Remote Sensing Applications in Precision Agriculture
Summary
Remote sensing has transformed modern agriculture by enabling non-invasive, high-resolution monitoring of crop health, soil properties and environmental conditions across vast areas. Satellite platforms such as multispectral and synthetic aperture radar constellations offer routine mapping of soil moisture, nutrient status and biomass, while airborne and unmanned aerial vehicles (UAVs) equipped with multispectral and hyperspectral sensors deliver centimetre-scale insights into plant physiology. These observations support variable-rate fertilisation, targeted irrigation and early detection of pest and disease outbreaks. Advances in data fusion, cloud computing and machine-learning algorithms now allow integration of heterogeneous datasets, yielding dynamic prescription maps for optimised input use and reduced environmental impact. By linking remotely sensed indicators to yield forecasts and phenotypic traits, farmers and agronomists can tailor management practices in near real time, enhancing productivity and resilience under changing climatic conditions.
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Remote Sensing Applications in Precision Agriculture publication trend
The graph below shows the total number of articles in remote sensing applications in precision agriculture across all publications each year (not limited to Nature Index journals).
Technical terms
Vegetation Index: A numerical indicator derived from specific spectral bands to quantify plant health and biomass.
Multispectral Imaging: Acquisition of image data at a limited number of discrete spectral bands across the electromagnetic spectrum.
Hyperspectral Imaging: Collection of image data in hundreds of contiguous spectral bands, enabling detailed material discrimination.
Unmanned Aerial Vehicle (UAV): Remotely piloted aircraft carrying lightweight sensors for high-resolution aerial surveys.
Synthetic Aperture Radar (SAR): Active microwave remote sensing technique providing all-weather measurements of surface structure and moisture.
References
- Significant Remote Sensing Vegetation Indices: A Review of Developments and Applications. Journal of Sensors (2017).
- Hyperspectral Imaging: A Review on UAV-Based Sensors, Data Processing and Applications for Agriculture and Forestry. Remote Sensing (2017).
- A Review of Imaging Techniques for Plant Phenotyping. Sensors (2014).
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