A static uniaxial (drained) compression test procedure using effectively saturated, remoulded soil samples is proposed which unifies soil consistency limit determination procedurally under similar experimental conditions. It yields numerically comparative (r2 = 0.786–0.931), rather than only correlative, indices of the upper and lower limits of soil plasticity while providing ancillary information on the effective stress regime when in these states of consistency. For the 44 soil horizon samples used in this study, apparent equivalent stresses at the Atterberg consistency limits ranged from 0.26 to 1.84 MPa for the lower plastic limit and 3.9 to 268 kPa for the upper plastic limit. Clay and organic matter contents had a significant influence on defining these equivalent static loadings. Organic matter was further shown to expand the range of moisture contents representative of the semisolid consistency state while constricting the plastic range. Potential areas for improvement in the procedures are discussed.

Abstract. Rural agricultural areas in southern Ontario, Canada, with potential for aggregate extraction have become a focus of conflict over proposed land use change. Geophysical and soil physical field measurements were used to map soil variation for quantitative land evaluation at the farm level. Apparent electrical conductivity of terrain was shown to be strongly correlated with depth to the groundwater table on two separate test sites. A digital terrain model was used to create thematic maps of the predicted pre‐growing season soil water regime by contouring irregularly spaced electromagnetic survey and soil inspection points. Overlay analysis with a geographical information system (GIS) was used to produce an agricultural soil capability map for crop production. Adoption of a larger map scale provided significant refinement in detail over the published Canada Land Inventory soil capability ratings for agriculture, but both showed that Class 2 soils are dominant. The approach can improve the reproducibility of land capability assessments.

A closed-form solution for the bit error probability for an energy detection receiver using OnOff-Keying in a frequency selective multipath fading channel with zero-mean complex-normal distributed fading amplitudes is introduced. Independent and correlated fading are considered. The presented results are valid for for all kinds of frequency selective fading channels, especially ultra wideband channels, where the Gaussian assumption for the decision statistic and the flat fading assumption do not hold. I. IntroductionAnalysis of the detection performance of energy detectors has been started by Urkowitz in 1967 [1] considering a simple AWGN channel model. More recently, Kostylev [2], Digham [3], [4], Herath [5], [6] and Atapattu [7] concentrate on the flat fading channel.These channel models only fit for narrowband systems, where the transmitted signal bandwidth is much smaller than the channel's coherence bandwidth. A wideband system, for example an ultra-wideband (UWB) receiver, uses an extreme high bandwidth, collects many different reflections and requires a more general model for channel fading: the frequency-selective fading (FSF). The product of integration time and channel bandwidth equals equals the number of signal paths distinguishable by the receiver.An independent decay coefficient is assigned to each signal path. The vector of those decay coefficients, sorted by path arrival time, represents the samples of the channel impulse response.Given free choice of the distribution of each decay coefficient, one fit this channel model to observed systems with arbitrary power spectrum. Thus this fading model is called frequency-selective.Because of the simple design of energy detection receivers, this method has been used in cognitive radio systems to detect spectrum holes [8], [9] and to transmit data for different low and high data rate UWB receivers [10], [11] including location and tracking [12].In this paper we focus on UWB energy detection receivers in FSF channels. We do not use the Gaussian assumption to simplify the decision statistics [13] of the energy detection receiver, because we do not want to limit system parameters in order to fulfil the central limit theorem and we do not limit our result to flat fading channels.