Field documentation is valuable for analyzing the farming practices and planning the next cropping cycle. Aerial photos can document information about the field and crop conditions throughout the season. Some natural events, like drought, storm, or hail, might damage crops, and drone images can be vital records that can be used for insurance claims. Similarly, reviewing the images helps us understand what management practices produced the best crops and what went wrong in the field. This information allows growers to plan for the upcoming cropping cycle.
Drones carry various cameras/sensors that capture multiple images of the field from numerous angles. Those images provide different information about the standing crop and field conditions.
The RGB camera captures what regular cell phone cameras capture and what our eyes see. Normal cameras and naked eyes can visualize obvious issues in the field, like moisture condition, disease and pest damage, but some stresses are not visible in RGB images until they become severe. However, several indices can be derived using multiple band information (Red, Green, Blue) in the RGB images which can provide crop health status. RGB cameras are the most affordable and easy to process for field scouting. Moreover, those indices can also help visualize and quantify stress across the field.
Multispectral sensors capture images that our regular camera and naked eyes cannot see (usually red-edge wavelength and near-infrared). The vegetation index map is generated using the amount of light absorbed or reflected in a particular bandwidth by the plants. Normalized Difference Vegetation Index (NDVI) is the most popular to visualize crop health status. Generally, healthy crops reflect NIR light, giving higher NDVI values (closer to 1), whereas stressed crops reflect less, giving lower NDVI values (Burgman & Murphy, 2021). The NDVI map generally represents higher NDVI in greener colors; lower values are shown in yellow to red. Farmers can detect early stress from nutrients, pests, and weeds using such indices maps.
A thermal camera on a drone can capture the temperature difference across the field. In the field, some areas with less water have stressed plants with warmer canopies because the cooling effect through evaporation is reduced compared to healthy, well-watered plants (Thompson et al., 2018). Using this information, a drone can help locate drought-prone and disease and insect infested areas. Farmers can use a field map derived from a thermal camera for appropriate field intervention.
LiDAR is the most advanced and expensive sensor that provides an accurate vertical crop structure. It is most helpful in studying plant height, biomass, and terrain variations (Pun Magar et al., 2025). However, it is a complex technology and requires high storage capacity and expertise to handle the huge volume of datasets.
Figure 1: RGB Ortho mosaic showing field condition.
Figure 2: Field patches indicating stress.
Figure 3: RGB-based indices showing vegetation health.
Figure 4: NDVI generated using multispectral sensor showing crop growth status.
Figure 5: LiDAR point clouds above the field are useful for providing information about field elevation and crop height.
Crop Scouting with Aerial Imagery – Choosing the Right Source | Integrated Crop Management. (2021). Retrieved April 29, 2025, from https://crops.extension.iastate.edu/post/crop-scouting-aerial-imagery-choosing-right-source.
Getting Started with Drones in Agriculture, NebGuide Nebraska Extension. (2017).
Pun Magar, L., Sandifer, J., Khatri, D., Poudel, S., KC, S., Gyawali, B., Gebremedhin, M., & Chiluwal, A. (2025). Plant height measurement using UAV-based aerial RGB and LiDAR images in soybean. Frontiers in Plant Science, 16. https://doi.org/10.3389/fpls.2025.1488760