Retrieval of canopy component temperatures through Bayesian inversion of directional thermal measurements

Evapotranspiration is usually estimated in remote sensing from single temperature value representing both soil and vegetation. This surface temperature is an aggregate over multiple canopy components. The temperature of the individual components can differ significantly, introducing errors in the evapotranspiration estimations. The temperature aggregate has a high level of directionality. An inversion method is presented in this paper to retrieve four canopy component temperatures from directional brightness temperatures. The Bayesian method uses both a priori information and sensor characteristics to solve the ill-posed inversion problem. The method is tested using two case studies: 1) a sensitivity analysis, using a large forward simulated dataset, and 2) in a reality study, using two datasets of two field campaigns. The results of the sensitivity analysis show that the Bayesian approach is able to retrieve the four component temperatures from directional brightness temperatures with good success rates using multi-directional sensors (Srspectra˜0.3, Srgonio˜0.3, and SrAATSR˜0.5), and no improvement using mono-angular sensors (Sr˜1). The results of the experimental study show that the approach gives good results for high LAI values (RMSEgrass=0.50 K, RMSEwheat=0.29 K, RMSEsugar beet=0.75 K, RMSEbarley=0.67 K); but for low LAI values the results were unsatisfactory (RMSEyoung maize=2.85 K). This discrepancy was found to originate from the presence of the metallic construction of the setup. As these disturbances, were only present for two crops and were not present in the sensitivity analysis, which had a low LAI, it is concluded that using masked thermal images will eliminate this discrepanc

Technique for validating remote sensing products of water quality

Remote sensing of water quality is initiated as an additional part of the on going activities of the EAGLE2006 project. Within this context intensive in-situ and airborne measurements campaigns were carried out over the Wolderwijd and Veluwemeer natural waters. However, in-situ measurements and image acquisitions were not simultaneous. This poses some constraints on validating air/space-borne remote sensing products of water quality. Nevertheless, the detailed insitu measurements and hydro-optical model simulations provide a bench mark for validating remote sensing products. That is realized through developing a stochastic technique to quantify the uncertainties on the retrieved aquatic inherent optical properties (IOP). The output of the proposed technique is applied to validate remote sensing products of water quality. In this processing phase, simulations of the radiative transfer in the coupled atmosphere-water system are performed to generate spectra at-sensor-level. The upper and the lower boundaries of perturbations, around each recorded spectrum, are then modelled as function of residuals between simulated and measured spectra. The perturbations are parameterized as a function of model approximations/inversion, sensor-noise and atmospheric residual signal. All error sources are treated as being of stochastic nature. Three scenarios are considered: spectrally correlated (i.e. wavelength dependent) perturbations, spectrally uncorrelated perturbations and a mixed scenario of the previous two with equal probability of occurrence. Uncertainties on the retrieved IOP are quantified with the relative contribution of each perturbation component to the total error budget of the IOP. This technique can be used to validate earth observation products of water quality in remote areas where few or no in– situ measurements are available

The Use of Mixed Methods for Therapeutic Massage Research

Mixed methods research is the integration of quantitative and qualitative components in a research project. Whether you are reading or designing a mixed methods research project, it is important to be familiar with both qualitative and quantitative research methods and the specific purposes for which they are brought together in a study: triangulation, complementarity, expansion, initiation, or development. In addition, decisions need to be made about the sequencing and the priority or importance of each qualitative and quantitative component relative to the other components, and the point or points at which the various qualitative and quantitative components will be integrated

A stochastic model of congestion caused by speed differences

The authors study interaction on a two-lane road between the trips of two types of drivers who differ by their desired speeds. The difference in desired speeds causes congestion, because slow vehicles force fast vehicles to reduce their speed. Results for this type of congestion with respect to tolling are very different from those of the classic Pigou--Knight model, where the marginal external costs are an increasing function of the number of road users. In our model we find the opposite result: the marginal external costs of slow vehicles are a decreasing function of the number of slow vehicles. This leads to rather different policy recommendations