Remote Sensing in Precision Agriculture
Remote Sensors
Sensors come in various types, including visible light (RGB) sensors, multispectral sensors, hyperspectral sensors, light detection and ranging (LiDAR) sensors, and thermal sensors, each designed to gather specific information. RGB sensors are commonly used to capture visible light images, suitable for general imaging purposes. Multispectral sensors capture light in multiple bands beyond the visible spectrum, typically including near-infrared (NIR). Hyperspectral sensors capture hundreds or even thousands of narrow wavelength bands, providing a more detailed spectral profile. LiDAR measures laser pulses to measure distances and create 3D models of the Earth’s surface. Thermal infrared detects infrared radiation, facilitating tasks such as search and rescue or inspections. Table 6.3 outlines the strengths and weaknesses of commonly used imaging sensors. Understanding these trade-offs is essential for selecting the most suitable imaging sensor based on the specific requirements of the application.
- RGB Remote Sensing
- Multispectral Remote Sensing
- Hyperspectral Remote Sensing
- Thermal Remote Sensing
- Microwave Remote Sensing
- Synthetic Aperture Radar Remote Sensing
- Interferometric Synthetic Aperture Radar Remote Sensing
- LiDAR Remote Sensing
- Structured Light Remote Sensing
- Structure from Motion Remote Sensing
Click on the following topics for more information on remote rensing in precision agriculture.
Topics Within This Chapter:
- Introduction to Greenhouse Environmental Monitoring and Control
- Advantages and Limitations of Remote Sensing
- Fundamentals of Remote Sensing
- Image Resolution In Remote Sensing
- Remote Sensors
- Point Cloud
- Remote Sensing Platforms
- Remote Image Processing and Data Analysis
- Remote Sensing Applications in Precision Agriculture

