Database extension for digital soil mapping using artificial neural networks

Cost and time are the two most important factors conditioning soil surveys. Since these surveys provide basic information for modelling and management activities, new methods are needed to speed the soil-mapping process with limited input data. In this study, the polypedon concept was used to extend the spatial representation of sampled pedons (point data) in order to train artificial neural networks (ANNs) for digital soil mapping (DSM). The input database contained 97 soil profiles belonging to 7 different soil series and 15 digital elevation model (DEM) attributes. Pedons were represented in raster format as one-cell areas. The corresponding polypedons were then spatially represented by neighbouring raster cells (e.g. 2 × 2, … up to 6 × 6 cells). The primary database contained 97 pedons (97 cells) that were extended up to 3492 cells (in the case of 6 × 6-cell regions). This approach employed test and validation areas to calculate the respective accuracies of data interpolation and extrapolation. The results showed increased accuracies in training and interpolation (test area) but a poor level of accuracy in the extrapolation process (validation area). However, the overall precision of all predictions increased considerably. Using only topographic attributes for extrapolation was not sufficient to obtain an accurate soil map. To improve prediction, other soil-forming factors, such as landforms and/or geology, should also be considered as input data in the ANN. The proposed method could help to improve existing soil maps by using DSM results in areas with limited soil data and to save time and money in soil survey work.     

Seasonal variation of the double diffusion processes at the Strait of Hormuz

Profiles of salinity and temperature were measured in the strait of Hormuz (SH) during the winter of 2012, spring and summer of 2013. To investigate the double diffusion (DD) processes, Turner (TU) angle values are calculated in all the stations in the SH. Different TU angle values correspond to salt fingering (SF), diffusive convection (DC) and stable stratification. The distributions of the two forms of DD were plotted vertically along transects in the eastern, central and western part of the SH, and corresponding DD processes were described. The results show that both SF and DC occurred in most part of the study area. Two different water masses (the Indian Ocean surface water and the Persian Gulf water) were evident at the SH, and SF and DC were evident at the interface of two water masses. Due to evaporation, SF occurred in the surface layer of most Stations throughout the year. In the eastern part of the SH, occurrences of DC were more feasible in wintertime. SF was the main phenomenon at the end of hot season. For central part, SF occurred throughout the year in water column. In the western part, water column was stable in summer and DC happened in most part of water column in winter.     

Monitoring surface changes in discontinuous permafrost terrain using small baseline SAR interferometry,object-based classification,and geological features: a case study from Mayo,Yukon Territory,Canada

Permafrost-induced deformation of ground features is threating infrastructure in northern communities. An understanding of permafrost distribution is therefore critical for sustainable adaptation planning and infrastructure maintenance. Considering the large area underlain by permafrost in the Yukon Territory, there is a need for baseline information to characterize the permafrost in this region. In this study, the Differential Interferometric Synthetic Aperture Radar (DInSAR) technique was used to identify areas of ground movement likely caused by changes in permafrost. The DInSAR technique was applied to a series of repeat-pass C-band RADARSAT-2 observations collected in 2015 over the Village of Mayo, in central Yukon Territory, Canada. The conventional DInSAR technique demonstrated that ground deformation could be detected in this area, but the resulting deformation maps contained errors due to a loss of coherence from changes in vegetation and atmospheric phase delay. To address these limitations, the Small BAseline Subset (SBAS) InSAR technique was applied to reduce phase error, thus improving the deformation maps. To understand the relationship between the deformation maps and land cover types, an object-based Random Forest classification was developed to classify the study area into different land cover types. Integration of the InSAR results and the classification map revealed that the built-up class (e.g., airport) was affected by subsidence on the order of ?2 to ?4 cm. The spatial extent of the surface displacement map obtained using the SBAS InSAR technique was then correlated with the surficial geology map. This revealed that much of the main infrastructure in the Village of Mayo is underlain by interbedded glaciofluvial and glaciolacustrine sediments, the latter of which caused the most damage to human made structures. This study provides a method for permafrost monitoring that builds upon the synergistic use of the SBAS InSAR technique, object-based image analysis, and surficial geology data.     

Numerical simulation of incipient particle motion

A two-dimensional(2D)computational model for simulation of incipient sediment motion for noncohesive uniform and non-uniform particles on a horizontal bed was developed using the Discrete Element Method(DEM).The model was calibrated and verified using various experimental data reported in the literature and compared with different theories of incipient particle motion.Sensitivity analysis was done and the effects of relevant parameters were determined.In addition to hydrodynamic forces such as drag,shear lift and Magnus force,the particle-particle interaction effects were included in the model.The asymptotic critical mobility number was evaluated for various critical particle Reynolds numbers(R*)in the range of very small and very large R*.The obtained curve is classified into four regions.It was found that in the linear region,the drag force has the principal role on the initiation of motion.Moreover,the critical mobility number is independent of particle diameter.A procedure for estimating the critical shear velocity directly from the information on particle diameter and roughness height was developed.Finally,the mechanism of incipient motion for the different regions was studied and the effect of different forces on the incipient particle motion was obtained.It was found that the maximum effects of lift and Magnus forces were,respectively,less than ten and twenty percent of the total force.The drag force,however,was typically the dominant force accounting for majority of the net hydrodynamic force acting on sediment particles at the onset of incipient motion.