Mapping the surface properties of the Asal-Ghoubbet rift by massive inversion of the Hapke model on Pleiades multiangular images

IF 11.1 1区 地球科学 Q1 ENVIRONMENTAL SCIENCES
D.T. Nguyen , S. Jacquemoud , A. Lucas , S. Douté , C. Ferrari , S. Coustance , S. Marcq , A. Meygret
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引用次数: 0

Abstract

A massive inversion of the Hapke model is carried out over the Asal-Ghoubbet rift (Republic of Djibouti) using high-resolution multiangular Pleiades images. This is the first time that such an inversion is performed on Earth over an entire image, previous studies having focused on planetary surfaces. This work addresses challenges such as atmospheric and geometrical corrections of these images to produce parameter maps. The use of fast Bayesian inversion significantly reduces computation times thanks to efficient exploration of the parameter space and leads to improved prediction. The parameters of the Hapke model are also interpreted in terms of surface physical properties, thanks to field measurements. Single scattering albedo is the parameter extracted with the greatest reliability, although its validation is still difficult due to the absence of a simple formula linking it to surface reflectance. Our study reveals a close relationship between photometric roughness and single scattering albedo, indicating that accurate extraction of the former is highly dependent on values of the latter, which must be below 0.8 for reliable estimation. Finally, the correlation between phase function parameters and grain properties depends on surface type and material properties.
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来源期刊
Remote Sensing of Environment
Remote Sensing of Environment 环境科学-成像科学与照相技术
CiteScore
25.10
自引率
8.90%
发文量
455
审稿时长
53 days
期刊介绍: Remote Sensing of Environment (RSE) serves the Earth observation community by disseminating results on the theory, science, applications, and technology that contribute to advancing the field of remote sensing. With a thoroughly interdisciplinary approach, RSE encompasses terrestrial, oceanic, and atmospheric sensing. The journal emphasizes biophysical and quantitative approaches to remote sensing at local to global scales, covering a diverse range of applications and techniques. RSE serves as a vital platform for the exchange of knowledge and advancements in the dynamic field of remote sensing.
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