Open Access

REVIEW

3D LiDAR-Based Techniques and Cost-Effective Measures for Precision Agriculture: A Review

Mukesh Kumar Verma^1,2,*, Manohar Yadav¹

1 Geographic Information System (GIS) Cell, Motilal Nehru National Institute of Technology, Allahabad, Prayagraj, 211004, Uttar Pradesh, India
2 AIT-CSE (AIML), Chandigarh University, Mohali, 140413, Punjab, India

* Corresponding Author: Mukesh Kumar Verma. Email:

(This article belongs to the Special Issue: Progress, Challenges, and Opportunities in GIS 3D Modeling and UAV Remote Sensing)

Revue Internationale de Géomatique 2025, 34, 855-879. https://doi.org/10.32604/rig.2025.069914

Received 03 July 2025; Accepted 20 October 2025; Issue published 17 November 2025

Abstract

Precision Agriculture (PA) is revolutionizing modern farming by leveraging remote sensing (RS) technologies for continuous, non-destructive crop monitoring. This review comprehensively explores RS systems categorized by platform—terrestrial, airborne, and space-borne—and evaluates the role of multi-sensor fusion in addressing the spatial and temporal complexity of agricultural environments. Emphasis is placed on data from LiDAR, GNSS, cameras, and radar, alongside derived metrics such as plant height, projected leaf area, and biomass. The study also highlights the significance of data processing methods, particularly machine learning (ML) and deep learning (DL), in extracting actionable insights from large datasets. By analyzing the trade-offs between sensor resolution, cost, and application, this paper provides a roadmap for implementing PA technologies. Challenges related to sensor integration, affordability, and technical expertise are also discussed, promoting the development of cost-effective, scalable solutions for sustainable agriculture.

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Keywords

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