Acta Scientific Agriculture (ASAG)(ISSN: 2581-365X)

Editorial Volume 7 Issue 2

How Remote Sensing are Used for Crop Protection

Aakash Adhikari1*, Dipiza Oli2, Deepak Pandey1 and Ditya Lamichhaney1

1George August Universität Göttingen, Göttingen, Germany
2Montana State University, Bozeman, USA

*Corresponding Author: Aakash Adhikari, George August Universität Göttingen, Göttingen, Germany.

Received: December 26, 2022; Published: January 01, 2023

Abstract

Remote sensing involves the use of sensors on aircraft or satellites to collect data about the Earth's surface, including information about crop health and the presence of pests and diseases. This data can be used by farmers to make informed decisions about how to protect their crops and maximize yields. In recent years, satellite-based systems and unmanned aerial vehicles (UAVs or drones) have been developed for this purpose, using high-resolution imagery and machine learning algorithms to detect problems in fields and provide real-time data to farmers. Remote sensing has the potential to greatly improve crop protection in agriculture by providing timely, accurate information to farmers.

References

  1. C Atzberger. “Advances in Remote Sensing of Agriculture: Context Description, Existing Operational Monitoring Systems and Major Information Needs”. Remote Sensing 5.2 (2013): 949-981.
  2. K Ennouri and A Kallel. “Remote Sensing: An Advanced Technique for Crop Condition Assessment” (2019).
  3. MHM Roslim., et al. “Using Remote Sensing and an Unmanned Aerial System for Weed Management in Agricultural Crops: A Review”. Agronomy 11.9 (2021): 1809.
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  5. P Hara., et al. “Selection of Independent Variables for Crop Yield Prediction Using Artificial Neural Network Models with Remote Sensing Data”. Land 6 (2021): 609.
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Citation

Citation: Aakash Adhikari.,et al. “How Remote Sensing are Used for Crop Protection". Acta Scientific Agriculture 7.2 (2023): 01-02.

Copyright

Copyright: © 2023 Aakash Adhikari.,et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.




Metrics

Acceptance rate32%
Acceptance to publication20-30 days
Impact Factor1.014

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