Farm Level Monitoring Through UAV Remote Sensing: a Novel Approach Towards Precision Farming

The demand for increasing food demand can be addressed through precise management of agro-inputs in the limited arable land. To address this, a study was conducted to explore the integration of Unmanned Aerial Vehicle (UAV) and satellite remote sensing for farm level crop monitoring to achieve precision agriculture. Conducted in Bandia, Assam, the research utilized a UAV multispectral data alongside Sentinel-2 satellite data. The methodology involved image segmentation, classification using Naϊve Bayes, and farm-level crop monitoring through various vegetation indices and biophysical parameters. Results showed high accuracy in crop discrimination and demonstrated the complementary capabilities of UAV and satellite data for comprehensive crop analysis. The study highlights the potential of combined UAV and satellite technologies in addressing agricultural challenges, emphasizing for real-time crop requirement for precision farming.

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Publication Details

Published
2024-12-02
DOI
https://doi.org/10.1109/ingarss61818.2024.10984389
Citations
1
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
0.21
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article

Farm Level Monitoring Through UAV Remote Sensing: a Novel Approach Towards Precision Farming

B. K. Handique, Francis Dutta, S. P. Aggarwal, Pradesh Jena
1 citations
Remote Sensing and LiDAR Applications
0.21
article

Farm Level Monitoring Through UAV Remote Sensing: a Novel Approach Towards Precision Farming

B. K. Handique, Francis Dutta, S. P. Aggarwal, Pradesh Jena
article en
1 citations

Abstract

The demand for increasing food demand can be addressed through precise management of agro-inputs in the limited arable land. To address this, a study was conducted to explore the integration of Unmanned Aerial Vehicle (UAV) and satellite remote sensing for farm level crop monitoring to achieve precision agriculture. Conducted in Bandia, Assam, the research utilized a UAV multispectral data alongside Sentinel-2 satellite data. The methodology involved image segmentation, classification using Naϊve Bayes, and farm-level crop monitoring through various vegetation indices and biophysical parameters. Results showed high accuracy in crop discrimination and demonstrated the complementary capabilities of UAV and satellite data for comprehensive crop analysis. The study highlights the potential of combined UAV and satellite technologies in addressing agricultural challenges, emphasizing for real-time crop requirement for precision farming.

Government of India (IN), North Eastern Space Applications Centre (IN)
Zero hunger
Openalex Percentile: Top 47%
Remote Sensing and LiDAR Applications
0.21
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