Rice Inundation Assessment Using Polarimetric UAVSAR Data

Irrigated rice requires intense water management under typical agronomic practices. Cost effective tools to improve the efficiency and assessment of water use is a key need for industry and resource managers to scale ecosystem services. In this research we advance model-based decomposition and machine learning to map inundated rice using time-series polarimetric, L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) observations. Simultaneous ground truth observations recorded water depth inundation during the 2019 crop season using instrumented fields across the study site in Arkansas, USA. A three-component model-based decomposition generated metrics representing surface-, double bounce-, and volume-scattering along with a shape factor, randomness factor, and the Radar Vegetation Index (RVI). These physically meaningful metrics characterized crop inundation status independent of growth stage including under dense canopy cover. Machine learning (ML) comparisons employed Random Forest (RF) using the UAVSAR derived parameters to identify cropland inundation status across the region. Outcomes show that RVI, proportion of the double-bounce within total scattering, and the relative comparison between the double-bounce and the volume scattering have moderate to strong mechanistic ability to identify rice inundation status with Overall Accuracy (OA) achieving 75%. The use of relative ratios further helped mitigate the impacts of far range incidence angles. The RF approach, which requires training data, achieved a higher OA and Kappa of 88% and 71%, respectively, when leveraging multiple SAR parameters. Thus, the combination of physical characterization and ML provides a powerful approach to retrieving cropland inundation under the canopy. The growth of polarimetric L-band availability should enhance cropland inundation metrics beyond open water that are required for tracking water quantity at field scale over large areas.

Naphthalene-induced respiratory tract toxicity: metabolic mechanisms of toxicity

The lung, which is in intimate contact with the external environment, is exposed to a number of toxicants both by virtue of its large surface area and because it receives 100% of the cardiac output. Lung diseases are a major disease entity in the U.S. population ranking third in terms of morbidity and mortality. Despite the importance of these diseases, key issues remain to be resolved regarding the interactions of chemicals with lung tissue and the factors that are critical determinants of chemical-induced lung injury. The importance of cytochrome P450 monooxygenase dependent metabolism in chemical-induced lung injury in animal models was established over 25 years ago with the furan, 4-ipomeanol. Since then, the significance of biotransformation and the reasons for the high degree of pulmonary selectivity for a myriad of different chemicals has been well documented, mainly in rodent models. However, with many of these chemicals there are substantial differences in the susceptibility of rats vs. mice. Even within the same species, varied levels of the respiratory tract respond differently. Thus, key pieces of data are still missing when evaluating the applicability of data generated in rodents to primates, and as a result of this, there are substantial uncertainties within the regulatory community with regards to assessing the risks to humans for exposure to some of these chemicals. For example, all of the available data suggest that the levels of cytochrome P450 monooxygenases in rodent lungs are 10-100 times greater than those measured in the lungs of nonhuman primates or in man. At first glance, this suggests that a significant margin of safety exists when evaluating the applicability of rodent studies in the human, but the issues are more complex. The intent of this review is to outline some of the work conducted on the site and species selective toxicity and metabolism of the volatile lung toxic aromatic hydrocarbon, naphthalene. We argue that a complete understanding of the cellular and biochemical mechanisms by which this and other lung toxic compounds generate their effects in rodent models with subsequent measurement of these cellular and biochemical events in primate and human tissues in vitro will provide a far better basis for judging whether the results of studies done in rodent models are applicable to humans.

Use of biomarkers in an indoor air study: lack of correlation between aromatic VOCs with respective urinary biomarkers

The benzene and toluene levels inside of eight homes with attached garages were measured during July 1998 in Fairbanks, Alaska. A thermal desorption tube method and charcoal tube method were used to collect and analyze samples (thermal desorption tube method %RDS = 1.9 for n = 6; charcoal tube method %RDS = 6.5 for n = 4). Results for both methods were compared and showed indoor benzene levels ranging between 1.2 and 72 ppbv. The charcoal tube method usually gave lower results than the thermal desorption method. Nevertheless, the difference observed in benzene levels from each method was not significant as determined by application of the Wilcoxon t-test to these data. Using the thermal desorption method, the range of toluene found in homes was 0.1-111 ppbv. A correlation between toluene and benzene levels suggested the same point source. The benzene and toluene content of the indoor air and the number of small engines stored in the attached garage was also correlated. There was no correlation found between the urinary biomarker concentrations and the level of benzene or toluene measured inside the homes in the summer.