A Ray Optics Framework for the Computation of The Sieve Effect Factor for Blood

Light may traverse a turbid material, such as blood, without encountering any of its pigment particles, a phenomenon known as sieve effect. This phenomenon may result in a decrease in the amount of light absorbed by the material. Accordingly, the corresponding sieve factor needs to be accounted for in optical investigations aimed at the derivation of blood biophysical properties from light transmittance measurements. The existing procedures used for its estimation either lack the flexibility required for practical applications or are based on general formulas that incorporate other light and matter interaction phenomena. In this thesis, a ray optics framework is proposed to estimate the sieve factor for blood samples using a first principles approach. It consists in applying ray-casting techniques to determine the probability that light can traverse a blood sample without encountering any of the pigment (hemoglobin) containing cells. The thickness of the samples as well as the distribution, orientation and shape of the red blood cells are taken into account by the simulation algorithm employed in this framework. The predictive capabilities of the proposed approach are demonstrated through a series of in silico experiments. Its effectiveness is further illustrated by visualizations depicting the different blood parameterizations considered in the simulations

Coniferous needle-leaves, shots and canopies : a remote sensing approach

Coniferous forests are important in the regulation of the Earth’s climate and thus continuous monitoring of these ecosystems is crucial to better understand potential responses to climate change. Optical remote sensing (RS) provides powerful methods for the estimation of essential climate variables and for global forest monitoring. However, coniferous forests represent challenging targets for RS methods, mainly due to structural features specific for coniferous trees (e.g. narrow needle leaves, shoot clumping) whose effects on the RS signal are not yet known or not yet fully understood. Recognizing the need for a better adaptation of RS methods to such spatially heterogeneous and structurally complex canopies, this thesis contributes to improving the interpretation of the remotely sensed optical signal reflected from coniferous stands by focusing on specific knowledge gaps identified in the RS methods at different scales of the coniferous canopies. In addition, it explores the application of approaches that simplify the way the structural complexity of such an environment is tackled when using canopy-level radiative transfer approaches. Three main levels based on the identified gaps were defined for the analysis: (needle) leaf level (chapter 2 and 3); shoot level (chapter 4) and canopy level (chapter 5). At leaf levelthis thesis contributes to minimizing the uncertainties and errors related to leaf optical measuring methods adapted for needle leaves. Although optical properties of coniferous leaves are extensively used in RS approaches (i.e. as input or as validation data), there is only a limited number of techniques available for measuring coniferous leaves. The first focus of this thesis was to review the shortcomings and uncertainties of such methods in order to identify application limits and potential improvements (chapter 2). A review showed that a more standardized measuring protocol was needed, for which measurement uncertainties and errors had to be identified, quantified and preferably removed or minimized. Thus, an experimental set-up improving the original method of Mesarch et al. (1999) was presented (chapter 3), which focused on analyzing uncertainties caused by the presence of the sample holder and by the multiple scattering triggered by both the shape of the specific needle cross-section, and the distance between the needles composing a sample. Results showed that both the sample holder and the multiple scattering, triggered specially by the shape of the non-flat cross section of the coniferous needle-leaves, had a non-negligible effect on the optical signal when measured using a standard spectroradiometer coupled to a single-beam integrating sphere and following the method suggested by Mesarch. Thus, approaches designed to measure optical properties of non-flat coniferous needle samples more comprehensively should take into account these effects in their current signal correction algorithms. Needle clumping into shoots quickly transforms the optical signal making the description of the canopy radiative transfer a complex task and encouraging the search for simplified yet robust approaches. Thus, subsequent steps in this thesis focus on one such simplified approach, known as the recollision probability theory (“p-theory”), applied at two hierarchical levels, i.e., shoots (Chapter 4) and the whole canopy (Chapter 5).At shoot level, an empirical verification of the relationship between the photon recollision probability and a structural parameter called STAR was investigated. The approach allows upscaling needle albedo to shoot albedo and was previously theoretically tested only (chapter 4). For this analysis empirical optical measurements of Scots pine needles and shoots were used. Results showed that the approach works well for the VIS and SWIR spectral regions. However, it was less accurate for the NIR and also for sparse shoots (STAR Finally, accurate modelling of the reflectance signal at canopy levelfor coniferous canopies requires realistic representations of the forest stands, which in general implies a large number of input parameters and computationally demanding algorithms. Radiative transfer modelling based on the photon recollision probability offers an alternative for a simplified definition of the forest canopy structure. The performance of such approach for estimation of the leaf chlorophyll content from satellite imaging spectroscopy data acquired by the CHRIS-PROBA sensor was investigated. The approach was compared to a computationally more demanding one based on a detailed 3D structural description of a forest (chapter 5). For this purposes two canopy models, PARAS and DART, representing the first and second approach respectively, were used. Top-of-canopy bidirectional reflectance factors (BRF) were simulated for both models and used to calculate two optical indices, ANCB670–720 and ANMB670–720.Subsequently, the empirical relationships established between the optical indices and the needle-leaf chlorophyll content (Cab) were applied to the CHRIS-PROBA image of a Norway spruce forest stand to retrieve a map of Cab estimates. Results showed that for the spatial resolution of CHRIS-PROBA (17 m), the simpler model PARAS can be applied to retrieve plausible needle-leaf Cab estimates from satellite imaging spectroscopy data with less intensive model parameterization and reduced computational powerthan when using a model like DART. The ANMB670–720 optical indexwas more robust andresulted in a linear relationship between the Cab estimated by both models. This relationship showed, however, a systematic offset that is potentially caused by differences in the implementation of woody elements in each model or by a different parameterization of leaf optical properties. Thus, further investigation on the impact of parameterization differences related to the needle optical properties and the implementation of woody elements in such a model is recommended.</p

Remote Sensing of Plant Biodiversity

At last, here it is. For some time now, the world has needed a text providing both a new theoretical foundation and practical guidance on how to approach the challenge of biodiversity decline in the Anthropocene. This is a global challenge demanding global approaches to understand its scope and implications. Until recently, we have simply lacked the tools to do so. We are now entering an era in which we can realistically begin to understand and monitor the multidimensional phenomenon of biodiversity at a planetary scale. This era builds upon three centuries of scientific research on biodiversity at site to landscape levels, augmented over the past two decades by airborne research platforms carrying spectrometers, lidars, and radars for larger-scale observations. Emerging international networks of fine-grain in-situ biodiversity observations complemented by space-based sensors offering coarser-grain imagery—but global coverage—of ecosystem composition, function, and structure together provide the information necessary to monitor and track change in biodiversity globally. This book is a road map on how to observe and interpret terrestrial biodiversity across scales through plants—primary producers and the foundation of the trophic pyramid. It honors the fact that biodiversity exists across different dimensions, including both phylogenetic and functional. Then, it relates these aspects of biodiversity to another dimension, the spectral diversity captured by remote sensing instruments operating at scales from leaf to canopy to biome. The biodiversity community has needed a Rosetta Stone to translate between the language of satellite remote sensing and its resulting spectral diversity and the languages of those exploring the phylogenetic diversity and functional trait diversity of life on Earth. By assembling the vital translation, this volume has globalized our ability to track biodiversity state and change. Thus, a global problem meets a key component of the global solution. The editors have cleverly built the book in three parts. Part 1 addresses the theory behind the remote sensing of terrestrial plant biodiversity: why spectral diversity relates to plant functional traits and phylogenetic diversity. Starting with first principles, it connects plant biochemistry, physiology, and macroecology to remotely sensed spectra and explores the processes behind the patterns we observe. Examples from the field demonstrate the rising synthesis of multiple disciplines to create a new cross-spatial and spectral science of biodiversity. Part 2 discusses how to implement this evolving science. It focuses on the plethora of novel in-situ, airborne, and spaceborne Earth observation tools currently and soon to be available while also incorporating the ways of actually making biodiversity measurements with these tools. It includes instructions for organizing and conducting a field campaign. Throughout, there is a focus on the burgeoning field of imaging spectroscopy, which is revolutionizing our ability to characterize life remotely. Part 3 takes on an overarching issue for any effort to globalize biodiversity observations, the issue of scale. It addresses scale from two perspectives. The first is that of combining observations across varying spatial, temporal, and spectral resolutions for better understanding—that is, what scales and how. This is an area of ongoing research driven by a confluence of innovations in observation systems and rising computational capacity. The second is the organizational side of the scaling challenge. It explores existing frameworks for integrating multi-scale observations within global networks. The focus here is on what practical steps can be taken to organize multi-scale data and what is already happening in this regard. These frameworks include essential biodiversity variables and the Group on Earth Observations Biodiversity Observation Network (GEO BON). This book constitutes an end-to-end guide uniting the latest in research and techniques to cover the theory and practice of the remote sensing of plant biodiversity. In putting it together, the editors and their coauthors, all preeminent in their fields, have done a great service for those seeking to understand and conserve life on Earth—just when we need it most. For if the world is ever to construct a coordinated response to the planetwide crisis of biodiversity loss, it must first assemble adequate—and global—measures of what we are losing

Remote Sensing of Plant Biodiversity

This Open Access volume aims to methodologically improve our understanding of biodiversity by linking disciplines that incorporate remote sensing, and uniting data and perspectives in the fields of biology, landscape ecology, and geography. The book provides a framework for how biodiversity can be detected and evaluated—focusing particularly on plants—using proximal and remotely sensed hyperspectral data and other tools such as LiDAR. The volume, whose chapters bring together a large cross-section of the biodiversity community engaged in these methods, attempts to establish a common language across disciplines for understanding and implementing remote sensing of biodiversity across scales. The first part of the book offers a potential basis for remote detection of biodiversity. An overview of the nature of biodiversity is described, along with ways for determining traits of plant biodiversity through spectral analyses across spatial scales and linking spectral data to the tree of life. The second part details what can be detected spectrally and remotely. Specific instrumentation and technologies are described, as well as the technical challenges of detection and data synthesis, collection and processing. The third part discusses spatial resolution and integration across scales and ends with a vision for developing a global biodiversity monitoring system. Topics include spectral and functional variation across habitats and biomes, biodiversity variables for global scale assessment, and the prospects and pitfalls in remote sensing of biodiversity at the global scale

Mass Transfer in Multiphase Systems and its Applications

This book covers a number of developing topics in mass transfer processes in multiphase systems for a variety of applications. The book effectively blends theoretical, numerical, modeling and experimental aspects of mass transfer in multiphase systems that are usually encountered in many research areas such as chemical, reactor, environmental and petroleum engineering. From biological and chemical reactors to paper and wood industry and all the way to thin film, the 31 chapters of this book serve as an important reference for any researcher or engineer working in the field of mass transfer and related topics