EventsThe 3rd International Electronic Conference on Agronomy
Published
This submission belongs to the session S4. Digital farming for the evolution of agriculture and agricultural engineering of the event The 3rd International Electronic Conference on Agronomy
Published date
13 Oct, 2023
Academic Editor
author-avatarMario Cunha
Citation
Varun Narayan Mishra, Baljit Singh, Bhavya Chauhan, Sandeep Kumar Kaushik, Monitoring of wheat crop growth at farm level using time series multispectral satellite imagery, in Proceedings of The 3rd International Electronic Conference on Agronomy, 15 October–30 October 2023, MDPI: Basel, Switzerland, doi: 10.3390/IECAG2023-14983
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Monitoring of wheat crop growth at farm level using time series multispectral satellite imagery

Baljit Singh 1
Bhavya Chauhan 1
1. Amity Institute of Geoinformatics and Remote Sensing (AIGIRS), Amity University, Sector 125, Noida 201313, India, India
2. DeHaat Pvt. Ltd, Sector 30, Gurugram 122011, India, India
Abstract

Monitoring of wheat crop growth plays a crucial role in ensuring effective agricultural management and enhancing food security. Valuable insights into the spatial distribution and various growth stages of wheat crop can be obtained through the combination of multi spectral remote sensing datasets, data analysis, and ground-truth verification. This work aims to monitor the wheat crop at the farm le­vel in the Bathinda district of India during the agricultural ye­ar 2022-23. It involves collecting and analyzing multispe­ctral satellite data collected and analyzed over five­ selected farmlands in study region. Preprocessing of the multispe­ctral satellite data is performed including radiometric and atmosphe­ric corrections. The wheat crop’s health and growth are examined by utilizing various indices such as Land Surface Water Index (LSWI), Normalized Difference Red Edge (NDRE), and Normalized Difference Vegetation Index (NDVI) retrieved from the time series remote sensing datasets. Furthermore, wheat crop monitoring is performed fortnightly data to encompass its health, moisture­ levels, and growth stages for individual farmland. Different farmlands have shown varying LSWI, NDRE, and NDVI values. Variations in crop growth and productivity were observe­d among farmlands due to differe­nces in soil properties and sowing date­s. The findings from this study offer valuable­ insights into the importance of timely sowing, crop he­alth monitoring, irrigation management, and soil suitability in optimizing wheat crop production.

Keywords
Wheat crop
LSWI
NDRE
NDVI
Multi-spectral remote sensing
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