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Hyper spectral Imaging Satellite (HysIS)

PSLV-C43 lifted off at 0957 hrs (IST) on November 29, 2018 from the First Launch Pad (FLP) of Satish Dhawan Space Centre SHAR, Sriharikota and successfully launched India’s Hyper spectral Imaging Satellite (HysIS) and 30 international co-passenger satellites. The hyper-spectral imaging satellite HysIS was the principal payload for the rocket PSLV-C43. This was the 68th launch mission for the national space agency ISRO from Sriharikota and the sixth one this year. For more number crunch, this was the second launch this month. The rocket PSLV put the satellite HysIS first at an altitude of about 637 kilometer.

HysIS, the primary satellite of PSLV-C43 mission, weighing about 380 kg, is an earth observation satellite configured around ISRO’s Mini Satellite-2 (IMS-2) bus. The primary goal of HysIS is to study the earth’s surface in the visible, near infrared and shortwave infrared regions of the electromagnetic spectrum. The co-passengers of HysIS include 1 Micro and 29 Nano satellites from 8 different countries. These satellites have been commercially contracted for launch through Antrix Corporation Limited, the commercial arm of ISRO.

Hyperspectral imaging or hyspex imaging (imaging spectroscopy) combines the power of digital imaging and spectroscopy. It collects and processes information from across the electromagnetic spectrum. Hyspex’ imaging enables distinct identification of objects, materials or processes on Earth by reading the spectrum for each pixel of a scene from space.

Isro officials said their endeavour is to enter the domain of operational hyperspectral imaging from earth orbit with a satellite that can see in 55 spectral or color bands from 630 km above ground. The HySIS is meant to provide hyperspectral imaging services to the country for a range of applications in agriculture, forestry and assessment of coastal zones, inland waters, soil and other geological environments, etc. HySIS carries two payloads in visible and near infrared regions of the electromagnetic spectrum. This earth observing imaging spectrometer will operate in the 0.4 to 0.95µm spectral range, will have 55 spectral bands with 10 nanometre spectral sampling and 30 metre spatial sampling. Push-broom scanning mode is the operating mode of this sensor from a 630-km orbit.

Hyperspectral imaging is a technique used for surveillance and reconnaissance in military, geophysical and marine science applications. Objects viewed by a hyperspectral imaging system are often observed in three-dimensions, x, y (spatial) and .lamda. (color wavelength). Spatial observations (x, y) allow a person to observe an image when high contrast is available. However, when an object is too far away to resolve, is camouflaged, or of unique chemical composition, spectral signatures help identify otherwise unobservable objects, for example to differentiate between friendly and enemy artillery.

A black-and-white photograph of an object or a geographic area is a two dimensional construct of the actual image or area--for each x, y coordinate in the image there is a single value blackness or whiteness of that particular image spot. As human beings, the eye can perceive useful information about objects or areas based on the differences between black, white, and the shades of gray. Color photographs add more visual information, but for most purposes the color information that is represented is tied to the visual spectrum. For each x, y coordinate in the image there is an approximation of the visual color spectrum of that particular image spot created through the blending of three color values, such as for example Red, Green, and Blue.

Multi-spectral sensing systems such as the Landsat Thematic Mapper remote imager and weather satellites produce images with a few relatively broad wavelength bands. The imager may capture a visual spectrum image and also one in infrared, but still they are limited in their ability to perceive information that may otherwise be present in a different part of the spectrum.

Hyperspectral sensors, on the other hand, collect image data across dozens if not hundreds of spectral bands, combining the technology of spectroscopy and remote imaging. The measurements captured by hyperspectral sensors make it possible to derive a contiguous spectrum for each image pixel. In other words for each x, y coordinate of an image (i.e., a pixel), rather than a single value for a gray or visible color, there is a third dimension--a vector, providing distinct information for that particular pixel across the large spectrum of wavelengths.

As different materials reflect wavelengths of visible and invisible light selectively, analysis of the contiguous wavelength spectrum permits finer resolution and greater perception of information contained in the image, through separation and evaluation of different wavelengths. For example, inorganic materials such as minerals, chemical compositions and crystalline structures control the shape of a representative spectral curve and the presence and positions of specific absorption bands.

The spectral reflectance curves of organic materials, such as healthy green plants also have a characteristic shape that is dictated by various plant attributes, such as the absorption effects from chlorophyll and other leaf pigments. Leaf structure varies significantly between plant species, and can be affected by plant stress. Therefore species type, plant stress and canopy state can all affect near infrared reflectance measurements, which are captured by hyperspectral sensors.

In addition, for a given pixel, a combination of different materials, e.g., biological, chemical, mineral, will provide a composite signal. Upon analysis and through comparison to known signal waveforms (e.g., known spectra) it is frequently possible to derive the presence of materials within a pixel, and therefore appreciate a detection granularity that is greater than the actual pixel resolution.

Hyperspectral sensors providing hyperspectral imaging can therefore be beneficially applied in a wide array of practical applications. Examples of such uses include aid in the detection of chemical or biological weapons, bomb damage assessment of underground structures, drug production and cultivation, as well as the detection of friend or foe troops and vehicles beneath foliage or camouflage.

Some targets are relatively easy to detect using standard techniques; whereas, other may not be. For example, detection of a terrain, such as asphalt, or concrete may be relatively straightforward for some images in which pixels (ground resolution cells) are filled by substantially the same material (e.g., asphalt or concrete). Alternatively, the measured signatures of a dispersed target, such as a gaseous plume, are complicated by a combination of phenomenology including effects of the atmosphere, spectral characteristics of the background material under the plume, temperature contrast between the gas and the surface, and the concentration of the gas.

All of these quantities vary spatially further complicating the detection problem. For example, an effluent target in a low wind and having a relatively dense and very bright target signature on at least a few contiguous pixels may be relatively easy to detect, even with a substantially high threshold. Accordingly, such relatively easy to detect targets would require minimal or no spatial processing. Alternatively, targets in a high wind and/or sparse, or weak may be present in dozens to hundreds pixels of a given image. Unfortunately, all or most such pixels may be below conventional thresholds.

Hyperspectral imaging typically employs a scanning slit spectrometer; although Fourier-transform imaging spectrometers (FTIS) and scanning filter (Fabry-Perot) imaging systems have also been used. These devices, however, record only two-dimensions of a three-dimensional data set at any one time. For example, the scanning slit spectrometer takes spectral information over a one-dimensional field of view (FOV) by imaging a scene onto a slit then collimating light from the slit through a dispersive element (prism) and re-imaging various wavelength images of the slit onto a detector array. In order to develop three-dimensional information, the slit is scanned over the entire scene producing different images that must be positionally matched in post-processing. The FTIS and Fabry-Perot techniques also scan: the former scans in phase space and the latter scans in frequency space.

The HySIS satellite has critical chip called an “optical imaging detector array’” indigenously developed by ISRO. ‘Hyspex’ imaging will enable distinct identification of objects, materials or processes on Earth by reading the spectrum for each pixel of a scene from space. Isro's Satellite Applications Centre has designed a chip to meet the project requirements with respect to spatial and temporal resolution, dynamic range, modulation transfer function, smear and spectral responsivity.

According to ISRO officials, 1000 X 66 pixels were designed to be readout, from both top and bottom directions, using four analog video ports to meet the frame rate requirement. Metal strapping was used for swiftly transferring integrated charges from image to storage region, in order to reduce image smear. Designs (both at chip and package levels) went through detailed review, before clearing for mask making and package fabrication, by a team consisting of members from Isro's SCL (Semiconductor Laboratory) and SAC (Satellite Application Centre).

ISRO officials said HySIS is increasingly being used in the field of remote sensing from airborne and space-borne platforms for a variety of applications. The HySIS spacecraft carries the Hyper Spectral Compact Imaging in VNIR (Visible and Near Infrared) and SWIR (Shortwave Infrared) spatial region in 60 and 256 contiguous spectral bands respectively, with 10 nm bandwidth providing 30m spatial resolution and covering a swath of 30 km at 630 km orbit.