S U M M A R YThe Canada Basin and the southern Alpha-Mendeleev ridge complex underlie a significant proportion of the Arctic Ocean, but the geology of this undrilled and mostly ice-covered frontier is poorly known. New information is encoded in seismic wide-angle reflections and refractions recorded with expendable sonobuoys between 2007 and 2011. Velocity-depth samples within the sedimentary succession are extracted from published analyses for 142 of these records obtained at irregularly spaced stations across an area of 1.9E + 06 km 2 . The samples are modelled at regional, subregional and station-specific scales using an exponential function of inverse velocity versus depth with regionally representative parameters determined through numerical regression. With this approach, smooth, non-oscillatory velocity-depth profiles can be generated for any desired location in the study area, even where the measurement density is low. Practical application is demonstrated with a map of sedimentary thickness, derived from seismic reflection horizons interpreted in the time domain and depth converted using the velocity-depth profiles for each seismic trace. A thickness of 12-13 km is present beneath both the upper Mackenzie fan and the middle slope off of Alaska, but the sedimentary prism thins more gradually outboard of the latter region. Mapping of the observed-to-predicted velocities reveals coherent geospatial trends associated with five subregions: the Mackenzie fan; the continental slopes beyond the Mackenzie fan; the abyssal plain; the southwestern Canada Basin; and, the Alpha-Mendeleev magnetic domain. Comparison of the subregional velocity-depth models with published borehole data, and interpretation of the station-specific best-fitting model parameters, suggests that sandstone is not a predominant lithology in any of the five subregions. However, the bulk sand-to-shale ratio likely increases towards the Mackenzie fan, and the model for this subregion compares favourably with borehole data for Miocene turbidites in the eastern Gulf of Mexico. The station-specific results also indicate that Quaternary sediments coarsen towards the Beaufort-Mackenzie and Banks Island margins in a manner that is consistent with the variable history of Laurentide Ice Sheet advance documented for these margins. Lithological factors do not fully account for the elevated velocity-depth trends that are associated with the southwestern Canada Basin and the Alpha-Mendeleev magnetic domain. Accelerated porosity reduction due to elevated palaeo-heat flow is inferred for these regions, which may be related to the underlying crustal types or possibly volcanic
We evaluated the utility of Terra/MODIS-derived crop metrics for yield estimation across the Canadian Prairies. This study was undertaken at the Census Agriculture Region (CAR) and the Rural Municipality (RM) of the province of Saskatchewan, in three prairie agro-climate zones. We compared MODIS-derived vegetation indices, gross primary productivity (GPP), and net primary productivity (NPP) to the known yields for barley, canola, and spring wheat. Multiple linear regressions were used to assess the relationships between the metrics and yield at the CAR and RM levels for the years 2000 to 2016. Models were evaluated using a leave-one-out cross validation (LOOCV) approach. Results showed that vegetation indices at crop peak growing stages were better predictors of yield than GPP or NPP, and EVI2 was better than NDVI. Using seasonal maximum EVI2, CAR-level crop yields can be estimated with a relative root-mean-square-error (RRMSE) of 14-20% and a Nash-Sutcliffe model efficiency coefficient (NSE) of 0.53-0.70, though the exact relationship varies by crop type and agro-climate zone. LOOCV showed the stability of the models across different years, although interannual fluctuations of estimation accuracy were observed. Assessments using RM-level yields showed slightly reduced accuracy, with NSE of 0.37-0.66, and RRMSE of 18-28%. The best performing models were used to map annual crop yields at the Soil Landscapes of Canada (SLC) polygon level. The results indicated that the models could perform well at both spatial scales, and thus, could be used to disaggregate coarse resolution crop yields to finer spatial resolutions using MODIS data.
Commonly, seismic data processing procedures, such as stacking and prestack migration, require the ability to detect bad traces/shots and restore or replace them by interpolation, particularly when the seismic observations are noisy or there are malfunctioned components in the recording system. However, currently available trace/shot interpolation methods in the spatial or Fourier domain must deal with requirements such as evenly sampled traces/shots, infinite bandwidth of the signals, and linear seismic events. In this paper, we present a novel method, termed the E-S (eigenspace seismic) method, using principal component analysis (PCA) of the seismic signal to address the issue of reliable detection or interpolation of bad traces/shots. The E-S method assumes the existence of a correlation between the observed seismic entities, such as trace or shot gathers, making it possible to estimate one of these entities from all others for interpolation or seismic quality control. It first transforms a trace (or shot) gather into an eigenspace using PCA. Then in the eigenspace, it treats every trace as a point with its loading scores of PCA as its coordinates. Simple linear, bilinear, or cubic spline 1 dimensional (1D) interpolation is used to determine PCA loading scores for any arbitrary coordinate in the eigenspace, which are then used to construct an interpolated trace for the desired position in physical space. This E-S method works with either regular or irregular sampling and, unlike various other published methods, it is well-suited for band-limited seismic records with curvilinear reflection events. We developed related algorithms and applied these to processed synthetic and offshore seismic survey data with or without simulated noises to demonstrate their performance. By comparing the interpolated and observed seismic traces, we find that the E-S method can effectively assess the quality of the trace, and restore poor quality data by interpolation. The successful processing of synthetic and real data using the E-S method presented in this approach will be widely applicable to seismic trace/shot interpolation and seismic quality control.
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