A comprehensive review of remote sensing platforms, sensors, and applications in nut crops

Background: Due to their high protein content, nuts (almond, walnut, and pistachio) are among the main substitutes for meat, with a growing share of the food basket in the United States. However, the rapidly growing acreage of these crops, new legislations, the necessity of minimizing the environmental footprint, and a costeffective production demand certain managerial practices based on precision agriculture and remote sensing, which have shown promising results in food production. Scope and approach: This paper presents a comprehensive review of remote sensing platforms, sensors, applications, and analytic pipelines with a focus on nut crops, even though the materials are applicable for other specialty crops. In this regard, the paper is divided into five main sections: First, the problems and potential solutions are elaborated in the introduction. Second, the available platforms: satellites, manned aircraft, and UASs are discussed. Then the sensors used for remote sensing, their working principle, and the pros and cons of each are presented. Next, practiced and suggested applications of remote sensing data are reviewed. Finally, data processing and analytics needed to produce and interpret reliable results are highlighted.Key findings and conclusions: Key findings are listed as: 1) The acreage of the nut orchards and the purpose of the studies determine the fitting sensor and platform. 2) Although various sensors are available and reported to have promising results in other crops, they have not been used for nut crops. 3) Accurate sensor calibration is crucial for repeatable results as well as temporal and inter-field comparisons. 4) Except for water management, most remote sensing applications are limitedly studied in nut orchards, creating some research opportunities. 5) Finally, increasing data size requires new machine learning techniques and data fusion frameworks to handle all variables and fill the knowledge gap.

Automated summary

This paper provides a comprehensive review of remote sensing platforms, sensors, applications, and analytic pipelines in the context of nut crops. The findings suggest that the choice of sensor and platform depends on the acreage and purpose of the nut orchards. While various sensors have shown promising results in other crops, they have not been extensively used for nut crops. Accurate sensor calibration is crucial for obtaining repeatable results and enabling temporal and inter-field comparisons. Most remote sensing applications in nut orchards are limited, except for water management, presenting research opportunities. The increasing data size requires the adoption of new machine learning techniques and data fusion frameworks to handle all variables and fill the knowledge gap.