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Catherine Robin Shannon Nudds Phillip MacAulay André Godin Bodo De Lange Boom Jason Bartlett 《Marine Geodesy》2016,39(2):195-222
Since the advent of Global Navigation Satellite Systems, it has been possible to perform hydrographic survey reductions through the ellipsoid, which has the potential to simplify operations and improve bathymetric products. This technique requires a spatially continuous separation surface connecting chart datum (CD) to a geodetic ellipsoid. The Canadian Hydrographic Service (CHS), with support from the Canadian Geodetic Survey, has developed a new suite of such surfaces, termed Hydrographic Vertical Separations Surfaces, or HyVSEPs, for CD and seven tidal levels. They capture the spatial variability of the tidal datum and levels between tide gauges and offshore using semiempirical models coupling observations at tide stations with relative sea-level rise estimates, dynamic ocean model solutions, satellite altimetry, and a geoid model. HyVSEPs are available for all tidal waters of Canada, covering over seven million square kilometers of ocean and more than 200,000 kilometers of shoreline. This document provides an overview of the CHS's modeling approach, tools, methods, and procedures.
The HyVSEP for CD defines the new hydrographic datum for the tidal waters of Canada. HyVSEPs for other tidal levels are fundamental for coastal studies, climate change adaptation and the definition of the Canadian shoreline and offshore boundaries. HyVSEPs for inland waters are not discussed. 相似文献
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Michael J. Friedel Massimo Buscema Luiz Eduardo Vicente Fabio Iwashita Andréa Koga-Vicente 《International Journal of Digital Earth》2018,11(7):670-690
An unsupervised machine-learning workflow is proposed for estimating fractional landscape soils and vegetation components from remotely sensed hyperspectral imagery. The workflow is applied to EO-1 Hyperion satellite imagery collected near Ibirací, Minas Gerais, Brazil. The proposed workflow includes subset feature selection, learning, and estimation algorithms. Network training with landscape feature class realizations provide a hypersurface from which to estimate mixtures of soil (e.g. 0.5 exceedance for pixels: 75% clay-rich Nitisols, 15% iron-rich Latosols, and 1% quartz-rich Arenosols) and vegetation (e.g. 0.5 exceedance for pixels: 4% Aspen-like trees, 7% Blackberry-like trees, 0% live grass, and 2% dead grass). The process correctly maps forests and iron-rich Latosols as being coincident with existing drainages, and correctly classifies the clay-rich Nitisols and grasses on the intervening hills. These classifications are independently corroborated visually (Google Earth) and quantitatively (random soil samples and crossplots of field spectra). Some mapping challenges are the underestimation of forest fractions and overestimation of soil fractions where steep valley shadows exist, and the under representation of classified grass in some dry areas of the Hyperion image. These preliminary results provide impetus for future hyperspectral studies involving airborne and satellite sensors with higher signal-to-noise and smaller footprints. 相似文献
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Natural Hazards - Long-period waves propagating inside harbours can lead to the generation of seiche that can affect and significantly disrupt port operations. This study is based on the analysis... 相似文献
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Energy-intensive industries play an important role in low-carbon development, being particularly exposed to climate policies. Concern over possible carbon leakage in this sector poses a major challenge for designing effective carbon pricing instruments (CPI). Different methodologies for assessing carbon leakage exposure are currently used by different jurisdictions, each of them based on different approaches and indicators. This paper aims to analyse the extent to which the use of different methodologies leads to different results in terms of exposure to the risk of carbon leakage, using the Brazilian industry sector as a case study. Results indicate that carbon leakage exposure is an expected outcome of eventual CPI implementation in Brazilian industry. However, results vary according to the chosen methodology, so the definition of the criteria is paramount for assessing sectoral exposure to the risk of carbon leakage.
Key policy insights
Despite increasing discussion about the implementation of carbon pricing on the Brazilian industrial sector, the evaluation of carbon leakage risks is still neglected.
Assessments of the risk of carbon leakage are directly related to the indicators and criteria used by each methodology. Thus, a given subsector may present different levels of exposure to carbon leakage depending on the methodological choice.
More than a purely technical discussion, the methodological definition of carbon leakage risk is a political discussion – it can be well-conducted, leading to the success of a CPI, or even sabotaged, by implicitly subsidizing energy-intensive industries.
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