Crop Monitoring using Unmanned Aerial Vehicles: A Review

Cuaran, Jose; Leon, Jose Leon

doi:10.18805/ag.r-180

Cited by 28 publications

(17 citation statements)

References 46 publications

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“…Collecting real-time data helps farmers to immediately evaluate and react to environmental events. The final results include reduced operating costs, improved crop quality, and increased yield rates (4). Therefore, the selection of sensors is one of the fundamental building blocks of real-time RS (5).…”

Section: Introductionmentioning

confidence: 99%

Preliminary Approach for UAV-Based Multi-Sensor Platforms for Reconnaissance and Surveillance applications

Amézquita-Gómez,

González-Bautista,

Teran

et al. 2023

Ing.

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Context: Unmanned Aerial Vehicles (UAVs) equipped with remote sensing platforms have become increasingly popular due to their applications in aerial surveillance, environmental control, and disaster response. However, the limited flight range and on-board energy resources of UAVs pose significant challenges to their practical deployment and operating efficiency, which has led to the exploration of energy-efficient platforms for remote sensing. Method: This paper proposes a preliminary approach for UAV multi-sensor reconnaissance and surveillance platforms (MRSS) that target low energy consumption. The approach implemented four sensor modules controlled by one multi-functional integrated edge computer for control and data collection, which can be interchanged according to battery lifetime requirements. Results: The main contribution of this work was an analysis of the energy consumption behavior of sensor modules managed by an embedded system with edge computing capabilities as the central control unit. Conclusions: The high energy consumption associated with modules such as GEOINT leads to deep discharge in excess of 20 % DOD, resulting in a maximum battery degradation of 2,4 years.

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Section: Introductionmentioning

confidence: 99%

Preliminary Approach for UAV-Based Multi-Sensor Platforms for Reconnaissance and Surveillance applications

Amézquita-Gómez,

González-Bautista,

Teran

et al. 2023

Ing.

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“…In contrast, unmanned aerial vehicles (UAVs), due to their flexibility and low-altitude flight capability, have quickly become an ideal tool for the precision monitoring of crops [7,8] . UAV-based low-altitude remote sensing platforms can obtain images with very high temporal and spatial resolution that are free from atmospheric interference [9][10][11] . Akash et al [12] developed a machine learning framework for estimating cotton yields using multitemporal remote sensing data collected with unmanned aerial systems (UASs), and obtained more reliable crop yield estimates.…”

Section: Introductionmentioning

confidence: 99%

Yield Estimation of High-Density Cotton Fields Using Low-Altitude UAV Imaging and Deep Learning

Bai

Zhang

et al. 2022

Preprint

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Background: Different from other parts of the world, China has its own cotton planting pattern. Cotton are densely planted in wide-narrow rows to increase yield in Xinjiang, China, causing the difficulty in the accurate evaluation of cotton yields using remote sensing in such field with branches occluded and overlapped. Results: In this study, low-altitude unmanned aerial vehicle (UAV) imaging and deep convolutional neural networks (DCNN) were used to estimate the yields of densely planted cotton. Images of cotton field were acquired by an UAV at the height of 5 m. Cotton bolls were manually harvested and weighted afterwards. Then, a modified DCNN model was developed by applying encoder-decoder recombination and dilated convolution for pixel-wise cotton boll segmentation termed CD-SegNet. Linear regression analysis was employed to build up the relationship between cotton boll pixels ratio and cotton yield. Yield estimations of four cotton fields were verified after machine harvest and weighting. The results showed that CD-SegNet outperformed the other tested models including SegNet, support vector machine (SVM), and random forest (RF). The average error of the estimated yield of the cotton fields was 6.2%. Conclusions: Overall, the yield estimation of densely planted cotton based on lowaltitude UAV imaging is feasible. This study provides a methodological reference for cotton yield estimation in China.

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“…Unmanned aerial vehicles (UAVs) or drones have been developed significantly over the past two decades, for a wide variety of applications such as surveillance, geographic studies, fire monitoring, security, military applications, search and rescue, agriculture, etc. In agriculture, for example, remote sensing by means of unmanned aerial vehicles has proven to be the most efficient way to monitor crops from images (Cuaran and Leon, 2021).…”

Section: Introductionmentioning

confidence: 99%

Advancement of Agricultural Technology in Farming of India

Sharma¹,

Devadas²,

Sharma³

et al. 2022

BKAP

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Background: Agricultural technology is an innovated, invented and discovered material that assists people and the country for improving production and productivity. Conventional agricultural technologies were practiced in the country in sustainable agriculture. A large number of inventions from several research and development projects were evolved and discovered that help in boosting transformation of sustainable agriculture into modern agriculture. Methods: The agriculture technology is currently utilized in the dairy farming, poultry farming and organic farming. The working principles of agriculture technology were glanced from the dairy farming, poultry farming and organic farming and collected from the Andhra Pradesh, Karnataka, Maharashtra, Punjab and Gujarat. Result: The control of fly, milking parlours, calf care, young stock housing, hygiene, milk testing technologies etc are currently utilized into the dairy farming in rural India. The robots carries out ding dirty work, flock protection using drones and use of sensors for monitoring and management are applied in the poultry animals. The Information and Communication Technology (ICT) contributes at production and management in dairy farming and poultry farming. It imposes crop development and management and sprays adequate organic chemicals in the crop field. The effective and less expensive technologies like neem based preparations, concentrated organic manure, organic formulations for seed treatment and plant protection, broad-spectrum botanical pesticides and many more have been developed that promote organic agriculture.

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Crop Monitoring using Unmanned Aerial Vehicles: A Review

Cited by 28 publications

References 46 publications

Preliminary Approach for UAV-Based Multi-Sensor Platforms for Reconnaissance and Surveillance applications

Preliminary Approach for UAV-Based Multi-Sensor Platforms for Reconnaissance and Surveillance applications

Yield Estimation of High-Density Cotton Fields Using Low-Altitude UAV Imaging and Deep Learning

Advancement of Agricultural Technology in Farming of India

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