Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects <s> C. Environmental Studies <s> In a tape cassette with a housing including top and bottom walls having respective pairs of spaced apart openings aligned with each other, a pair of hubs disposed rotatably within the housing between the walls and being accessible through the respective aligned openings for selectively driving the hubs of the cassette, and a magnetic tape wound on a cylindrical circumferential surface of an outer peripheral portion of each of the hubs; each of the hubs includes an annular rib radially inward from the outer peripheral portion and projecting axially beyond opposite flanks of the outer peripheral portion of the hub so as to extend rotatably around annular flanges directed axially inward from the respective aligned openings of the housing walls, and a pair of lubricating sheets are disposed against the inner surfaces of the housing walls and each have a pair of ridges or beads projecting therefrom and a pair of holes located between the ridges and through which the annular flanges on the adjacent wall extend with the annular rib of each hub engaging flat surface portions located between the holes and ridges of the sheets while the ridges of the lubricating sheets are engageable with the flanks of the outer peripheral portions of the hubs for accurately guiding the wound tape in the axial direction of the hubs. <s> BIB001 </s> Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects <s> C. Environmental Studies <s> The global spread of wireless networks brings a great opportunity for their use in environmental studies. Weather, atmospheric conditions, and constituents cause propagation impairments on radio links. As such, while providing communication facilities, existing wireless communication systems can be used as a widely distributed, high-resolution atmospheric observation network, operating in real time with minimum supervision and without additional cost. Here we demonstrate how measurements of the received signal level, which are made in a cellular network, provide reliable measurements for surface rainfall. We compare the estimated rainfall intensity with radar and rain gauge measurements. <s> BIB002 </s> Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects <s> C. Environmental Studies <s> We propose a new technique that overcomes the obstacles of the existing methods for monitoring near-surface water vapour, by estimating humidity from data collected through existing wireless communication networks. Weather conditions and atmospheric phenomena affect the electromagnetic channel, causing attenuations to the radio signals. Thus, wireless communication networks are in effect built-in environmental monitoring facilities. The wireless microwave links, used in these networks, are widely deployed by cellular providers for backhaul communication between base stations, a few tens of meters above ground level. As a result, if all available measurements are used, the proposed method can provide moisture observations with high spatial resolution and potentially high temporal resolution. Further, the implementation cost is minimal, since the data used are already collected and saved by the cellular operators. In addition – many of these links are installed in areas where access is difficult such as orographic terrain and complex topography. As such, our method enables measurements in places that have been hard to measure in the past, or have never been measured before. The technique is restricted to weather conditions which exclude rain, fog or clouds along the propagation path. Strong winds that may cause movement of the link transmitter or receiver (or both) may also interfere with the ability to conduct accurate measurements. We present results from real-data measurements taken from two microwave links used in a backhaul cellular network that show convincing correlation to surface station humidity measurements. The measurements were taken daily in two sites, one in northern Israel (28 measurements), the other in central Israel (29 measurements). The correlation between the microwave link measurements and the humidity gauges were 0.9 and 0.82 for the north and central sites, respectively. The Root Mean Square Differences (RMSD) were 1.8 g/m 3 and 3.4 g/m 3 for the northern and central site measurements, respectively. <s> BIB003 </s> Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects <s> C. Environmental Studies <s> The application of sensor technology has brought considerable interest in the area of image fusion. Written by leading experts in the field, this book brings together in one volume the most recent algorithms, design techniques and applications in the topical field of image fusion. The applications are drawn from military, medical and civilian areas and give practical advice and pointers to the development of future applications in a variety of fields.This book will be an invaluable resource to R&D engineers, academic researchers and system developers requiring the most up-to-date and complete information on image fusion algorithms, design architectures and applications.*Brings together the latest algorithms, design techniques and applications in the hot area of Image Fusion*A large number of applications from military, medical and civilian fields give practical advice on how to develop future applications.* Combines theory and practice to create a unique point of reference <s> BIB004 </s> Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects <s> C. Environmental Studies <s> Coupled non-negative matrix factorization (CNMF) is applied to hyperspectral, multispectral, and panchromatic data fusion. This unmixing based method extracts and fuses hyperspectral endmember spectra and high-spatial-resolution abundance maps using these three data. An experiment with the synthetic data simulating ALOS-3 (advanced land observing satellite 3) dataset shows that the CNMF method has a possibility to produce fused data which have both high spatial and spectral resolutions with smaller spectral distortion. <s> BIB005 </s> Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects <s> C. Environmental Studies <s> The 2009-2010 Data Fusion Contest organized by the Data Fusion Technical Committee of the IEEE Geoscience and Remote Sensing Society was focused on the detection of flooded areas using multi-temporal and multi-modal images. Both high spatial resolution optical and synthetic aperture radar data were provided. The goal was not only to identify the best algorithms (in terms of accuracy), but also to investigate the further improvement derived from decision fusion. This paper presents the four awarded algorithms and the conclusions of the contest, investigating both supervised and unsupervised methods and the use of multi-modal data for flood detection. Interestingly, a simple unsupervised change detection method provided similar accuracy as supervised approaches, and a digital elevation model-based predictive method yielded a comparable projected change detection map without using post-event data. <s> BIB006 </s> Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects <s> C. Environmental Studies <s> We present cosmological parameter constraints based on the final nine-year WMAP data, in conjunction with additional cosmological data sets. The WMAP data alone, and in combination, continue to be remarkably well fit by a six-parameter LCDM model. When WMAP data are combined with measurements of the high-l CMB anisotropy, the BAO scale, and the Hubble constant, the densities, Omegabh2, Omegach2, and Omega_L, are each determined to a precision of ~1.5%. The amplitude of the primordial spectrum is measured to within 3%, and there is now evidence for a tilt in the primordial spectrum at the 5sigma level, confirming the first detection of tilt based on the five-year WMAP data. At the end of the WMAP mission, the nine-year data decrease the allowable volume of the six-dimensional LCDM parameter space by a factor of 68,000 relative to pre-WMAP measurements. We investigate a number of data combinations and show that their LCDM parameter fits are consistent. New limits on deviations from the six-parameter model are presented, for example: the fractional contribution of tensor modes is limited to r<0.13 (95% CL); the spatial curvature parameter is limited to -0.0027 (+0.0039/-0.0038); the summed mass of neutrinos is<0.44 eV (95% CL); and the number of relativistic species is found to be 3.84+/-0.40 when the full data are analyzed. The joint constraint on Neff and the primordial helium abundance agrees with the prediction of standard Big Bang nucleosynthesis. We compare recent PLANCK measurements of the Sunyaev-Zel'dovich effect with our seven-year measurements, and show their mutual agreement. Our analysis of the polarization pattern around temperature extrema is updated. This confirms a fundamental prediction of the standard cosmological model and provides a striking illustration of acoustic oscillations and adiabatic initial conditions in the early universe. <s> BIB007 </s> Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects <s> C. Environmental Studies <s> The 2012 Data Fusion Contest organized by the Data Fusion Technical Committee (DFTC) of the IEEE Geoscience and Remote Sensing Society (GRSS) aimed at investigating the potential use of very high spatial resolution (VHR) multi-modal/multi-temporal image fusion. Three different types of data sets, including spaceborne multi-spectral, spaceborne synthetic aperture radar (SAR), and airborne light detection and ranging (LiDAR) data collected over the downtown San Francisco area were distributed during the Contest. This paper highlights the three awarded research contributions which investigate (i) a new metric to assess urban density (UD) from multi-spectral and LiDAR data, (ii) simulation-based techniques to jointly use SAR and LiDAR data for image interpretation and change detection, and (iii) radiosity methods to improve surface reflectance retrievals of optical data in complex illumination environments. In particular, they demonstrate the usefulness of LiDAR data when fused with optical or SAR data. We believe these interesting investigations will stimulate further research in the related areas. <s> BIB008 </s> Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects <s> C. Environmental Studies <s> This paper presents the first cosmological results based on Planck measurements of the cosmic microwave background (CMB) temperature and lensing-potential power spectra. We find that the Planck spectra at high multipoles (l greater than or similar to 40) are extremely well described by the standard spatially-flat six-parameter ACDM cosmology with a power-law spectrum of adiabatic scalar perturbations. Within the context of this cosmology, the Planck data determine the cosmological parameters to high precision: the angular size of the sound horizon at recombination, the physical densities of baryons and cold dark matter, and the scalar spectral index are estimated to be theta* = (1.04147 +/- 0.00062) x 10(-2), Omega(b)h(2) = 0.02205 +/- 0.00028, Omega(c)h(2) = 0.1199 +/- 0.0027, and n(s) = 0.9603 +/- 0.0073, respectively (note that in this abstract we quote 68% errors on measured parameters and 95% upper limits on other parameters). For this cosmology, we find a low value of the Hubble constant, H-0 = (67.3 +/- 1.2) km s(-1) Mpc(-1), and a high value of the matter density parameter, Omega(m) = 0.315 +/- 0.017. These values are in tension with recent direct measurements of H-0 and the magnitude-redshift relation for Type Ia supernovae, but are in excellent agreement with geometrical constraints from baryon acoustic oscillation (BAO) surveys. Including curvature, we find that the Universe is consistent with spatial flatness to percent level precision using Planck CMB data alone. We use high-resolution CMB data together with Planck to provide greater control on extragalactic foreground components in an investigation of extensions to the six-parameter ACDM model. We present selected results from a large grid of cosmological models, using a range of additional astrophysical data sets in addition to Planck and high-resolution CMB data. None of these models are favoured over the standard six-parameter ACDM cosmology. The deviation of the scalar spectral index from unity is insensitive to the addition of tensor modes and to changes in the matter content of the Universe. We find an upper limit of r(0.002) < 0.11 on the tensor-to-scalar ratio. There is no evidence for additional neutrino-like relativistic particles beyond the three families of neutrinos in the standard model. Using BAO and CMB data, we find N-eff = 3.30 +/- 0.27 for the effective number of relativistic degrees of freedom, and an upper limit of 0.23 eV for the sum of neutrino masses. Our results are in excellent agreement with big bang nucleosynthesis and the standard value of N-eff = 3.046. We find no evidence for dynamical dark energy; using BAO and CMB data, the dark energy equation of state parameter is constrained to be w = -1.13(-0.10)(+0.13). We also use the Planck data to set limits on a possible variation of the fine-structure constant, dark matter annihilation and primordial magnetic fields. Despite the success of the six-parameter ACDM model in describing the Planck data at high multipoles, we note that this cosmology does not provide a good fit to the temperature power spectrum at low multipoles. The unusual shape of the spectrum in the multipole range 20 less than or similar to l less than or similar to 40 was seen previously in the WMAP data and is a real feature of the primordial CMB anisotropies. The poor fit to the spectrum at low multipoles is not of decisive significance, but is an "anomaly" in an otherwise self-consistent analysis of the Planck temperature data. <s> BIB009 </s> Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects <s> C. Environmental Studies <s> The 2013 Data Fusion Contest organized by the Data Fusion Technical Committee (DFTC) of the IEEE Geoscience and Remote Sensing Society aimed at investigating the synergistic use of hyperspectral and Light Detection And Ranging (LiDAR) data. The data sets distributed to the participants during the Contest, a hyperspectral imagery and the corresponding LiDAR-derived digital surface model (DSM), were acquired by the NSF-funded Center for Airborne Laser Mapping over the University of Houston campus and its neighboring area in the summer of 2012. This paper highlights the two awarded research contributions, which investigated different approaches for the fusion of hyperspectral and LiDAR data, including a combined unsupervised and supervised classification scheme, and a graph-based method for the fusion of spectral, spatial, and elevation information. <s> BIB010 </s> Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects <s> C. Environmental Studies <s> Abstract. One of the main challenges for meteorological and hydrological modelling is accurate rainfall measurement and mapping across time and space. To date, the most effective methods for large-scale rainfall estimates are radar, satellites, and, more recently, received signal level (RSL) measurements derived from commercial microwave networks (CMNs). While these methods provide improved spatial resolution over traditional rain gauges, they have their limitations as well. For example, wireless CMNs, which are comprised of microwave links (ML), are dependant upon existing infrastructure and the ML' arbitrary distribution in space. Radar, on the other hand, is known in its limitation for accurately estimating rainfall in urban regions, clutter areas and distant locations. In this paper the pros and cons of the radar and ML methods are considered in order to develop a new algorithm for improving rainfall measurement and mapping, which is based on data fusion of the different sources. The integration is based on an optimal weighted average of the two data sets, taking into account location, number of links, rainfall intensity and time step. Our results indicate that, by using the proposed new method, we not only generate more accurate 2-D rainfall reconstructions, compared with actual rain intensities in space, but also the reconstructed maps are extended to the maximum coverage area. By inspecting three significant rain events, we show that our method outperforms CMNs or the radar alone in rain rate estimation, almost uniformly, both for instantaneous spatial measurements, as well as in calculating total accumulated rainfall. These new improved 2-D rainfall maps, as well as the accurate rainfall measurements over large areas at sub-hourly timescales, will allow for improved understanding, initialization, and calibration of hydrological and meteorological models mainly necessary for water resource management and planning. <s> BIB011 </s> Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects <s> C. Environmental Studies <s> Aims. We present cosmological constraints from a joint analysis of type Ia supernova (SN Ia) observations obtained by the SDSS-II and SNLS collaborations. The dataset includes several low-redshift samples (z< 0.1), all three seasons from the SDSS-II (0.05 <z< 0.4), and three years from SNLS (0.2 <z< 1), and it totals 740 spectroscopically confirmed type Ia supernovae with high-quality light curves. ::: ::: Methods. We followed the methods and assumptions of the SNLS three-year data analysis except for the following important improvements: 1) the addition of the full SDSS-II spectroscopically-confirmed SN Ia sample in both the training of the SALT2 light-curve model and in the Hubble diagram analysis (374 SNe); 2) intercalibration of the SNLS and SDSS surveys and reduced systematic uncertainties in the photometric calibration, performed blindly with respect to the cosmology analysis; and 3) a thorough investigation of systematic errors associated with the SALT2 modeling of SN Ia light curves. ::: ::: Results. We produce recalibrated SN Ia light curves and associated distances for the SDSS-II and SNLS samples. The large SDSS-II sample provides an effective, independent, low-z anchor for the Hubble diagram and reduces the systematic error from calibration systematics in the low-z SN sample. For a flat ΛCDM cosmology, we find Ωm =0.295 ± 0.034 (stat+sys), a value consistent with the most recent cosmic microwave background (CMB) measurement from the Planck and WMAP experiments. Our result is 1.8σ (stat+sys) different than the previously published result of SNLS three-year data. The change is due primarily to improvements in the SNLS photometric calibration. When combined with CMB constraints, we measure a constant dark-energy equation of state parameter w =−1.018 ± 0.057 (stat+sys) for a flat universe. Adding baryon acoustic oscillation distance measurements gives similar constraints: w =−1.027 ± 0.055. Our supernova measurements provide the most stringent constraints to date on the nature of dark energy. <s> BIB012 </s> Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects <s> C. Environmental Studies <s> We present constraints on the parameters of the $\Lambda$CDM cosmological ::: model in the presence of massive neutrinos, using the one-dimensional ::: Ly$\alpha$ forest power spectrum obtained with the Baryon Oscillation ::: Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey (SDSS) by ::: Palanque-Delabrouille et al. (2013), complemented by additional cosmological ::: probes. The interpretation of the measured Ly$\alpha$ spectrum is done using a ::: second-order Taylor expansion of the simulated power spectrum. BOSS ::: Ly$\alpha$ data alone provide better bounds than previous Ly$\alpha$ results, ::: but are still poorly constraining, especially for the sum of neutrino masses ::: $\sum m_\nu$, for which we obtain an upper bound of 1.1~eV (95\% CL), including ::: systematics for both data and simulations. Ly$\alpha$ constraints on ::: $\Lambda$CDM parameters and neutrino masses are compatible with CMB bounds from ::: the Planck collaboration. Interestingly, the combination of Ly$\alpha$ with CMB ::: data reduces the uncertainties significantly, due to very different directions ::: of degeneracy in parameter space, leading to the strongest cosmological bound ::: to date on the total neutrino mass, $\sum m_\nu < 0.15$~eV at 95\% CL (with a ::: best-fit in zero). Adding recent BAO results further tightens this constraint ::: to $\sum m_\nu < 0.14$~eV at 95\% CL. This bound is nearly independent of the ::: statistical approach used, and of the different combinations of CMB and BAO ::: data sets considered in this paper in addition to Ly$\alpha$. Given the ::: measured values of the two squared mass differences $\Delta m^2$, this result ::: tends to favor the normal hierarchy scenario against the inverted hierarchy ::: scenario for the masses of the active neutrino species. <s> BIB013 </s> Multimodal Data Fusion: An Overview of Methods, Challenges, and Prospects <s> C. Environmental Studies <s> Pansharpening aims at fusing a multispectral and a panchromatic image, featuring the result of the processing with the spectral resolution of the former and the spatial resolution of the latter. In the last decades, many algorithms addressing this task have been presented in the literature. However, the lack of universally recognized evaluation criteria, available image data sets for benchmarking, and standardized implementations of the algorithms makes a thorough evaluation and comparison of the different pansharpening techniques difficult to achieve. In this paper, the authors attempt to fill this gap by providing a critical description and extensive comparisons of some of the main state-of-the-art pansharpening methods. In greater details, several pansharpening algorithms belonging to the component substitution or multiresolution analysis families are considered. Such techniques are evaluated through the two main protocols for the assessment of pansharpening results, i.e., based on the full- and reduced-resolution validations. Five data sets acquired by different satellites allow for a detailed comparison of the algorithms, characterization of their performances with respect to the different instruments, and consistency of the two validation procedures. In addition, the implementation of all the pansharpening techniques considered in this paper and the framework used for running the simulations, comprising the two validation procedures and the main assessment indexes, are collected in a MATLAB toolbox that is made available to the community. <s> BIB014
Example II-C.1: Remote Sensing and Earth Observations: Various sensor technologies can report on different aspects of objects on Earth. Passive optical hyperspectral (respectively, multispectral) imaging technologies report on material content of the surface by reconstructing its spectral characteristics from hundreds of (respectively, a few) narrow (respectively, broad) adjacent spectral bands within the visible range and beyond. A third type of an optical sensor is panchromatic imaging, which generates a monochromatic image with a much broader band. Typical spatial resolutions of hyperspectral, multispectral, and panchromatic images are tens of meters, a few meters, and less than one meter, respectively. Hence, there exists a tradeoff between spectral and spatial resolution BIB004 Ch. 9] , BIB005 , BIB014 . Topographic information can be acquired from active sensors such as light detection and ranging (LiDAR) and synthetic aperture radar (SAR). LiDAR is based on a narrow pulsed laser beam and thus provides highly accurate information about distance to objects, i.e., altitude. SAR is based on radio waves that illuminate a rather wide area, and the backscattered components reaching the sensor are registered; interpreting the reflections from the surface requires some additional processing with respect to (w.r.t.) LiDAR. Both technologies can provide information about elevation, 3-D structure of the observed objects, and their surface properties. LiDAR, being based on a laser beam, generally reports on the structure of the surface, although it can partially penetrate through certain areas such as forest canopy, providing information on the internal structure of the trees, for example. This ability is a mixed blessing, however, since it generates reflections that have to be accounted for. SAR and LiDAR use different electromagnetic frequencies and thus interact differently with materials and surfaces. As an example, depending on the wavelength, SAR may see the canopy as a transparent object (waves reach the soil under the canopy), a semitransparent object (they penetrate the canopy and interact with it) or an opaque object (they are reflected by the top of the canopy). Optical techniques are passive, which implies that they rely on natural illumination. Active sensors such as LiDAR and SAR can operate at night and in shaded areas BIB008 . Beyond the strengths and weaknesses of each technology w.r.t. the others, the use of each is limited by a certain inherent ambiguity. For example, hyperspectral imaging cannot distinguish between objects made of the same material that are positioned at different elevations, such as concrete roofs and roads. LiDAR cannot distinguish between objects with the same elevation and surface roughness that are made of different materials such as natural and artificial grass BIB010 . SAR images may sometimes be difficult to interpret due to their complex dependence on the geometry of the surface BIB008 . In real-life conditions, interpretability of the observations of one modality may be difficult without additional information. For example, in hyperspectral imaging, on a flat surface, reflected light depends on the abundance (proportion of a material in a pixel) and on the endmember (pure material present in a pixel) reflectance. In a nonflat surface, the reflected light depends also on the topography, which may induce variations in scene illumination and scattering. Therefore, in nonflat conditions, one cannot accurately extract material content information from optical data alone. Adding a modality that reports on the topography, such as LiDAR, is necessary to resolve spectra accurately  . As an active initiative, we point out the yearly data fusion contest of the IEEE Geoscience and Remote Sensing Society (GRSS) (see dedicated paper in this issue  ). Problems addressed include multimodal change detection, in which the purpose is to detect changes in an area before and after an event (a flood, in this case), given SAR and multispectral imaging, using either all or part of the modalities BIB006 ; multimodal multitemporal data fusion of optical, SAR, and LiDAR images taken at different years over the same urban area, where suggested applications include assessing urban density, change detection and overcoming adverse illumination conditions for optical sensors BIB008 ; and proposing new methods for fusing hyperspectral and LiDAR data of the same area, e.g., for improved classification of objects BIB010 . Example II-C.2: Meteorological Monitoring: Accurate measurements of atmospheric phenomena such as rain, water vapor, dew, fog, and snow are required for meteorological analysis and forecasting, as well as for numerous applications in hydrology, agriculture, and aeronautical services. Data can be acquired from various devices such as rain gauges, radars, satellite-borne remote sensing devices (see Example II-C.1), and recently also by exploiting existing commercial microwave links BIB002 . Rain gauges, as an example, are simply cups that collect the precipitation. Albeit the most direct and reliable technique, their small sampling area implies very localized representativeness and thus poor spatial resolution (e.g., BIB002 and BIB011 ). Rain gauges may be read automatically at intervals as short as seconds. Satellites observe Earth at different frequencies, including visible, microwave, infrared, and shortwave infrared to report on various atmospheric phenomena such as water vapor content and temperature. The accuracy of radar rainfall estimation may be affected by topography, beam effects, distance from the radar, and other complicating factors. Radars and satellite systems provide large spatial coverage; however, they are less accurate in measuring precipitation at ground level (e.g.,  ). Microwave links are deployed by cellular providers for backhaul communication between base stations. The signals transmitted by the base stations are influenced by various atmospheric phenomena (e.g., BIB003 ), primarily attenuation due to rainfall BIB002 , BIB011 . These changes in signal strength are recorded at predefined time intervals and kept in the cellular provider's logs. Hence, the precipitation data is in fact a ''reverse engineering'' of this information. The microwave links' measurements provide average precipitation on the entire link and close to ground level BIB002 . Altogether, these technologies are largely complementary in their ability to detect and distinguish between different meteorological phenomena, spatial coverage, temporal resolution, measurement error, and other properties. Therefore, meteorological data are often combined for better accuracy, coverage and resolution; see, e.g.,  , BIB011 ,  , and references therein. Example II-C.3: Cosmology: A major endeavour in astronomy and astrophysics is understanding the formation of our Universe. Recent results include robust support for the six-parameter standard model of cosmology, of a Universe dominated by Cold Dark Matter and a cosmological constant L, known as LCDM  , BIB007 . The purpose of ongoing and planned sky surveys is to decrease the allowable uncertainty volume of the six-dimensional LCDM parameter space and to improve the constraints on the other cosmological parameters that depend on it BIB007 . The goal is to validate (or disprove) the standard model. A major difficulty in astrophysics and cosmology is the absence of ground truth. This is because cosmological processes involve very high energies, masses, large space and time scales that make experimental study prohibitive. The lack of ground truth and experimental support implied that, from its very beginning, cosmological research had to rely on cross validation of outcomes of different observations, numerical simulations, and theoretical analysis; in other words, data fusion. A complicating factor associated with this task is the fact that in many types of inferences, for all practical purposes, we have only one realization of the Universe. This means that even if we make statistical hypotheses about underlying processes, there is still only one sample. This fact induces an uncertainty called ''cosmic variance'' that cannot be accommodated by improving the measurement precision. Despite its simplicity, the LCDM model has proved to be successful in describing a wide range of cosmological data BIB009 . In particular, it is predicted that its six parameters can fully explain the angular power spectra of the temperature and polarization fluctuations of the cosmic microwave background radiation (CMB). Therefore, since the first experimental discovery of the CMB in 1965 BIB001 , there has been an ongoing effort to obtain better and more accurate measurements of these fluctuations. A severe problem in validating the LCDM model from CMB observations is known as ''parameter degeneracy.'' Although the CMB power spectrum can be fully explained by the standard model, this relationship is not unique in the sense that the same measured CMB power spectrum can be explained by other models, not only LCDM. These degeneracies can be broken by combining CMB observations with other cosmological data. While CMB corresponds to photons released about 300 000 years after the Big Bang, the same parameters that controlled the evolution of the early Universe continue to influence its matter distribution and expansion rate to our very days. Therefore, other measures, such as redshift from certain types of supernovae, angular and radial baryon acoustic oscillation scales that can be derived from galaxy surveys, galaxy clustering BIB012 , BIB013 , and stacked gravitational lensing, also serve as important cosmological probes BIB007 , BIB009 . Since the cosmological parameters that determine the evolution of the early Universe are the same as those that control high-energy physics, cosmological observations are fused and cross validated with experimental outcomes such as the Large Hadron Collider Higgs data  .