pantnagar-263145, Uttarakhand, India
  • AKARSH S.G. Agriculture & Soils Department, Indian Institute of Remote Sensing ISRO, Govt. of India, 4, Kalidas Road Dehradun- 248001, Uttarakhand, India
  • R.S. RANA Centre for Geo-Informatics, Research & Training, Chaudhary Sarwan Kumar Himachal Pradesh Krishi Vishwavidyalaya, Palampur, Himachal Pradesh
  • R.K. SINGH Department of Agrometeorology, College of Agriculture, G.B. Pant University of Agriculture and Technology, Pantnagar 263145, Uttarakhand, India
  • RAJEEV RANJAN Department of Agrometeorology, College of Agriculture, G.B. Pant University of Agriculture and Technology, Pantnagar 263145, Uttarakhand, India

DOI:

https://doi.org/10.54386/jam.v26i4.2663

Keywords:

Google Earth Engine, crop phenology, Sentinel-2, NDPI, NDVI, EVI

Abstract

Monitoring vegetation phenology is essential for understanding the impacts of climate change on agricultural production. This study leverages Sentinel-2 data to develop an algorithm in Google Earth Engine (GEE) for calculating phenological metrics of rice crop cultivated over the hilly area, allowing for high-resolution, efficient, and large-scale analysis without the need for data download. The study focuses on key metrics, including the start of the season  and end of the season , length of growing season derived from various vegetation indices. The results demonstrate that NDVI-based phenological metrics closely align with the observed values at the experimental site, Malan. Moreover, the relationship of NDVI based length of growing season with the rice crop yield was found stronger with a R2 value of 0.68, depicting the capability of the satellite-based phenology metrics to estimate the rice crop yield in hilly region of Himachal Pradesh.

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Published

01-12-2024

How to Cite

POKHARIYAL, S., PATEL, N., NAIN, A. S., S.G., A., RANA, R., SINGH, R., & RANJAN, R. (2024). Evaluating rice crop phenology and crop yield in hilly region using satellite imagery and Google Earth Engine. Journal of Agrometeorology, 26(4), 395–400. https://doi.org/10.54386/jam.v26i4.2663

Issue

Vol. 26 No. 4 (2024): December

Section

Research Paper

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Copyright (c) 2024 SHWETA POKHARIYAL, N.R. PATEL, AJEET SINGH NAIN, AKARSH S.G., R.S. RANA, R.K. SINGH, RAJEEV RANJAN

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