M4L10: Hyper Spectral Imaging (HySPex)

The Space vision 2025, proposed by A.P.J. Abdul Kalam, presents a roadmap for the Indian Space Industry ISRO. In his vision, he has specifically emphasized on improvement of imaging capabilities of ISRO.

Remote sensing is based on the measurement of reflected or emitted radiation from different bodies. Objects having different surface features reflect or absorb the sun's radiation in different ways (known as albedo). The reflectance properties of an object depend on the particular material and its physical and chemical state (e.g. moisture), the surface roughness as well as the geometric circumstances (e.g. incidence angle of the sunlight).

This reflected energy can be in the form of UV, Visible band or Infra-Red. This individual reflected bands can be detected &used to identify the object on earth’ surface. Since, each and every object has its own chemical composition, it has its own spectral signature.

Hyperspectral imagery consists of spectral imaging in narrower bands (10-20 nm). A hyperspectral image collects digital data by imaging in hundreds or thousands of such narrow bands. Having a higher level of spectral detail in hyperspectral images gives better capability to see the unseen.

For example, in mineral exploration, there are over 4000 different types of minerals. Each mineral has its own composition. hyperspectral remote sensing helps us to distinguish between most of the types of minerals based on their spectral signature. It can also be used to map invasive species& this technique has already been used by NASA & ISRO to restore the ecology of Chilka lake. (Fortunately, now because of these reasons, Chilka lake is out of Montreaux Records)

This technique can also be used in the fields of agriculture, ecology, oil and gas, oceanography and atmospheric studies.

There are many applications which can take advantage of hyperspectral remote sensing.

Atmosphere: water vapor, cloud properties, aerosols

Ecology: chlorophyll, leaf water, cellulose, pigmemts, lignin

Geology: mineral and soil types

Coastal Waters: chlorophyll, phytoplankton, dissolved organic materials, suspended sediments

Snow/Ice: snow cover fraction, grainsize, melting

Biomass Burning: subpixel temperatures, smoke

Commercial: mineral exploration, agriculture and forest production

Hyper Spectral Imaging	Multi Spectral Imaging
Pseudo-continuous spectrum (100s of wavelengths)	Several discrete wavelengths (typically 3-10)
Greater flexibility and resolution	(Fixed) wavelengths selected according to specific application
1-10 frames per second image capture	Faster data acquisition (30 frames per second)
Higher cost and complexity	Lower cost, increased robustness
More data processing required	Reduced data processing requirements
Better suited as a research/science tool	Well-suited to repetitive, production/industrial applications

An example of a multispectral sensor is Landsat-8. Landsat-8 produces 11 images of the same location with the following bands: 1.    Coastal aerosol in band 1 (0.43-0.45 um) 2.    Blue in band 2 (0.45-0.51 um) 3.    Green in band 3 (0.53-0.59 um) 4.    Red in band 4 (0.64-0.67 um) 5.    Near infrared NIR in band 5 (0.85-0.88 um) 6.    Short-wave Infrared SWIR 1 in band 6 (1.57-1.65 um) 7.    Short-wave Infrared SWIR 2 in band 7 (2.11-2.29 um) 8.    Panchromatic in band 8 (0.50-0.68 um) 9.    Cirrus in band 9 (1.36-1.38 um) 10. Thermal Infrared TIRS 1 in band 10 (10.60-11.19 um) 11. Thermal Infrared TIRS 2 in band 11 (11.50-12.51 um) Coastal Aerosol (0.43-0.45μm) band can penetrate clean waters upto 20-30 meters. Therefore, it is used for counting whale populations from, submarine vegetation like seagrass and another underwater benthic habitat. Blue (0.45-0.51μm) colour is used for deep water imaging of ocean floor, underwater reefs, water turbidity and sediment, submerged aquatic vegetation, turbidity and bathymetric mapping makes for some unique remote sensing applications. Green (0.53-0.59μm) to know the presence of plants, trees and forest. It is also used to study algal and cyanobacterial blooms & urban recreation areas like parks, golf courses and cemeteries. Red (0.64-0.67μm) to identify Tropical soils, watershed delineation, for discriminating between man-made objects and vegetation. Yellow (0.585-0.625μm) to identify tree disease, loss of tree crowns lost by insect diseases, stressed plants and manganese-deficient leaves, to delineate invasive grass and other general features. It’s also been used to classify individual tree species and crop types by season. Red-Edge (0.705-0.745μm) band is between the near infrared and red band. It is used to study the crop conditions, plant health status and age, monitoring crop growth in precision farming and even discriminating between healthy and crops impacted by disease. It’s been used to distinguish between crop types and nutrition. Near Infrared 1 – NIR-1 (0.76-0.90μm) is used to classify healthy vegetation from water cover, because in the near infrared spectrum, healthy plants reflect, while it is absorbed more by water. It is also used for mapping of biodiversity, vegetation health and biomass content, unearthing of ancient archaeological sites by interpreting denser mud bricks, crop marks and subtle differences in vegetation, soil, and geology from near-infrared radiation. Near Infrared 2 – NIR-2 (0.86-1.04μm) for more sophisticated vegetation analysis and biomass studies primarily because it’s less impacted by the atmosphere. It is used to identify boundaries between land and water since water is a strong absorber of near infrared light, while vegetation is a strong reflector. Thermal Infrared – TIRS-1 (10.60–12.51μm) band sees heat. This can be used to identify Volcano Activity, Volcano Monitoring, Urban Heat Generation, Weather Prediction. Short-wave Infrared 1 – SWIR-1 (1.57-1.65μm) to discriminate between dry and wet soils. It’s used in the spectral signature for geology and soils classification like mineral deposits, exploration & mining, moisture content etc. SWIR is known for its ability to penetrate thin clouds, and even smoke and haze better than visible bands & therefore it helps to detect forest fires more effectively. Short-wave Infrared 2 – SWIR-2 (2.08-2.35μm) used for imaging soil types, geological features and minerals such as copper and sulfates. It’s also sensitive to vegetation and soil moisture variations. Snow and ice feature and clouds appear darker toned. It is used to know the availability of clean water, understanding crop water stress and targeting irrigation in areas of drought. Panchromatic (0.50-0.68μm) shows image just like black and white film. It is used to sharpen images with boundaries & contours, identified by the panchromatic band. Cirrus (1.36 -1.38μm) to detect high-altitude clouds (Cirrus Clouds).