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112 5. Application : Restoration of Aqua MODIS Band 6 Figure 5.1 – (Left) Image from Aqua MODIS band 6 showing 4 non functional detectors (Right) Image from Aqua band 6 after removal of missing lines : functional detectors are contaminated with stripe noise approaches related to the analysis of snow cover use the Normalized Difference Snow Index (NDSI). This index exploits snow high reflectivity in the visible (0.5-0.7 µm) and its low reflectance in the SWIR (1-4 µm). Defined as a spectral band ratio, the NDSI allows a robust separation of snow from clouds and also reduces the influence of atmospheric effects and viewing geometry [Salomonson and Appel]. On MODIS, the NDSI can be expressed as the difference of reflectances ρ measured in the visible band 4 (0.555 µm) and a SWIR band such as band 6 divided by the sum of the two reflectances : NDSI 16 = ρ 4 − ρ 6 ρ 4 + ρ 6 (5.1) The evaluation of the NDSI index on the Aqua sensor is problematic due to the non functional detectors. Nevertheless, to ensure complementary observations to Terra MODIS band 6 and provide continuous monitoring and mapping of snow coverage, scientists have relied on Aqua MODIS band 7 (2.105-2.155 µm). This is a reasonnable alternative, given that snow has similar reflectance properties over bands 6 and 7, which happen to display a high correlation over land surfaces. As a result, Aqua-based snow coverage is determined using a secondary NDSI defined as : NDSI 17 = ρ 4 − ρ 7 ρ 4 + ρ 7 (5.2) It was however pointed out in [Hall et al.], that the reflectance of snow is slightly weaker in band 7 compared to band 6. Consequently, values of NDSI 17 are higher than NDSI 16 and the estimation of snow coverage is compromised. Given the importance of retrieving
113 Figure 5.2 – Location of the Terra MODIS scenes selected over snow-covered regions for the study of Aqua MODIS band 6 restoration (Left) Alaska, May 5, 2001 (Center) Labrador, Canada, November 7, 200 (Right) Siberia, Russia, May 24, 2001 accurate quantitative variables associated with snow and ice components, and used in climate change numerical models, an alternative option to NDSI 17 is mandatory. To this purpose, restoration techniques for Aqua MODIS band 6 have been recently proposed. 5.2 Existing restoration techniques 5.2.1 Global interpolation [L. L. Wang and Nianzeng] were the first to investigate the relationship between bands 6 and 7 and demonstrated the feasability of restoring Aqua MODIS band 6 missing data. The authors first remarqued that the difference of snow reflectance between Terra MODIS bands 6 and 7 is very close to the same difference on Aqua MODIS. Using observations consisting of Terra MODIS level 1B calibrated and geolocated radiances at TOA, polynomial regression was used to quantify the analytical relationship between Terra MODIS bands 6 and 7. Quantitative analysis conducted by the authors over snow covered areas, shows that TOA reflectances in Terra MODIS band 6/7, and NDSI 16 /NDSI 17 were highly correlated with correlation coefficients of 0.9821 and 0.9777 respectively. Linear, quadratic, cubic, and fourth-degree polynomials were derived from Terra bands 6/7 scatter plots in order to be applied to Aqua MODIS. Wang et al. suggest restoring Aqua MODIS band 6 using cubic and quadratic polynomes of the corresponding band 7 reflectances : ρ 6 =1.6032ρ 3 7 − 1.9458ρ 2 7 +1.7948ρ 7 +0.012396 ρ 6 = −0.70472ρ 2 7 +1.5369ρ 7 +0.025409 (5.3) These analytical relationships between bands 6 and 7 were derived fom Terra measurements over snow covered regions. It obviously do not account for land surface cover types, spectral characteristics, scanning geometry. Application of this approach to restore band 6
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École Doctorale d’Informatique,
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5 Résumé Nou abordons dans cette
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8 TABLE DES MATIÈRES 3.5 Frequency
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10 TABLE DES MATIÈRES
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14 1. Introduction
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40 3. Standard destriping technique
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