Precision Agriculture: UAV-Based Soil Mapping and Remote Sensing Applications

Using Unmanned Aerial Vehicle (UAV) equipped with remote sensing cameras that measure the electromagnetic spectrum of light reflected back from the ground below, this technology does soil mapping and field analysis. The way that different elements reflect different light wavelengths can be used to identify them. Reams of data on those wavelengths are gathered by multispectral image sensors, which power sophisticated AI software that can identify even the smallest variations in the elemental composition of soil. There are numerous positives to soil mapping, including helping farmers choose the best crops, applying the right fertilizers, and scheduling irrigation. Soil mapping also makes it easier to create plans for soil conservation and restoration that work. UAVs facilitate rapid deployment, enabling data collection near end-users, while delivering a more comprehensive and precise dataset compared to traditional camera-based methods. This study will provide effective technical support and decision-making assistance for future agricultural land planning.

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Publication Details

Journal
Asian Research Journal of Agriculture
Published
2024-11-20
DOI
https://doi.org/10.9734/arja/2024/v17i4598
Citations
2
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
1.20
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article

Precision Agriculture: UAV-Based Soil Mapping and Remote Sensing Applications

Yogesh A. Shaniware, Priya Pandey, Pranali G. Meshram, Gauri P. Bhondave et al.
2 citations
Asian Research Journal of Agriculture
Smart Agriculture and AI
1.20
article

Precision Agriculture: UAV-Based Soil Mapping and Remote Sensing Applications

Yogesh A. Shaniware, Priya Pandey, Pranali G. Meshram, Gauri P. Bhondave, Dnyaneshwari M. Zol
article en
2 citations

Abstract

Using Unmanned Aerial Vehicle (UAV) equipped with remote sensing cameras that measure the electromagnetic spectrum of light reflected back from the ground below, this technology does soil mapping and field analysis. The way that different elements reflect different light wavelengths can be used to identify them. Reams of data on those wavelengths are gathered by multispectral image sensors, which power sophisticated AI software that can identify even the smallest variations in the elemental composition of soil. There are numerous positives to soil mapping, including helping farmers choose the best crops, applying the right fertilizers, and scheduling irrigation. Soil mapping also makes it easier to create plans for soil conservation and restoration that work. UAVs facilitate rapid deployment, enabling data collection near end-users, while delivering a more comprehensive and precise dataset compared to traditional camera-based methods. This study will provide effective technical support and decision-making assistance for future agricultural land planning.

Asian Research Journal of AgricultureVol. 17(4)
Marathwada Agricultural University (IN), Mahatma Phule Krishi Vidyapeeth (IN)
Openalex Percentile: Top 16%
Smart Agriculture and AI
1.20
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