Machine learning algorithms are an important measure with which to perform landslide susceptibility assessments,but most studies use GIS-based classification methods to conduct susceptibility zonation.This study presents a machine learning approach based on the C5.0 decision tree(DT)model and the K-means cluster algorithm to produce a regional landslide susceptibility map.Yanchang County,a typical landslide-prone area located in northwestern China,was taken as the area of interest to introduce the proposed application procedure.A landslide inventory containing 82 landslides was prepared and subse-quently randomly partitioned into two subsets:training data(70%landslide pixels)and validation data(30%landslide pixels).Fourteen landslide influencing factors were considered in the input dataset and were used to calculate the landslide occurrence probability based on the C5.0 decision tree model.Susceptibility zonation was implemented according to the cut-off values calculated by the K-means clus-ter algorithm.The validation results of the model performance analysis showed that the AUC(area under the receiver operating characteristic(ROC)curve)of the proposed model was the highest,reaching 0.88,compared with traditional models(support vector machine(SVM)=0.85,Bayesian network(BN)=0.81,frequency ratio(FR)=0.75,weight of evidence(WOE)=0.76).The landslide frequency ratio and fre-quency density of the high susceptibility zones were 6.76/km2 and 0.88/km2,respectively,which were much higher than those of the low susceptibility zones.The top 20%interval of landslide occurrence probability contained 89%of the historical landslides but only accounted for 10.3%of the total area.Our results indicate that the distribution of high susceptibility zones was more focused without contain-ing more"stable"pixels.Therefore,the obtained susceptibility map is suitable for application to landslide risk management practices. 相似文献
Strong and rapid greenhouse gas (GHG) emission reductions, far beyond those currently committed to, are required to meet the goals of the Paris Agreement. This allows no sector to maintain business as usual practices, while application of the precautionary principle requires avoiding a reliance on negative emission technologies. Animal to plant-sourced protein shifts offer substantial potential for GHG emission reductions. Unabated, the livestock sector could take between 37% and 49% of the GHG budget allowable under the 2°C and 1.5°C targets, respectively, by 2030. Inaction in the livestock sector would require substantial GHG reductions, far beyond what are planned or realistic, from other sectors. This outlook article outlines why animal to plant-sourced protein shifts should be taken up by the Conference of the Parties (COP), and how they could feature as part of countries’ mitigation commitments under their updated Nationally Determined Contributions (NDCs) to be adopted from 2020 onwards. The proposed framework includes an acknowledgment of ‘peak livestock’, followed by targets for large and rapid reductions in livestock numbers based on a combined ‘worst first’ and ‘best available food’ approach. Adequate support, including climate finance, is needed to facilitate countries in implementing animal to plant-sourced protein shifts.
Key policy insights
Given the livestock sector’s significant contribution to global GHG emissions and methane dominance, animal to plant protein shifts make a necessary contribution to meeting the Paris temperature goals and reducing warming in the short term, while providing a suite of co-benefits.
Without action, the livestock sector could take between 37% and 49% of the GHG budget allowable under the 2°C and 1.5°C targets, respectively, by 2030.
Failure to implement animal to plant protein shifts increases the risk of exceeding temperate goals; requires additional GHG reductions from other sectors; and increases reliance on negative emissions technologies.
COP 24 is an opportunity to bring animal to plant protein shifts to the climate mitigation table.
Revised NDCs from 2020 should include animal to plant protein shifts, starting with a declaration of ‘peak livestock’, followed by a ‘worst first’ replacement approach, guided by ‘best available food’.
This study focuses on model predictive skill with respect to stratospheric sudden warming(SSW) events by comparing the hindcast results of BCC_CSM1.1(m) with those of the ECMWF's model under the sub-seasonal to seasonal prediction project of the World Weather Research Program and World Climate Research Program. When the hindcasts are initiated less than two weeks before SSW onset, BCC_CSM and ECMWF show comparable predictive skill in terms of the temporal evolution of the stratospheric circumpolar westerlies and polar temperature up to 30 days after SSW onset. However, with earlier hindcast initialization, the predictive skill of BCC_CSM gradually decreases, and the reproduced maximum circulation anomalies in the hindcasts initiated four weeks before SSW onset replicate only 10% of the circulation anomaly intensities in observations. The earliest successful prediction of the breakdown of the stratospheric polar vortex accompanying SSW onset for BCC_CSM(ECMWF) is the hindcast initiated two(three) weeks earlier. The predictive skills of both models during SSW winters are always higher than that during non-SSW winters, in relation to the successfully captured tropospheric precursors and the associated upward propagation of planetary waves by the model initializations. To narrow the gap in SSW predictive skill between BCC_CSM and ECMWF, ensemble forecasts and error corrections are performed with BCC_CSM. The SSW predictive skill in the ensemble hindcasts and the error corrections are improved compared with the previous control forecasts. 相似文献
There is an increased demand for the accurate prediction of fog events in the Sichuan Basin (SCB) using numerical methods. A dense fog event that occurred over the SCB on 22 December 2016 was investigated. The results show that this dense fog event was influenced by the southwest of a low pressure with a weak horizontal pressure gradient and high relative humidity. This fog event showed typical diurnal variations. The fog began to form at 1800 UTC on 21 December 2016 (0200 local standard time on 22 December 2016) and dissipated at 0600 UTC on 22 December 2016 (1400 local standard time on 22 December 2016). The Weather Research and Forecasting model was able to partially reproduce the main features of this fog event and the diurnal variation in the local mountain to basin winds. The simulated horizontal visibility and liquid water content were used to characterize the fog. The mountain to basin winds had an important role in the diurnal variation of the fog event. The positive feedback mechanism between the fog and mountain to basin winds was good for the formation and maintain of the fog during the night. During the day, the mountain to basin wind displayed a transition from downslope flows to upslope flows. Water vapor evaporated easily from the warm, strong upslope winds, which resulted in the dissipation of fog during the day. The topography surrounding the SCB favored the lifting and condensation of air parcels in the lower troposphere as a result of the low height of the lifting condensation level. 相似文献
The American Great Plains is a region dominated by a flat, treeless, semiarid environment that has challenged population settlement for over 140 years. As railroad companies successfully attracted pioneers to settle the land, state governments established hundreds of counties. Following Jeffersonian ideals, many of the counties were small in area so they could better serve the local agricultural‐based population. When states established these counties, they envisioned that the population would continue to grow and the Great Plains would become the breadbasket of North America. Unfortunately that did not materialize. A succession of hardships combined with serious environmental constraints has discouraged large‐scale settlement in the region. Many counties reached their maximum population in the early 1900s and their totals have decreased ever since (in some counties by as much as 60 percent to 80 percent). This has led a number of government officials to consider consolidating counties much like school districts have been combined. Using Logan and Gove counties in western Kansas as a case study, our purpose is to understand how attached people are to the county in which they live. Employing multiple methods, we gathered information about how different segments of the population regard their local county. We learned that changing computer technology and the Internet has the biggest impact on peoples' attachment to the county seat. 相似文献
In this article I consider the initial period of solid waste management planning in the US state of Hawaii. The State encountered a number of economic and ecological controversies during its solid waste management planning, a process that was prompted by the US Environmental Protection Agency. Some issues, like project financing, were common across the US, while others, such as the potential of waste materials to reduce reliance on imported food and materials, were more unique to Hawaii. The controversies from this initial planning period were never quite fully resolved; as they lingered, they were interpreted differently across the Islands. Based on a close reading of government, advocacy group, waste industry and news media documents, I examine the controversies over solid waste management of the time and consider how the ‘dual nature’ of waste in Hawaii—simultaneously an ecological threat and (potential) economic input—shaped the adoption of solid waste management systems there. This article adds to an expanding literature examining infrastructure in environmental and technology histories. 相似文献