Davide D'Alimonte , Tamito Kajiyama , Jaime Pitarch , Vittorio Ernesto Brando , Marco Talone , Constant Mazeran , Michael Twardowski , Srinivas Kolluru , Alberto Tonizzo , Ewa Kwiatkowska , David Dessailly , Juan Ignacio Gossn
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引用次数: 0
Abstract
Several methods were developed in Ocean Colour remote sensing over the last 25 years to model the anisotropy of the upwelling radiant field with respect to observation and solar-illumination geometries, also denoted as bidirectional reflectance distribution function (BRDF). These methods are necessary to produce normalized, or “BRDF-corrected,” marine reflectance representative of the seawater's inherent optical properties (IOPs) independently of the measurement conditions. Each scheme relies on specific modeling assumptions and implementation solutions, which can lead to different results depending on the actual combination of the seawater IOPs with the illumination and viewing geometry. The first aim of this study is to analyze the principles and methods of the reference BRDF schemes presented by Morel et al. (denoted as M02), Park and Ruddick (P05), Lee et al. (L11), He et al. (H17), and Twardowski and Tonizzo (T18). Acknowledging the direct applicability of M02, P05, and L11, their performance has been verified under a variety of conditions, including in situ measurements, matchup observations, and space-borne images. Comparisons between non-corrected and normalized data clearly confirm the need to account for the BRDF effect. In particular, the analysis of the results indicates 1) a substantial equivalence of M02, P05, and L11 in clear waters and 2) the tendency to obtain better results with M02 and L11 as the optical complexity increases. Although M02 was conceived for Case 1 waters, the underlying Chlorophyll-a overestimation tendency in some optically complex conditions is likely the reason for its extended applicability. Since L11 is based on a more comprehensive and flexible framework for all water types, the design of this method is suggested for revisions and BRDF correction improvements.
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.