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Lunar Iron and Titanium Extraction Usine Chang’E-1Interference Imaging Spectroradiometer Data

Author: XueQiao
Tutor: ZhaoShuHe; WuZuoZhao
School: Nanjing University
Course: Cartography and Geographic Information Systems
Keywords: Moon Chang’E-1 Interference Imaging Spectroradiometer iron titanium
CLC: TP391.41
Type: Master's thesis
Year: 2012
Downloads: 119
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Abstract


Until now, people’s knowledge on the mineralogy and elements of the moon is quite limited.Remote sensing is the main way to acquire information about these. Knowing the contents and spatial distribution of elements are important goals of lunar researches, among which iron and titanium are two important elements.This study focuses on the calibration of Chang’E-1interference imaging spectroradiometer (IIM) data and extraction of lunar iron and titanium based on it, which include removing bad lines and bad points of IIM data,relative calibration of IIM images, absolute calibration, photometric correction and extraction of lunar iron and titanium. The major contents and conclusions are as follows:(1) Bad lines, bad points and bad bands of images are detected and removed. Bad lines are detected and repaired using the column slop method, and the GST is3and BFNP is0.4.Bad points are detected and removed using a new method applying a threshold to all the bands and the threshold is2.7. Distribution principles of bad line and bad points between columns and orbits are discussed, which indicates that the84th and110th column have the most bad lines and images acquired earlier have more bad lines and lesser bad points. It is found that Skewness and Kurtosis can distinguish bad bands and normal ones effectively.(2)IIM images show heterogeneity between the left sides and the right sides because of the inhomogeneity of spatial response of the detectors.This study discusses the methods to perform relative radiometric calibration of IIM data.IIM data is of large amount and has complicated imaging geometries,which cause the radiances diffrences between low and high latitude regions. Commonly used methods based on linear regression or ones based on mean and variance are not suitable to IIM data. So,the corrections are executed using a histogram matching algorithm by matching the columns to the entire band.This algorithm achieves good results, and it does not change the DN distribution and at the same time the stripes are also removed.(3)An absolute calibration method for remotely sensed imagery is improved.The methods include ones based on lunar sample spectra and ones based on the solar irradiance. By comparison, the method based on the lunar soil spectra is chosen to convert IIM data to reflectance, and the calibration area is in the2844orbit. This method makes full use of the precise measurements of the lunar soil spectra, as a result the derived reflectance images are insensitive to noise and the results from four calibration areas are much alike. The solar irradiance method is not suitable for IIM data because of IIM’s spectral noise in spite of many uses in other researches, and the solar irradiance may have errors. The reflectance result is about2%lower between band27and band30, while it is very similar to truth from band7to band26.The spectra shows better spectral resolution.(4)A method of the photometric correction of IIM data is proposed. The images are photometrically normalized using multi-band phase curves, which are derived from the data after noise removed.As a result, the calibration is largely enhanced. After that, ways on how to extract iron and titanium are discussed.We successfully acquire lunar iron and titanium maps of high spatial resolution using Lucey’s method, the parameters used are retrieved from the calibrated data.The results are compared with thoese derived from other remotely sensed data. Our results are very similar to them, the iron result is2-3wt.%lower in lunar maria and the titanium result is within lwt.%higher in parts of lunar maria.

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