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Methods and Applications of 3D Ground Crop Analysis Using LiDAR Technology: A Survey.
Matias J Micheletto1, Carlos I Chesñevar2, Rodrigo Santos3
1Golfo San Jorge Research and Transfer Center (CIT-GSJ), CONICET, Comodoro Rivadavia 9000, Argentina.
Sensors (Basel, Switzerland)
|August 26, 2023
Summary
Light Detection and Ranging (LiDAR) provides accurate 3D crop data for agriculture. Current methods require calibration for multi-species applications, highlighting a need for adaptable LiDAR technology.
Area of Science:
- Agricultural Science
- Remote Sensing Technology
- Geospatial Analysis
Background:
- Light Detection and Ranging (LiDAR) is a key non-destructive technology for precise agricultural data collection.
- 3D models generated by LiDAR enable rapid measurement of critical crop parameters like biomass and yield.
- LiDAR applications in agriculture have expanded significantly, covering phenotyping to robotic control.
Purpose of the Study:
- To systematically review and analyze research papers utilizing LiDAR for 3D ground crop analysis.
- To classify studies based on application areas, crop types, LiDAR systems, and data processing tools.
- To identify trends, limitations, and future directions in LiDAR technology for precision agriculture.
Main Methods:
- Systematic literature review of 53 research papers published between 2005 and 2022.
- Classification of studies based on application domains, crop species, LiDAR scanner types, and mounting platforms.
- Analysis of integrated instrumentation and software tools used in conjunction with LiDAR.
Main Results:
- Identified a hierarchy of LiDAR scanning platforms and their usage frequency in agricultural research.
- Established a correlation between the economic investment in LiDAR deployment and the quality of agronomic data obtained.
- Observed a lack of universal configurations for multi-species crop analysis using LiDAR.
Conclusions:
- LiDAR technology offers significant potential for enhancing precision agriculture through detailed 3D crop analysis.
- The cost-benefit analysis of LiDAR deployment varies, influencing its adoption rate.
- Future research should focus on developing adaptable LiDAR systems and algorithms for effective multi-species crop management and calibration.
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