Search results for " statistics"
showing 10 items of 1891 documents
Joint Gaussian processes for inverse modeling
2017
Solving inverse problems is central in geosciences and remote sensing. Very often a mechanistic physical model of the system exists that solves the forward problem. Inverting the implied radiative transfer model (RTM) equations numerically implies, however, challenging and computationally demanding problems. Statistical models tackle the inverse problem and predict the biophysical parameter of interest from radiance data, exploiting either in situ data or simulated data from an RTM. We introduce a novel nonlinear and nonparametric statistical inversion model which incorporates both real observations and RTM-simulated data. The proposed Joint Gaussian Process (JGP) provides a solid framework…
Estimating “land use heritage” to model changes in archaeological settlement patterns
2016
International audience; In this paper, we present a method to calculate a “land use heritage map” based on the concept of “memory of landscape”. Such a map can be seen as one variable among others influencing site location preference, and can be used as input for predictive models. The computed values equate to an index of long-term land use intensity. We will first discuss the method used for creating the land use heritage map, for which kernel density estimates are used.We will then present the use of these land use heritage maps for site location analysis in two study areas in SE France. Earlier analyses showed that the influence of the natural environment on settlement location choice i…
« On-the-go » multispectral imaging system to characterize the development of vineyard foliage
2015
International audience; In Precision Viticulture, multispectral imaging systems are currently used in remote sensing for vineyard vigor characterization but few are employed in proximal sensing. This work presents the potential of a proximal multispectral imaging system mounted on a track-laying tractor equipped with a Greenseeker RT-100 to provide an NDVI index. The camera acquired visible and near-infrared images which were calibrated in reflectance. Vegetation indices were computed and compared to Greenseeker data. From two of the resulting datasets, a spatio-temporal study of foliage description through both optical systems is presented. This first study assessed the proximal imagery re…
Shape, size, and quantity of ingested external abrasives influence dental microwear texture formation in guinea pigs
2020
Food processing wears down teeth, thus affecting tooth functionality and evolutionary success. Other than intrinsic silica phytoliths, extrinsic mineral dust/grit adhering to plants causes tooth wear in mammalian herbivores. Dental microwear texture analysis (DMTA) is widely applied to infer diet from microscopic dental wear traces. The relationship between external abrasives and dental microwear texture (DMT) formation remains elusive. Feeding experiments with sheep have shown negligible effects of dust-laden grass and browse, suggesting that intrinsic properties of plants are more important. Here, we explore the effect of clay- to sand-sized mineral abrasives (quartz, volcanic ash, loess,…
gllvm: Fast analysis of multivariate abundance data with generalized linear latent variable models inr
2019
The work of J.N. was supported by the Wihuri Foundation. The work of S.T. was supported by the CRoNoS COST Action IC1408.F.K.C.H. was also supported by an ANU cross disciplinary grant.
Calibrating Expert Assessments Using Hierarchical Gaussian Process Models
2020
Expert assessments are routinely used to inform management and other decision making. However, often these assessments contain considerable biases and uncertainties for which reason they should be calibrated if possible. Moreover, coherently combining multiple expert assessments into one estimate poses a long-standing problem in statistics since modeling expert knowledge is often difficult. Here, we present a hierarchical Bayesian model for expert calibration in a task of estimating a continuous univariate parameter. The model allows experts' biases to vary as a function of the true value of the parameter and according to the expert's background. We follow the fully Bayesian approach (the s…
The past and the present in decision-making: the use of conspecific and heterospecific cues in nest site selection
2014
International audience; Nest site selection significantly affects fitness, so adaptations for assessment of the qualities of available sites are expected. The assessment may be based on personal or social information, the latter referring to the observed location and performance of both conspecific and heterospecific individuals. Contrary to large-scale breeding habitat selection, small-scale nest site selection within habitat patches is insufficiently understood. We analyzed nest site selection in the migratory Collared Flycatcher Ficedula albicollis in relation to present and past cues provided by conspecifics and by resident tits within habitat patches by using long-term data. Collared F…
Potential of using data assimilation to support forest planning
2017
Uncertainty in forest information typically results in economic and ecological losses as a consequence of suboptimal management decisions. Several techniques have been proposed to handle such uncertainties. However, these techniques are often complex and costly. Data assimilation (DA) has recently been advocated as a tool that may reduce the uncertainty, thereby improving the quality of forest planning results. It offers an opportunity to make use of all new sources of information in a systematic way and thus provides more accurate and up-to-date information to forest planning. In this study, we refer to literature on handling uncertainties in forest planning, as well as related literature…
Incorporating Biotic Information in Species Distribution Models: A Coregionalized Approach
2021
In this work, we discuss the use of a methodological approach for modelling spatial relationships among species by means of a Bayesian spatial coregionalized model. Inference and prediction is performed using the integrated nested Laplace approximation methodology to reduce the computational burden. We illustrate the performance of the coregionalized model in species interaction scenarios using both simulated and real data. The simulation demonstrates the better predictive performance of the coregionalized model with respect to the univariate models. The case study focus on the spatial distribution of a prey species, the European anchovy (Engraulis encrasicolus), and one of its predator spe…
Unsupervised Classification of Acoustic Echoes from Two Krill Species in the Southern Ocean (Ross Sea)
2021
This work presents a computational methodology able to automatically classify the echoes of two krill species recorded in the Ross sea employing scientific echo-sounder at three different frequencies (38, 120 and 200 kHz). The goal of classifying the gregarious species represents a time-consuming task and is accomplished by using differences and/or thresholds estimated on the energy features of the insonified targets. Conversely, our methodology takes into account energy, morphological and depth features of echo data, acquired at different frequencies. Internal validation indices of clustering were used to verify the ability of the clustering in recognizing the correct number of species. Th…