Remote sensing techniques are changing very fast and undergoing a lot of advancements. Newer and advanced techniques are being introduced. Hyperspectral Remote Sensing is one of these techniques proving worth for various studies like environment, agriculture geology etc.
Hyperspectral remote sensing involves acquisition of the digital images in many, narrow, contiguous spectral bands throughout the visible, Near Infrared (NIR) , Mid-Infrared (MIR) and Thermal Infrared (TIR) regions of the electromagnetic spectrum.
Higher spectral resolution enables hyperspectral remote sensing instruments capable of detailed identification of material, geological features and vegetation at finer level, which is not possible with conventional multispectral remote sensors.
The multispectral satellite sensors contain less number of bands with broad spectral band width hence these are not capable of detecting fine details of the earth features being sensed. The broad band width cannot separate the objects having very little difference in their spectral reflectance. For instance if we talk about vegetation studies there are many plant species and vegetation classes, which possess almost similar spectral properties and hence these seem to fall in same class or seem to belong to same species. Such misinterpretation of the data leads to erroneous results thus creating limitations for multispectral sensors to work at micro level. Also, these sensors cannot detect very little changes in the moisture and chlorophyll content of the leaves.
On the other hand, Hyperspectral Imaging (HSI) instruments, possessing narrow large number of bands, make it possible to differentiate between the objects/features which may look similar in multispectral sensors. HSI can afford the detection of small alterations in the moisture content of the leaves, moisture status of soil, nutrient stress and other environmental stresses in the plants. The narrow bandwidth allows HSI to discriminate between the plant species and vegetation types having very small difference in the spectral reflectance.
Hyperspectral remote sensing is becoming popular among botanists, plant biochemists environmentalists, agriculturists and geologists. It is proving to be a good tool for studying plant physiology, canopy biochemistry, plant productivity, biomass, detecting health of the plants and for vegetation mapping.
This recent technique of remote sensing generates a large volume of data hence requires a lot of space to store it. Hyperspectral image processing is different from multipsectral one hence it requires special tools for processing and analysis.Also a lot of expertise and skills are needed for interpreting data acquired from HSI instruments correctly and for getting desired results.
Some of the Hyperspectral Remote Sensing systems are as follows:
Airborne Visible Infrared Imaging Spectrometer (AVIRIS)
AVIRIS acquires images in 224 spectral bands which are 9.6 nm wide. The range of these bands is in between 400nm to 2500 nm region of electromagnetic spectrum.
Compact Airborne Spectrographic Imager (CASI)
This imaging spectrometer collects data in 288 bands in the range between 400nm to 1000nm. The spectral interval of each band is 1.8nm.
Hyperspectral Mapping (HYMAP) System
It is an across-track hyperspectral imaging instrument. It collects data in 128 bands in the range of 400-2500nm.
Moderate Resolution Imaging Spectrometer (MODIS)
This hyperspectral imaging sensor is one of the sensors on TERRA satellite. It acquire data in 36 spectral bands and its spatial resolution ranges between 250m to 1 km (to be precise- Band 1 & 2 : 250m x 250m, Band 3 to 7 : 500m x 500m and Band 8 to 36 : 1km x 1km.)