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Chapter 6

Remote Sensing in Precision Agriculture

(book excerpts)

Remote sensing can be understood as the technique that uses sensors, without direct contact with the object of interest, to obtain information by capturing its reflected and/or emitted electromagnetic radiation. For this, a remote sensing system consists of a source of electromagnetic radiation (e.g., the sun), a terrestrial target (vegetation, water bodies, soil, etc.), a platform that carries sensors (e.g., satellites, aircraft, or drones), and a site of data processing, storage, and distribution. Remote sensing in agriculture utilizes various technologies, like satellites and drones, to gather information about crops, soil, and other agricultural factors from a distance. This data helps farmers and agricultural professionals make informed decisions regarding irrigation, fertilization, pest control, and other aspects of farming. Remote sensing allows for efficient and precise management of resources, leading to improved crop yields and more sustainable farming practices. Remote sensing in agriculture uses various platforms to gather information about crops and soil from a distance. These platforms include satellites, aircraft, and drones, each offering unique advantages and disadvantages for collecting data on crop health, soil conditions, and other relevant factors. Remote sensing in agriculture uses various types of sensors (e.g., optical, multispectral, hyperspectral, LiDAR, etc.) to gather information about crops and fields from a distance without physical contact. This technology plays a critical role in modern farming practices, enabling farmers to make informed decisions about crop management and resource allocation. Sensors used for remote sensing differ based on the spatial, spectral, radiometric, and temporal resolution they offer. Sensors mounted on satellites, airplanes, and UAVs are generally passive sensors, i.e., they do not have their own light source. Remotely sensed imagery can be used for mapping soil properties, classification of crop species, detection of crop water stress, monitoring of weeds and crop diseases, and mapping of crop yield. In precision agriculture, remote sensing technology facilitates the dividing of large fields into smaller management zones. Each zone aggregates specific crop management needs and production limitations. These divisions are accomplished mainly based on (1) soil characteristics such as soil types, soil pH, soil EC, soil moisture content, nutrient availability, and soil compaction and (2) crop characteristics such as crop canopy and density, insect and disease infestations, fertility requirements, hybrid responses, and crop stress. Observations made using remote sensing technology undergo digital image processing and are geo-referenced within a geographical information software (GIS) database. Remote sensing and ground-based proximal sensing are related but not the same. They involve collecting information about something without direct contact, but they differ mainly in distance and application.

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Table of Contents
Introduction
Precision Agriculture in Crop Production
Internet of Things in Precision Agriculture
Artificial Intelligence in Precision Agriculture
Wireless Sensor Networks in Precision Agriculture
Global Navigation Satellite System in Precision Agriculture
Remote Sensing in Precision Agriculture
Satellite Remote Sensing in Precision Agriculture
UAV Remote Sensing in Precision Agriculture
Ground-Based Sensing in Precision Agriculture
Spectral Reflectance of Crops and Soils
Yield Monitoring and Mapping in Precision Agriculture
Variable-Rate Technology in Precision Agriculture
Guidance and Steering Systems in Precision Agriculture
Robots in Precision Agriculture
Digital Image Processing of Remote-Sensed Data
Geographical Information Systems in Agriculture
Glossary
References
Index (PDF)

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