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Journal ArticleDOI

Second Simulation of the Satellite Signal in the Solar Spectrum, 6S: an overview

TLDR
The 6S code has still limitations; it cannot handle spherical atmosphere and as a result, it cannot be used for limb observations, and the decoupling the authors are using for absorption and scattering effects does not allow to use the code in presence of strong absorption bands.
Abstract
Remote sensing from satellite or airborne platforms of land or sea surfaces in the visible and near infrared is strongly affected by the presence of the atmosphere along the path from Sun to target (surface) to sensor. This paper presents 6S (Second Simulation of the Satellite Signal in the Solar Spectrum), a computer code which can accurately simulate the above problems. The 6S code is an improved version of 5S (Simulation of the Satellite Signal in the Solar Spectrum), developed by the Laboratoire d'Optique Atmospherique ten years ago. The new version now permits calculations of near-nadir (down-looking) aircraft observations, accounting for target elevation, non lambertian surface conditions, and new absorbing species (CH/sub 4/, N/sub 2/O, CO). The computational accuracy for Rayleigh and aerosol scattering effects has been improved by the use of state-of-the-art approximations and implementation of the successive order of scattering (SOS) algorithm. The step size (resolution) used for spectral integration has been improved to 2.5 nm. The goal of this paper is not to provide a complete description of the methods used as that information is detailed in the 6S manual, but rather to illustrate the impact of the improvements between 5S and 6S by examining some typical remote sensing situations. Nevertheless, the 6S code has still limitations. It cannot handle spherical atmosphere and as a result, it cannot be used for limb observations. In addition, the decoupling the authors are using for absorption and scattering effects does not allow to use the code in presence of strong absorption bands.

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Citations
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NDWI--a normalized difference water index for remote sensing of vegetation liquid water from space.

TL;DR: The normalized difference water index (NDWI) as discussed by the authors was proposed for remote sensing of vegetation liquid water from space, which is defined as (ϱ(0.86 μm) − ϱ(1.24 μm)) where ϱ represents the radiance in reflectance units.
Journal ArticleDOI

Change detection techniques

TL;DR: This paper is a comprehensive exploration of all the major change detection approaches implemented as found in the literature and summarizes and reviews these techniques.
Journal ArticleDOI

A survey of image classification methods and techniques for improving classification performance

TL;DR: It is suggested that designing a suitable image‐processing procedure is a prerequisite for a successful classification of remotely sensed data into a thematic map and the selection of a suitable classification method is especially significant for improving classification accuracy.
Book

Remote sensing, models, and methods for image processing

TL;DR: The Nature of Remote Sensing: Introduction, Sensor Characteristics and Spectral Stastistics, and Spatial Transforms: Introduction.
References
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Journal ArticleDOI

Measurement of the Roughness of the Sea Surface from Photographs of the Sun’s Glitter

TL;DR: In this paper, a method was developed for interpreting the statistics of the sun's glitter on the sea surface in terms of the statistic of the slope distribution, which was applied to aerial photographs taken under carefully chosen conditions in the Hawaiian area.
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Optical modeling of the upper ocean in relation to its biogenous matter content (case I waters)

TL;DR: In this paper, a pigment-dependent optical model is developed to predict the propagation of visible radiant energy within the ocean or the backscattered radiation from the upper layer to be predicted as a function of the local phytoplanktonic content.
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A bidirectional reflectance model of the Earth's surface for the correction of remote sensing data

TL;DR: In this article, a surface bidirectional reflectance model was developed for the correction of surface bias in time series of satellite observations, where both sun and viewing angles are varying.
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Bidirectional reflectance spectroscopy. IV - The extinction coefficient and the opposition effect

TL;DR: In this paper, an analytical model was developed for the opposition effect (heiligenshein) in the case of light scattering from a semi-infinite, particulate medium with particles that are large relative to the wavelength.
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