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In this paper, a model for the distribution of the Global Carbon Budget between the countries of the world is presented. The model is based on the criteria of equity while also taking into account the different historical responsibilities. The Global Carbon Budget corresponds to the quantity of carbon dioxide emissions that can still be released into the atmosphere while maintaining the increase in the average earth surface temperature below 2 °C, and it is therefore compatible with the long-term objective defined in the Paris Agreement. The results of applying the model are shown both for the 15 emitters that currently top the ranking for world emissions as well as for the other countries, which are grouped together in three main groups: Other African, Other Latin American and Caribbean, and the Rest of the World. Mitigation curves compatible with the carbon budget allocated to the different countries are presented. When comparing each emitter’s historical emissions for the period 1971–2010 with the proposed distribution for the period 2011–2050 obtained using the model, it can be seen that developed countries must face the future with a greatly reduced carbon budget, whereas developing countries can make use of a carbon budget that is higher than their cumulative historical emissions. Finally, there is a discussion about how a model with these characteristics could be useful when implementing the Paris Agreement. 相似文献
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Accurate and reliable methods for quantifying grain size are important for river science, management and in various other sedimentological settings. Remote sensing offers methods of quantifying grain size, typically providing; (a) coarse outputs (c. 1 m) at the catchment scale where individual grains are at subpixel level, or; (b) fine resolution outputs (c. 1 mm) at the patch scale. Recently, approaches using unmanned aerial vehicles (UAVs) have started to fill the gap between these scales, providing hyperspatial resolution data (< 10 cm) over reaches a few hundred metres in length, where individual grains are at suprapixel level. This ‘mesoscale’ is critical to habitat assessments. Most existing UAV‐based approaches use two‐dimensional (2D) textural variables to predict grain size. Validation of results is largely absent however, despite significant differences in platform stability and image quality obtained by manned aircraft versus UAVs. Here, we provide the first quantitative assessment of the accuracy and precision of grain size estimates produced from a 2D image texture approach. Furthermore, we present a new method which predicts subaerial gravel size using three‐dimensional (3D) topographic data derived from UAV imagery. Data is collected from a small gravel‐bed river in Cumbria, UK. Results indicate that our new topographic method gives more accurate measures of grain size (mean residual error ‐0.0001 m). Better results for the image texture method may be precluded by our choice of texture measure, the scale of analysis or the effects of image blur resulting from an inadequate camera gimbal. We suggest that at our scale of assessment, grain size is more strongly related to 3D variation in elevation than to the 2D textural patterns expressed within the imagery. With on‐going improvements, our novel method has potential as the first grain size quantification approach where a trade‐off between coverage and resolution is not necessary or inherent. Copyright © 2017 John Wiley & Sons, Ltd. 相似文献
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Multi-scale landform characterization 总被引：4，自引：0，他引：4
One fundamental objective in geomorphometry is to extract signatures of geomorphologic processes on different spatial scales from digital terrain models (DTMs) and to describe the complexity of landforms as the synthesis of those individual imprints. We present an approach for characterizing land surfaces on multiple, spatially varying local scales. We approximate terrain surfaces locally to calculate surface derivatives at different window sizes. Local scale behaviour diagrams are used to define dominant scale ranges and multiple curvatures for each surface point. Multi-scale landform analysis leads to improved models of surface derivatives and new landform classifications, applicable in geomorphology, soil science and hydrology. 相似文献
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