Thermal imaging can be used in all fields where temperature differences help analyse an area or an object. It is a relatively new technology in agriculture, but it is quickly gaining popularity. As the cost of thermal cameras continues to decrease, and as more farmers become aware of the benefits of thermal imaging, it is likely to become an essential tool for many farmers in the future.

When used in agriculture, it helps a lot in plant disease detection, yield estimation, evaluating the maturity of the crop, water stress estimation, irrigation scheduling, as well as fertilization planning.

Currently, there is not much work being done in the field of combining thermal and multispectral images through machine learning. However, the fact is that by using both technologies, more comprehensive data can be obtained, and potential errors that may arise from using only one technology can be identified.

Nevertheless, for more complex research, both thermal and multispectral imaging are used seamlessly, and the gathered information, especially for thermal, is processed manually.