hyperspectral remote sensing
Recent advances in remote sensing, geographic information and computer technology have led the way for the generation of hyperspectral sensors and development of a new field of remote sensing. Hyperspectral remote sensing, also known as imaging spectroscopy, is a relatively new technology which was originally developed to obtain geochemical information from inaccessible planetary surfaces within the solar system.
The first hyperspectral image of the country
Recent advances in remote sensing, geographic information and computer technology have led the way for the generation of hyperspectral sensors and development of a new field of remote sensing. Hyperspectral remote sensing, also known as imaging spectroscopy, is a relatively new technology which was originally developed to obtain geochemical information from inaccessible planetary surfaces within the solar system. The primary application of this new technique, however, has recently changed towards the observation of the Earth, and now is being used by researchers and scientists for detection and identification of minerals, vegetation, and man-made materials.
Imaging spectroscopy has been used in the laboratory by physicists and chemists for over 100 years for identification of materials and their composition. Spectroscopy is based on the interaction and reflectance of photons with molecular structures of surface materials. In different wavelength ranges of electromagnetic spectrum, different types of objects reflect, absorb or emit a certain intensity of spectrum depending upon their physical or compositional attributes whether solid, liquid or gas. The curves showing the intensity of electromagnetic spectrum, reflected or emitted by the objects at different wavelengths are called spectral response curves and are used as spectral signatures for identification of different objects. Spectroscopy has the advantage of being sensitive to both crystalline and amorphous materials
Hyperspectral remote sensing combines imaging and spectroscopy in a single system making it possible to obtain contiguous spectral data of the Earth surface from an airborne or space-borne platform. Most natural Earth surface materials have diagnostic absorption features in the 0.4 -2.5mm range of the reflected spectrum. Since the diagnostic features for each material are apparent over very narrow spectral bands, different materials can only be identified if the spectrum is sampled at a sufficiently high resolution. Hyperspectral sensors image a scene in a large number of discrete contiguous narrow spectral bands ranging from 64 to more than 200 bands of relatively narrow bandwidths (10-20 nm), in comparison with the multispectral sensors in which there are typically 4-10 spectral channels at approximately 100-200 nm interval. Hyperspectral imagery is typically collected and represented as a data cube with spatial information collected in the X-Y directions, and spectral information represented in the Z-direction. The ultimate goal of Hyperspectral imagery is producing laboratory quality reflectance spectra for each pixel in an image. Detection of materials is dependent on the spectral coverage, spectral resolution, and signal-to-noise of the scanner, the abundance of the material and the strength of absorption features for that material in the measured wavelength region.
There are many applications which can take advantage of hyperspectral remote sensing. Geology is one of the first applications to benefit from imaging spectroscopy especially in the areas of identification and mapping of minerals, and lithological mapping in arid environments. Vegetation-based studies are also utilizing tools and techniques developed from imaging spectroscopy for geology. Ecological studies are likely to benefit greatly from the increased spectral resolution of imaging spectroscopy.
The Remote Sensing group of Geological Survey of Iran is currently utilizing hyperspectral imaging for mineral exploration. HyMap Airborne imaging spectrometer, which is an Australian development, is used for imaging. The sensor is a whisk-broom type and originally has been designed for mineral exploration. HyMap scanner collects 126 channels of data in the visible, near and short wave infrared bands (VNIR-SWIR) ranging between 400 and 2500 nm with a bandwidth of approx16 nm. The nominal spatial resolution is 5 m with FOV of 60¢ھ (512 pixels). The signal/noise ratio of the instrument is 500/1 which is more than those of most existing imaging spectrometers. Geolocation and image geocoding is achieved with DGPS and an integrated IMU (inertial monitoring unit). In the first phase of this project which is one of the largest projects regarding the spatial extent an area of 60000 km2 would be covered by hyperspectral imaging.
Abtorsh area located in Tarom Mountains is the first (test) area covered by imaging spectroscopy. In this method, the collected raw data first are preprocessed to be converted to spatially and spectrally rectified at-sensor radiance data. The radiance data are then converted to ground reflectance data in order to remove the influence of external factors (atmosphere and topography) so that they can be compared with the field and laboratory data collected on the ground. The reflectance data can be used to detect and map the hydrothermal alteration minerals associated with mineralization; to identify different zones of alteration; and to determine the type of mineralization.