Assessing the Spectral Sensitivity of Martian Terrains to Iron Oxide Variations Using the SPLITS Model

Baranoski, Gladimir V. G.; Kimmel, Bradley W.; Chen, T. Francis; Miranda, Erik

doi:10.1109/jstars.2015.2400228

Cited by 7 publications

(4 citation statements)

References 56 publications

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“…Moreover, we performed our in silico experiments using a first-principles light transport model, whose predictive capabilities have been qualitatively and quantitatively demonstrated in previous works. 22,24,[53][54][55] Hence, we are confident that our findings will be confirmed by actual spectrophotometric experiments as in situ measurement technologies capable of avoiding alterations in the samples' interstitial structure become readily available.…”

Section: Practical Issuessupporting

confidence: 55%

Assessing the impact of porosity variations on the reflectance and transmittance of natural sands

Baranoski

Kimmel

Varsa

2019

J. Appl. Rem. Sens.

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Porosity is a fundamental characteristic of naturally occurring sand-textured soils, commonly referred to as natural sands, found in a wide range of landscapes, from beaches to dune fields. As a primary determinant of the density and permeability of sediments, it represents a pivotal element in geophysical studies involving basin modeling and the optical dating of sand deposits formed in areas subjected to erosion like coasts and deltas. It is also of interest for geoaccoustics and geochemical research on sediment transport and water diffusion properties of these deposits, as well as for agricultural and ecological investigations on the germination of light-sensitive seeds and the photochemical transformation of substances (e.g., pesticides) that may be present in these soils. Despite the importance of these applications, however, the remote estimation of porosity and the quantification of its effects on the light penetration profiles of natural sands remain elusive tasks. In this work, we tackle one of the major obstacles in this interdisciplinary area of research, namely the relative scarcity of experimental information due to technical constraints associated with traditional laboratory procedures. More specifically, we systematically examine the impact of porosity variations on the reflectance and transmittance of natural sands (in the 400 to 1000 nm region of the light spectrum) through controlled in silico experiments supported by measured data. Our findings are expected to strengthen the knowledge basis required for advances in this area and contribute to the development of technologies aimed at the effective monitoring and prediction of environmentally triggered changes affecting these soils.

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Section: Practical Issuessupporting

confidence: 55%

Assessing the impact of porosity variations on the reflectance and transmittance of natural sands

Baranoski

Kimmel

Varsa

2019

J. Appl. Rem. Sens.

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“…Based on the works of Judd [54] and Nicodemus [53,55], the directional-hemispherical reflectance and the hemispherical-directional reflectance factor quantities are considered numerically equivalent for a given direction as a direct consequence of Kirchhoff's law [56] and the Helmholtz reciprocity principle [54]. Thus, for practicality, in studies involving the radiometric responses of materials characterized by a near-Lambertian behaviour, such as snow irradiated from an angle of incidence of 0 • [38,57], directional-hemispherical reflectance and hemispherical-directional reflectance factor can be used interchangeably [58,59].…”

Section: Methodsmentioning

confidence: 99%

Environmentally Induced Snow Transmittance Variations in the Photosynthetic Spectral Domain: Photobiological Implications for Subnivean Vegetation under Climate Warming Conditions

Baranoski,

Varsa

2024

Remote Sensing

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Variations in the productivity of subnivean vegetation can substantially affect the ecology of regions more susceptible to increasing warming levels and lead to significant feedback effects on the global climate. Due to its importance, this topic is at the center of a broad scope of interdisciplinary studies supported by field and remote sensing observations. However, the current knowledge about environmental factors affecting the penetration of photosynthetically active radiation (PAR) through snow is still constrained by the paucity of transmittance data. In this work, we aim to further the understanding about these interconnected processes. We conduct a systematic investigation about the effects of independent and combined changes in key nivological characteristics, namely thickness, saturation, density and grain size, on snow transmittance in the photosynthetic spectral domain. Our investigation is carried out through controlled in silico (computational) experiments supported by measured radiometric data. Its outcomes unveil fundamental quantitative and qualitative trends related to the role played by these nivological characteristics on the spectral quality of transmitted PAR, which is quantified in terms of red to blue (R/B), red to far-red (R/FR) and blue to far-red (B/FR) ratios. These trends include increases in the R/B ratio as well as decreases in the R/FR and B/FR ratios following thickness reductions or grain size increases, with opposite variations in these ratios being observed for saturation or density increases. Accordingly, the pairing of our findings with in situ and remotely collected information contributes to cement the scientific foundation required for the effective assessment of cause-effect loops linking accentuated vegetation greening to accelerated rates of snow cover recession.

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“…Similarly, models of light interaction with inorganic particulate materials, such as sand, can be used not only in the generation of images depicting the appearance of landscapes (e.g., [68,69]), but also in the remote hyperspectral analysis of their morphological attributes and mineral content (e.g., [10,11]). In the case of artistic objects and historic documents, their conservation can be substantially enhanced through the use of hyperspectral imaging analysis algorithms supported by predictive material fading simulations (e.g., [51,67,70,90]).…”

Section: Quest For Predictabilitymentioning

confidence: 99%

“…For materials characterized by a particulate nature, the SPLITS approach can lead to simulation results with a competitive fidelity to cost ratio. For example, besides its use in the predictive modeling of light interactions with sand grains found in terrestrial [10,69] and extraterrestrial landscapes [11], it has also been employed in the development of a hyperspectral appearance model for human blood, known as CLBlood (Cell-Based Light Interaction Model for Human Blood) [126].…”

Section: Level Of Abstractionmentioning

confidence: 99%

Hyperspectral Modeling of Material Appearance: General Framework, Challenges and Prospects

Baranoski

2015

RITA

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Abstract:The main purpose of this tutorial is to address theoretical and practical issues involved in the development of predictive material appearance models for interdisciplinary applications within and outside the visible spectral domain. We examine the specific constraints and pitfalls found in each of the key stages of the model development framework, namely data collection, design and evaluation, and discuss alternatives to enhance the effectiveness of the entire process. Although predictive material appearance models developed by computer graphics researchers are usually aimed at realistic image synthesis applications, they also provide valuable support for a myriad of advanced investigations in related areas, such as computer vision, image processing and pattern recognition, which rely on the accurate analysis and interpretation of material appearance attributes in the hyperspectral domain. In fact, their scope of contributions goes beyond the realm of traditional computer science applications. For example, predictive light transport simulations, which are essential for the development of these models, are also regularly being used by physical and life science researchers to understand and predict material appearance changes prompted by mechanisms which cannot be fully studied using standard "wet" experimental procedures. For completeness, this tutorial also provides an overview of such synergistic research efforts and in silico investigations, which are illustrated by case studies involving the use of hyperspectral material appearance models.

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Assessing the Spectral Sensitivity of Martian Terrains to Iron Oxide Variations Using the SPLITS Model

Cited by 7 publications

References 56 publications

Assessing the impact of porosity variations on the reflectance and transmittance of natural sands

Assessing the impact of porosity variations on the reflectance and transmittance of natural sands

Environmentally Induced Snow Transmittance Variations in the Photosynthetic Spectral Domain: Photobiological Implications for Subnivean Vegetation under Climate Warming Conditions

Hyperspectral Modeling of Material Appearance: General Framework, Challenges and Prospects

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