Senegalese land surface change analysis and biophysical parameter estimation using NOAA AVHRR spectral data

Surface biophysical estimates were derived from analysis of NOAA Advanced Very High Spectral Resolution (AVHRR) spectral data of the Senegalese area of west Africa. The parameters derived were of solar albedo, spectral visible and near-infrared band reflectance, spectral vegetative index, and ground temperature. Wet and dry linked AVHRR scenes from 1981 through 1985 in Senegal were analyzed for a semi-wet southerly site near Tambacounda and a predominantly dry northerly site near Podor. Related problems were studied to convert satellite derived radiance to biophysical estimates of the land surface. Problems studied were associated with sensor miscalibration, atmospheric and aerosol spatial variability, surface anisotropy of reflected radiation, narrow satellite band reflectance to broad solar band conversion, and ground emissivity correction. The middle-infrared reflectance was approximated with a visible AVHRR reflectance for improving solar albedo estimates. In addition, the spectral composition of solar irradiance (direct and diffuse radiation) between major spectral regions (i.e., ultraviolet, visible, near-infrared, and middle-infrared) was found to be insensitive to changes in the clear sky atmospheric optical depth in the narrow band to solar band conversion procedure. Solar albedo derived estimates for both sites were not found to change markedly with significant antecedent precipitation events or correspondingly from increases in green leaf vegetation density. The bright soil/substrate contributed to a high albedo for the dry related scenes, whereas the high internal leaf reflectance in green vegetation canopies in the near-infrared contributed to high solar albedo for the wet related scenes. The relationship between solar albedo and ground temperature was poor, indicating the solar albedo has little control of the ground temperature. The normalized difference vegetation index (NDVI) and the derived visible reflectance were more sensitive to antecedent rainfall amounts and green vegetation changes than were near-infrared changes. The information in the NDVI related to green leaf density changes primarily was from the visible reflectance. The contribution of the near-infrared reflectance to explaining green vegetation is largely reduced when there is a bright substrate

Preliminary evidence for the influence of physiography and scale upon the autocorrelation function of remotely sensed data

Previously established results demonstrate that LANDSAT data are autocorrelated and can be described by a univariate linear stochastic process known as auto-regressive-integrated-moving-average model of degree 1, 0, 1 or ARIMA (1, 0, 1). This model has two coefficients of interest for interpretation phi(1) and theta(1). In a comparison of LANDSAT thematic mapper simulator (TMS) data and LANDSAT MSS data several results were established: (1) The form of the relatedness as described by this model is not dependent upon system look angle or pixel size. (2) The phi(1) coefficient increases with decreasing pixel size and increasing topographic complexity. (3) Changes in topography have a greater influence upon phi(1) than changes in land cover class. (4) The theta(1) seems to vary with the amount of atmospheric haze. These patterns of variation in phi(1) and theta(1) are potentially exploitable by the remote sensing community to yield stochastically independent sets of observations, characterize topography, and reduce the number of bytes needed to store remotely sensed data

The cosine law at the atomic scale: Toward realistic simulations of Knudsen diffusion

We propose to revisit the diffusion of atoms in the Knudsen regime in terms of a complex dynamical reflection process. By means of molecular dynamics simulation we emphasize the asymptotic nature of the cosine law of reflection at the atomic scale, and carefully analyze the resulting strong correlations in the reflection events. A dynamical interpretation of the accomodation coefficient associated to the slip at the wall interface is also proposed. Finally, we show that the first two moments of the stochastic process of reflection non uniformly depend on the incident angle

A model for alignment between microscopic rods and vorticity

Numerical simulations show that microscopic rod-like bodies suspended in a turbulent flow tend to align with the vorticity vector, rather than with the dominant eignevector of the strain-rate tensor. This paper investigates an analytically solvable limit of a model for alignment in a random velocity field with isotropic statistics. The vorticity varies very slowly and the isotropic random flow is equivalent to a pure strain with statistics which are axisymmetric about the direction of the vorticity. We analyse the alignment in a weakly fluctuating uniaxial strain field, as a function of the product of the strain relaxation time $\tau_{\rm s}$ and the angular velocity $\omega$ about the vorticity axis. We find that when $\omega\tau_{\rm s}\gg 1$, the rods are predominantly either perpendicular or parallel to the vorticity

Benchmarking Approach for Empirical Comparison of Pricing Models in DRMS

emand response management systems often involve the use of pricing schemes to motivate the efficient use of electrical power. Achieving this efficiency requires the detection of electrical power patterns. The detection of these patterns normally involves use of non-linear, quasi-non-linear, and at times linear data pattern detection models. The behavioural disparities of these models and specifically when used for a specific set of data make it hard to select the most efficient model. The contribution of this study is devising an empirical benchmark (reference) ( perfect ) control pricing (PCP) model through which various models are compared in order to select the most efficient model. In this study, the authors elect neural networks, sliding window–multiple linear regression, and a proportional controller models to be representative of non-linear, quasi-non-linear, and linear models, respectively, in order to demonstrate the effectiveness of PCP. The dataset used for demonstrating both the operation of PCP and the elected models for comparisons is collected from Green Button project and Pacific Gas and Electric

International food trade contributes to dietary risks and mortality at global, regional and national levels

Food trade is generally perceived to increase the availability and diversity of foods available to consumers, but there is little empirical evidence on its implications for human health. Here we show that a substantial proportion of dietary risks and diet-related mortality worldwide is attributable to international food trade and that whether the contributions of food trade are positive or negative depends on the types of food traded. Using bilateral trade data for 2019 and food-specific risk–disease relationships, we estimate that imports of fruits, vegetables, legumes and nuts improved dietary risks in the importing countries and were associated with a reduction in mortality from non-communicable diseases of ~1.4 million deaths globally. By contrast, imports of red meat aggravated dietary risks in the importing countries and were associated with an increase of ~150,000 deaths. The magnitude of our findings suggests that considering impacts on dietary risks will become an important aspect of health-sensitive trade and agriculture policies, and of policy responses to disruptions in food chains