Skip to main content Skip to navigation

Unmanned Aerial Systems in Agriculture: Part 2 (Sensors)

Unmanned Aerial Systems in Agriculture: Part 2 (Sensors)

FS285E
Download PDF
Lav Khot, Automation Engineering, Department of Biological Systems Engineering
Sensors play a critical role in meaningful use of small unmanned aerial systems (UAS) in agriculture. Sensor types and pertinent specifications govern quality of data available for either the overall crop scouting or for more specific biotic and abiotic crop stressors detection. This publication describes the types and suitable uses of specific sensors in agricultural applications. Discussed are also issues with form factor, payload capabilities, and data analytics that may influence the sensor selection being integrated with small UAS.
Section 3 Lorem ipsum dolor sit amet, consectetur adipiscing elit. Mauris sit amet pulvinar massa, vel suscipit turpis. Vestibulum sollicitudin felis sit amet mi luctus, sed malesuada nibh ultricies. Nam sit amet accumsan dui, vitae placerat tortor. Vestibulum facilisis fermentum dignissim. Maecenas ultrices cursus diam, eu volutpat urna viverra non.

Page:

...

Introduction

Traditional crop scouting methods (e.g., visual scouting, field sampling and laboratory analysis) are not rapid especially when conditions affecting the crop are too complicated to be identified using these techniques. Advanced sensor technologies can help in such scenarios.

A sensor is “a device that responds to a physical stimulus such as heat, light, sound, pressure, magnetism, or a particular motion, and transmits a resulting impulse for measurement or operating a control” (Merriam-Webster 2017). Typically, sensor data can be used to detect early signs of biotic (biological in nature) or abiotic (water, solar radiation, temperature, air quality) crop stress. When combined with various sampling methods (i.e., ground or aerial), sensor-extracted data can be useful to farmers for monitoring plant growth and health. It can also help in potential crop yield estimation.

The emergence of unmanned aerial systems (UAS) has enhanced possibilities of acquiring high-resolution multi-spectral (i.e., few spectral bands) images of agricultural fields at a temporal resolution controlled by the user. It can lead to easier and faster monitoring of large farms and agricultural decision making. UAS have evolved into an important technology in precision agriculture with multiple companies and agricultural service providers exploring how to integrate it into production management decision making. Sensors are an integral part of UAS technology for its meaningful and efficient use in agriculture.

Today, a wide range of optical imaging systems are available which can be integrated with UAS. In general, optical sensors are classified based on the form of data acquired and source of electromagnetic radiation (EM) used to measure the response. Spectrometric or imaging sensors can capture spectral and spatial data about an object (e.g., plant canopy) in the EM radiation ranging from about 300 nm to 30 cm. For example, a simple point-and-shoot digital camera captures EM reflectance from the field-of-view (FOV) in red (650 nm), green (510 nm), and blue (475 nm) bands to form a color image. Time-of-Flight (ToF) sensors capture the time taken for the signals to reach an object and provide point cloud time series data describing the object features.

Sensors that capture and record natural EM radiation coming from the sun and reflected from the objects are termed as passive sensors. Most optical sensors used in agricultural remote sensing often are of passive type. Active sensors are integrated with specific energy source to illuminate the object and record the response. For example, the light detection and ranging (LiDAR) and ultrasonic sensors, respectively, use infrared light and short sound pulses as energy sources to capture ToF data. For example, a LiDAR sensor (from SICK Inc., Germany) emits infrared light (905 nm) in the sensor FOV and measures the response as reflected light intensity with distance.

A range of active and passive sensors can be integrated with small UAS. Georeferenced and processed data from such sensors can be used for decision support in crop management. Overall, the integration of a typical sensor with a small UAS depends on the specific agricultural application and the UAS platform payload lift capabilities. The section on Sensor Types summarizes some of the key sensors that can be integrated with small UAS for agricultural crop sensing.

Page:

...

Copyright Washington State University

WSU Extension bulletins contain material written and produced for public distribution. Alternate formats of our educational materials are available upon request for persons with disabilities. Please contact Washington State University Extension for more information

Issued by Washington State University Extension and the U.S. Department of Agriculture in furtherance of the Acts of May 8 and June 30, 1914. Extension programs and policies are consistent with federal and state laws and regulations on nondiscrimination regarding race, sex, religion, age, color, creed, and national or ethnic origin; physical, mental, or sensory disability; marital status or sexual orientation; and status as a Vietnam-era or disabled veteran. Evidence of noncompliance may be reported through your local WSU Extension office. Trade names have been used to simplify information; no endorsement is intended.