Efficient Emulation of Radiative Transfer Codes Using Gaussian Processes and Application to Land Surface Parameter Inferences

There is an increasing need to consistently combine observations from different sensors to monitor the state of the land surface. In order to achieve this, robust methods based on the inversion of radiative transfer (RT) models can be used to interpret the satellite observations. This typically results in an inverse problem, but a major drawback of these methods is the computational complexity. We introduce the concept of Gaussian Process (GP) emulators: surrogate functions that accurately approximate RT models using a small set of input (e.g., leaf area index, leaf chlorophyll, etc.) and output (e.g., top-of-canopy reflectances or at sensor radiances) pairs. The emulators quantify the uncertainty of their approximation, and provide a fast and easy route to estimating the Jacobian of the original model, enabling the use of e.g., efficient gradient descent methods. We demonstrate the emulation of widely used RT models (PROSAIL and SEMIDISCRETE) and the coupling of vegetation and atmospheric (6S) RT models targetting particular sensor bands. A comparison with the full original model outputs shows that the emulators are a viable option to replace the original model, with negligible bias and discrepancies which are much smaller than the typical uncertainty in the observations. We also extend the theory of GP to cope with models with multivariate outputs (e.g., over the full solar reflective domain), and apply this to the emulation of PROSAIL, coupled 6S and PROSAIL and to the emulation of individual spectral components of 6S. In all cases, emulators successfully predict the full model output as well as accurately predict the gradient of the model calculated by finite differences, and produce speed ups between 10,000 and 50,000 times that of the original model. Finally, we use emulators to invert leaf area index ( L A I ), leaf chlorophyll content ( C a b ) and equivalent leaf water thickness ( C w ) from a time series of observations from Sentinel-2/MSI, Sentinel-3/SLSTR and Proba-V observations. We use sophisticated Hamiltonian Markov Chain Monte Carlo (MCMC) methods that exploit the speed of the emulators as well as the gradient estimation, a variational data assimilation (DA) method that extends the problem with temporal regularisation, and a particle filter using a regularisation model. The variational and particle filter approach appear more successful (meaning parameters closer to the truth, and smaller uncertainties) than the MCMC approach as a result of using the temporal regularisation mode. These work therefore suggests that GP emulators are a practical way to implement sophisticated parameter retrieval schemes in an era of increasing data volumes

Assimilation of remote sensing into crop growth models: Current status and perspectives

Timely monitoring of crop lands is important in order to make agricultural activities more sustainable, as well as ensuring food security. The use of Earth Observation (EO) data allows crop monitoring at a range of spatial scales, but can be hampered by limitations in the data. Crop growth modelling, on the other hand, can be used to simulate the physiological processes that result in crop development. Data assimilation (DA) provides a way of blending the monitoring properties of EO data with the predictive and explanatory abilities of crop growth models. In this paper, we first provide a critique of both the advantages and disadvantages of both EO data and crop growth models. We use this to introduce a solid and robust framework for DA, where different DA methods are shown to be derived from taking different assumptions in solving for the a posteriori probability density function (pdf) using Bayes’ rule. This treatment allows us to provide some recommendation on the choice of DA method for particular applications. We comment on current computational challenges in scaling DA applications to large spatial scales. Future areas of research are sketched, with an emphasis on DA as an enabler for blending different observations, as well as facilitating different approaches to crop growth models. We have illustrated this review with a large number of examples from the literature

A new implicit review instrument for measuring quality of care delivered to pediatric patients in the emergency department

BackgroundThere are few outcomes experienced by children receiving care in the Emergency Department (ED) that are amenable to measuring for the purposes of assessing of quality of care. The purpose of this study was to develop, test, and validate a new implicit review instrument that measures quality of care delivered to children in EDs.MethodsWe developed a 7-point structured implicit review instrument that encompasses four aspects of care, including the physician's initial data gathering, integration of information and development of appropriate diagnoses; initial treatment plan and orders; and plan for disposition and follow-up. Two pediatric emergency medicine physicians applied the 5-item instrument to children presenting in the highest triage category to four rural EDs, and we assessed the reliability of the average summary scores (possible range of 5-35) across the two reviewers using standard measures. We also validated the instrument by comparing this mean summary score between those with and without medication errors (ascertained independently by two pharmacists) using a two-sample t-test.ResultsWe reviewed the medical records of 178 pediatric patients for the study. The mean and median summary score for this cohort of patients were 27.4 and 28.5, respectively. Internal consistency was high (Cronbach's alpha of 0.92 and 0.89). All items showed a significant (p < 0.005) positive correlation between reviewers using the Spearman rank correlation (range 0.24 to 0.39). Exact agreement on individual items between reviewers ranged from 70.2% to 85.4%. The Intra-class Correlation Coefficient for the mean of the total summary score across the two reviewers was 0.65. The validity of the instrument was supported by the finding of a higher score for children without medication errors compared to those with medication errors which trended toward significance (mean score = 28.5 vs. 26.0, p = 0.076).ConclusionThe instrument we developed to measure quality of care provided to children in the ED has high internal consistency, fair to good inter-rater reliability and inter-rater correlation, and high content validity. The validity of the instrument is supported by the fact that the instrument's average summary score was lower in the presence of medication errors, which trended towards statistical significance

Appropriateness of antibiotic treatment in intravenous drug users, a retrospective analysis

<p>Abstract</p> <p>Background</p> <p>Infectious disease is often the reason for intravenous drug users being seen in a clinical setting. The objective of this study was to evaluate the appropriateness of treatment and outcomes for this patient population in a hospital setting.</p> <p>Methods</p> <p>Retrospective study of all intravenous drug users hospitalized for treatment of infectious diseases and seen by infectious diseases specialists 1/2001–12/2006 at a university hospital. Treatment was administered according to guidelines when possible or to alternative treatment program in case of patients for whom adherence to standard protocols was not possible. Outcomes were defined with respect to appropriateness of treatment, hospital readmission, relapse and mortality rates. For statistical analysis adjustment for multiple hospitalizations of individual patients was made by using a generalized estimating equation.</p> <p>Results</p> <p>The total number of hospitalizations for infectious diseases was 344 among 216 intravenous drug users. Skin and soft tissue infections (n = 129, 37.5% of hospitalizations), pneumonia (n = 75, 21.8%) and endocarditis (n = 54, 15.7%) were most prevalent. Multiple infections were present in 25%. Treatment was according to standard guidelines for 78.5%, according to an alternative recommended program for 11.3%, and not according to guidelines or by the infectious diseases specialist advice for 10.2% of hospitalizations. Psychiatric disorders had a significant negative impact on compliance (compliance problems in 19.8% of hospitalizations) in multiple logistic regression analysis (OR = 2.4, CI 1.1–5.1, p = 0.03). The overall readmission rate and relapse rate within 30 days was 13.7% and 3.8%, respectively. Both non-compliant patient behavior (OR = 3.7, CI 1.3–10.8, p = 0.02) and non-adherence to treatment guidelines (OR = 3.3, CI 1.1–9.7, p = 0.03) were associated with a significant increase in the relapse rate in univariate analysis. In 590 person-years of follow-up, 24.6% of the patients died: 6.4% died during hospitalization (1.2% infection-related) and 13.6% of patients died after discharge.</p> <p>Conclusion</p> <p>Appropriate antibiotic therapy according to standard guidelines in hospitalized intravenous drug users is generally practicable and successful. In a minority alternative treatments may be indicated, although associated with a higher risk of relapse.</p

Retrieval and global assessment of terrestrial chlorophyll fluorescence from GOSAT space measurements

The recent advent of very high spectral resolution measurements by the Fourier Transform Spectrometer (FTS) on board the Greenhouse gases Observing SATellite (GOSAT) platform has made possible the retrieval of sun-induced terrestrial chlorophyll fluorescence (F s) on a global scale. The basis for this retrieval is the modeling of the in-filling of solar Fraunhofer lines by fluorescence. This contribution to the field of space-based carbon cycle science presents an alternative method for the retrieval of F s from the Fraunhofer lines resolved by GOSAT-FTS measurements. The method is based on a linear forward model derived by a singular vector decomposition technique, which enables a fast and robust inversion of top-of-atmosphere radiance spectra. Retrievals are performed in two spectral micro-windows (~2-3nm width) containing several strong Fraunhofer lines. The statistical nature of this approach allows to avoid potential retrieval errors associated with the modeling of the instrument line shape or with a given extraterrestrial solar irradiance data set. The method has been tested on 22 consecutive months of global GOSAT-FTS measurements. The fundamental basis of this F s retrieval approach and the results from the analysis of the global F s data set produced with it are described in this work. Among other findings, the data analysis has shown (i) a very good comparison of F s intensity levels and spatial patterns with the state-of-the-art physically-based F s retrieval approach described in Frankenberg et al. (2011a), (ii) the overall good agreement between F s annual and seasonal patterns and other space-based vegetation parameters, (iii) the need for a biome-dependent scaling from F s to gross primary production, and (iv) the apparent existence of strong directional effects in the F s emission from forest canopies. These results reinforce the confidence in the feasibility of F s retrievals with GOSAT-FTS and open several points for future research in this emerging field. © 2012 Elsevier Inc