## 3 Application of Hyperspectral RS into Plant RS and Military Actions
### Military Application of Hyperspectral RS  
Because of unique advantages, hyperspectral RS target detection has received extensive attention and research in the military field [1, 70, 71, 72, 73]. The U.S. Naval Research Laboratory (NRL) hosted the development of the Hyperspectral Digital Image Collection Experimental Instrument (HYDICE) in 1991. This airborne push-type hyperspectral instrument with a spectral coverage range of 0.4-2.5 \(\upmu\)m can collect data from 210 bands at the spectral resolution of 10 nm. In 2005, with the support of the U.S. Department of Defense, HYDICE was used in the Forest Radiance I experiment and Desert Radiance II experiment. Late-stage data analysis showed hyperspectral RS images with strong ability to identify camouflage can distinguish real targets from decoy targets against the background of green vegetation and quickly detect small tactical targets against the desert background. The current military applications of hyperspectral RS mainly cover three aspects: detailed battlefield reconnaissance, identification of camouflaged targets, and detection and calculation of the target's true temperature and emissivity:  
* Detailed battlefield reconnaissance  
Hyperspectral RS instruments can detect targets simultaneously in continuous working bands and can directly reflect the fine spectral characteristics of the measured object. They can distinguish the composition and state of the target surface. The precise correspondence between space detection information and actual targets on the ground can be obtained. Israeli scientists used a CASI hyperspectral imaging spectrometer to study Tel Aviv, selecting typical features from CASI images as end-member data, and achieved good results on rivers, sand, road surfaces, vegetation, and other features [74]. The hyperspectral imager designed by the U.S. Navy can provide spectral data in 210 bands at 0.4-2.5 \(\upmu\)m and can obtain the dynamic characteristics of offshore environmental targets (e.g., seawater transparency, ocean depth, ocean currents, seafloor features, underwater dangerous objects, and oil leaks) to provide reference for naval offshore operations. The United States has proposed digital earth research, aiming to establish a database of the global surface at the square meter level, and they involved various parameters, including target and background characteristic spectra. After the database is established, military targets anywhere in the world will be monitored and susceptible to attack;
* Identifying camouflage target In terms of military target reconnaissance and camouflage identification, hyperspectral RS can detect military equipment according to the different spectral characteristics of the background and camouflage targets. Through the spectral characteristic curve, the composition of the target can be inverted to reveal the target and its camouflage that are different from the background environment. An important method for detecting green camouflage materials is to use the red-edge effect of vegetation, as the reflectivity of vegetation increases sharply at 680-720 nm. The type and status of vegetation can be identified by detecting the characteristics of its position and slope [75]. The spectral curve of the existing green camouflage materials can generally match with the vegetation and can meet the camouflage requirements under multi-spectral reconnaissance conditions. However, the camouflaged target cannot be hidden under the fine resolution of hyperspectral;
* Detecting and calculating the target's true temperature and emissivity In the current thermal infrared detection, [PERSON]'s law is used to combine the two unknown parameters of emissivity and temperature into one parameter [76], which is called hypothetical temperature or radiation temperature in radiation thermometry. It is assumed that temperature is the coupling between the real temperature and spectral emissivity and does not reflect the real temperature of the measured target.