کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | ترجمه فارسی | نسخه تمام متن |
---|---|---|---|---|---|
1781165 | 1523944 | 2014 | 57 صفحه PDF | سفارش دهید | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Retrieving lunar topography from multispectral LROC images
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
فیزیک زمین (ژئو فیزیک)
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چکیده انگلیسی
A technique for retrieving information about the lunar topography from any individual multispectral LROC Wide Angle Camera (WAC) image has been developed. This technology is possible, since images acquired at different wavelengths correspond to different viewing angles and the influence of color differences between the images on the parallax assessments is small. This method provides the precision of Digital Elevation Models (DEMs) comparable to the global lunar 100Â m raster DTM retrieved from the LROC WAC stereo model (GLD100). It potentially allows one to obtain maps of the elevations with better horizontal resolution than those of the GLD100. An empirical model of the distortion for LROC WAC has been developed and used for correction of the initial WAC images. In contrast to the standard pre-flight model, our model allows for compensation of the radial distortion, decentering the optics, and tilt of the CCD array almost fully. The DEMs obtained using our approach exhibit real morphological details in some cases that are invisible in GLD100 maps. Thus, our method suggests additional independent information about the lunar topography. The fact that our elevation maps have the same projection as the initial images allows valid corrections of these images to account for topographic effects (i. e. orthorectification) in contrast to the use of the GLD100 that may have slightly different coordinates referencing in comparison to individual WAC images.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Planetary and Space Science - Volume 92, March 2014, Pages 65-76
Journal: Planetary and Space Science - Volume 92, March 2014, Pages 65-76
نویسندگان
Viktor V. Korokhin, Yuri I. Velikodsky, Eugene V. Shalygin, Yuriy G. Shkuratov, Vadym G. Kaydash, Gorden Videen,
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