A Review on UAV-Based Applications for Precision Agriculture

By Dimosthenis C. Tsouros, Stamatia Bibi, Panagiotis G. Sarigiannidis. Inf., 2019

1,020 citations recorded by the source corpus.

Emerging technologies such as Internet of Things (IoT) can provide significant potential in Smart Farming and Precision Agriculture applications, enabling the acquisition of real-time environmental data. IoT devices such as Unmanned Aerial Vehicles (UAVs) can be exploited in a variety of applications related to crops management, by capturing high spatial and temporal resolution images. These technologies are expected to revolutionize agriculture, enabling decision-making in days instead of weeks, promising significant reduction in cost and increase in the yield. Such decisions enable the effective application of farm inputs, supporting the four pillars of precision agriculture, i.e., apply the right practice, at the right place, at the right time and with the right quantity. However, the actual proliferation and exploitation of UAVs in Smart Farming has not been as robust as expected mainly due to the challenges confronted when selecting and deploying the relevant technologies, including the data acquisition and image processing methods. The main problem is that still there is no standardized workflow for the use of UAVs in such applications, as it is a relatively new area. In this article, we review the most recent applications of UAVs for Precision Agriculture. We discuss the most common applications, the types of UAVs exploited and then we focus on the data acquisition methods and technologies, appointing the benefits and drawbacks of each one. We also point out the most popular processing methods of aerial imagery and discuss the outcomes of each method and the potential applications of each one in the farming operations.

Subfields: Ecology, Environmental Engineering, Plant Science

View Paper: https://www.semanticscholar.org/paper/334af19ed84ac8aed01c9d2b58e3a1ded81c2b84

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. Madhusanka Liyanage
2. Spyros Fountas
3. Shen Wang
4. Athanasios Balafoutis
5. Patrick McEnroe

In Environmental Engineering

1. Madhusanka Liyanage
2. Shen Wang
3. Patrick McEnroe

In Plant Science

1. Madhusanka Liyanage
2. Shen Wang
3. Athanasios Balafoutis
4. Patrick McEnroe

Citations in the corpus

• A Survey on the Convergence of Edge Computing and AI for UAVs: Opportunities and Challenges (2022, methodology): “According to Tsouros et al. [147], the most common UAV precision agri-culture applications in the literature are: “weed mapping and management,” “vegetation growth monitoring and yield estimation,” “vegetation health monitoring and disease detection,” “irrigation management,” and “crop spraying.””
• Smart Farming Technology Trends: Economic and Environmental Effects, Labor Impact, and Adoption Readiness (2020, background): “These include variable rate applicators [15–17], Internet of things (IoT) [18,19], geo‐positioning systems [20,21], big data [22–24], unmanned aerial vehicles (UAVs, drones) [18,25], automated systems, and robotics [26,27].”