Remote sensing: the use of polarized visible light (PVL) to estimate surface soil moisture

Sunlight is unpolarized; if it is reflected from a soil surface it will become partially polarized. The degree of polarization will be dependent upon the soil surface roughness and moisture content. The study of polarized visible light (PVL) reflectance has developed in the past two decades, from the use of a non-imaging photometer-polarimeter to record the surface roughness of laboratory samples, to the use of a camera and polarizing filter to estimate surface soil moisture in the field. It is demonstrated that PVL recorded at a high phase angle, from up to light aircraft altitudes, can successfully estimate surface soil moisture. This is possible regardless of solar angle, soil albedo or soil slope, over a wide but not umlimited range of surface soil moisture states, but only if surface disturbance and cloud cover are minimized.While PVL cannot, in general, rival currently available techniques for the remote sensing of surface soil moisture it is eminently suitable where an estimate of surface soil moisture is required at low cost for a small area.     

Are the missing X-ray breaks in gamma-ray burst afterglow light curves merely hidden?

Gamma-ray burst (GRB) afterglow observations in the Swift era have a perceived lack of achromatic jet breaks compared to the BeppoSAX or pre- Swift era. Specifically, relatively few breaks, consistent with jet breaks, are observed in the X-ray light curves of these bursts. If these breaks are truly missing, it has serious consequences on the interpretation of GRB jet collimation and energy requirements, and the use of GRBs as cosmological tools. Here, we address the issue of X-ray breaks that are possibly 'hidden' and hence the light curves are misinterpreted as being single power laws. We do so by synthesizing X-ray telescope (XRT) light curves and fitting both single and broken power laws, and comparing the relative goodness of each fit via Monte Carlo analysis. Even with the well-sampled light curves of the Swift era, these breaks may be left misidentified, hence caution is required when making definite statements on the absence of achromatic breaks.     

Measuring Community and University Impacts of Critical Civic Geography: Insights from Chicago

Geographers have increasingly adopted community-based learning and research into their teaching and scholarly activities since Bunge and Harvey called for an applied public geography that is both useful and challenges societal inequalities. With few exceptions, however, there has been little discussion of methods for measuring this work. Many published assessments focus on the impacts of projects on students but overlook the impacts on community partners. Impacts on faculty and the larger university community are also often ignored. This article discusses literature on the evaluation of community–university research and service learning from a critical perspective. A discussion of service learning and community-based research (CBR) projects at two Chicago universities, DePaul and Chicago State, is presented. In both cases challenges were encountered to achieve full evaluation of projects, yet both included an evaluation of university and community partners that allowed for assessment of the projects’ value to all partners.     

Geochemical fractionation and ecological risks assessment of benthic sediment-bound heavy metals from coastal ecosystems off the Equatorial Atlantic Ocean

This study determines the pollution, fractionation, and ecological risks of sediment-bound heavy metals from coastal ecosystems off the Equatorial Atlantic Ocean. Contamination Factor(CF), pollution load index(PLI), and geoaccumulation index(Igeo) were used to assess the extent of the heavy metal pollution, while the potential ecological risk was evaluated using the risks assessment code(RAC) and Hkanson potential ecological risk. The analysis revealed concentrations(mg/g, dw) of the cadmium(Cd),chromium(Cr), copper(Cu), nickel(Ni), and lead(Pb) in sediments for wet and dry seasons vary from 4.40-5.08, 14.80-21.09. 35.03-44.8, 2.14-2.28, and 172.24-196.39, respectively. The results also showed that the metal fractionation percentages in the residual, oxidizable, and reducible fractions are the most significant, while the exchangeable and carbonate bound trace metals are relatively low. The RAC values indicate no risk for Cd and Ni and low risk for other metals at all the studied sites during both seasons.Potential ecological risk analysis of the heavy metal concentrations indicates that Cd had high individual potential ecological risk, while the other metals have low risk at all investigated sites. The multi-elemental potential ecological risk indices(R_1) indicate high ecological risk in all the ecosystems.     

Historical trends in Florida temperature and precipitation

Because of its low topographic relief, unique hydrology, and the large interannual variability of precipitation, Florida is especially vulnerable to climate change. In this paper, we investigate a comprehensive collection of climate metrics to study historical trends in both averages and extremes of precipitation and temperature in the state. The data investigated consist of long‐term records (1892–2008) of precipitation and raw (unadjusted) temperature at 32 stations distributed throughout the state. To evaluate trends in climate metrics, we use an iterative pre‐whitening method, which aims to separate positive autocorrelation from trend present in time series. Results show a general decrease in wet season precipitation, most evident for the month of May and possibly tied to a delayed onset of the wet season. In contrast, there seems to be an increase in the number of wet days during the dry season, especially during November through January. We found that the number of dog days (above 26.7 °C) during the year and during the wet season has increased at many locations. For the post‐1950 period, a widespread decrease in the daily temperature range (DTR) is observed mainly because of increased daily minimum temperature (Tmin). Although we did not attempt to formally attribute these trends to natural versus anthropogenic causes, we find that the urban heat island effect is at least partially responsible for the increase in Tmin and its corresponding decrease in DTR at urbanized stations compared with nearby rural stations. In the future, a formal trend attribution study should be conducted for the region. Copyright © 2012 John Wiley & Sons, Ltd.     

Airborne MSS for land cover classification II

A basic methodology for land cover classification using airborne multispectral scanner (MSS) imagery is outlined. This includes waveband selection and radiometric calibration; correction for scan angle and atmosphere; training and classification and accuracy assessment. Refinements to this basic methodology include per‐field sampling and the addition of low‐pass filtering, image texture, prior probabilities and two dates of imagery.

For a study area in upland England, eight land covers were classified with a mean accuracy of 52.6 percent using the basic methodology. This was increased to 79.0 percent by using a suitability refined methodology. Per‐field sampling accounted for the largest proportion of this increase.     

A continuum mechanics based framework for optimizing boundary and finite element meshes associated with underground excavations—accuracy,efficiency and applications

A framework was developed to address the automatic optimization of the level of geometric detail required for stress analysis of underground excavations in mining, which was presented in the companion paper. The motivation for optimizing the mesh geometry stems from the over‐discretization of computational domain as the digital mine model is built while our knowledge of some of the input parameters is quite limited. Thus, the accuracy of the solution is not expected to be increased with a finely discretized mesh, only the computation time does. Therefore, it is acceptable if the results obtained from an optimized model have accuracy comparable to the uncertainty in input data (e.g. rock mass properties, geology, etc.). Although the mesh optimization framework automates the geometry optimization and reduces computation time, the accuracy of the solution from the resulting geometry must be evaluated to ensure the quality of the solution at the ‘region of interest’. Both a priori (mesh quality) and a posteriori (solution quality) measures are employed along with recording the mesh optimization time. Finally, the applicability of the mesh optimization framework is demonstrated by analysing a number of mining and civil engineering underground models. Copyright © 2005 John Wiley & Sons, Ltd.     

An advanced GNSS code multipath detection and estimation algorithm

A novel maximum likelihood-based range estimation algorithm is designed to provide robustness to multipath, which is recognized as a dominant error source in DS-CDMA-based navigation systems. The detection–estimation problem is jointly solved to sequentially estimate the parameters of each individual multipath component and predict the existence of a next possible component. A comparison between contemporary maximum likelihood-based multipath estimation techniques and this new technique is provided. A selection of realistic channel simulation models is used to assess relative performance under different operating situations. A set of real GPS L1/CA data processing results are also presented to further assess the applicability of the proposed algorithm for urban navigation.