Abstract
In thermal remote sensing the invisible radiation patterns of objects are converted into visible images and these images are called thermograms or thermal images. Thermal images can be acquired using portable, hand-held or thermal sensors that are coupled with optical systems mounted on an airplane or satellite. This technology is a non-invasive, non-contact and non-destructive technique used to determine thermal properties and features of any object of interest and therefore it can be used in many fields, where heat is generated or lost in space and time. Potential use of thermal remote sensing in agriculture includes nursery and greenhouse monitoring, irrigation scheduling, plants disease detection, estimating fruit yield, evaluating maturity of fruits and bruise detection in fruits and vegetables. This paper reviews the application of thermal imaging in agriculture and its potential use in various agricultural practices.
Highlights
Thermal remote sensing is the branch of remote sensing that deals with the acquisition, processing and interpretation of data acquired primarily in the thermal infrared (TIR) region of the electromagnetic (EM) spectrum [1]
The purpose of this paper is to review the different thermal sensors that can be used in agriculture as well as summarize various studies conducted on the potential application of thermal imaging in agriculture
Researches combine thermal remote sensing with other methods to access crop water stress and irrigation scheduling. [54] developed an algorithm that can assess automatically canopy temperature by aligning an optical image taken from the plant canopy with the IR image, from simple color identification techniques in combination with Gaussian mixture distribution extraction techniques and based on measurement of data acquired from an IR thermography they were able to extract successfully and automatically the canopy temperature distribution of the leaf
Summary
Thermal remote sensing is the branch of remote sensing that deals with the acquisition, processing and interpretation of data acquired primarily in the thermal infrared (TIR) region of the electromagnetic (EM) spectrum [1]. Thermal wavelength region in terrestrial remote sensing ranges from 3 to 35 μm but interpretation of the data in 3 - 5 μm is complicated due to overlap with solar reflection in day imagery and 17 - 25 μm regions are still not well investigated. Thermal remote sensing exploits the fact that everything above absolute zero (0 K or −273.15 ̊C or −459 ̊F) emits radiation in the infrared range of the electromagnetic spectrum [1] approximately 80% of the energy thermal sensors received in the thermal wavelength region is emitted by land surface, making surface temperature as the easiest variable to extract from the thermal infrared signal [4]. Thermal imaging data may be used directly or indirectly for many applications such as civil engineering, industrial maintenance, aerospace, medicine, pharmacy and veterinary. The application of thermal imaging is gaining popularity in agriculture in recent years [6] due to the reductions in cost of the equipment and simple operational procedure that have created opportunities for its application in several fields of agricultural and food industries [7] and it is presently refined for integration into precision farming [8]
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