کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6347316 | 1621265 | 2013 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Unattended processing of shipborne hyperspectral reflectance measurements
ترجمه فارسی عنوان
پردازش بی نظیری از اندازه گیری انعکاس هیبرید در کشتی
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
بازتاب تابش آسمان، بیش از حد، آب مورد 2 مانیتورینگ کشتی،
موضوعات مرتبط
مهندسی و علوم پایه
علوم زمین و سیارات
کامپیوتر در علوم زمین
چکیده انگلیسی
Hyperspectral remote-sensing reflectance (Rrs) from above-surface (ir)radiance measurements is derived using a new, automated method that is suitable for use on moving platforms. The sensors are mounted on a rotating platform that compensates for changing solar and ship azimuth angles, optimizing the sensor azimuth for minimal contribution of sky radiance to measured water-leaving radiance. This sea-surface reflectance (Ïs) lies in the order of 2.5-8% of sky radiance, and is determined through spectral optimization, minimizing the propagation of atmospheric absorption features to Rrs. Up to 15 of these gas absorption features are frequently recognized in (ir)radiance spectra under clear and overcast skies. Rrs was satisfactorily reproduced for a wide range of simulated Case 2 waters and clear sky conditions. A set of 13,784 in situ measurements collected with optimized viewing angles on the high-absorption, low-scattering Baltic Sea was collected in April and July 2010-2011. The processing procedure yielded a 22% retrieval rate of Ïs for the field data. The shape of the subsurface irradiance reflectance measurements (R(0â)) measured at anchor stations was well reproduced in above-surface Rrs in those cases where the algorithm converged on a solution for Ïs, except under unstable or weak illumination conditions. Clear-sky conditions resulted in the best correspondence of Rrs and R(0â) and gave the highest (>Â 50%) retrieval rates of Ïs. Two indices, derived from the available sensor data, are given to describe illumination conditions, and are shown to predict the ability of the algorithm to retrieve Rrs.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Remote Sensing of Environment - Volume 135, August 2013, Pages 202-212
Journal: Remote Sensing of Environment - Volume 135, August 2013, Pages 202-212
نویسندگان
Stefan G.H. Simis, John Olsson,