基于MODIS数据的地表组分温度反演研究

组分温度的反演是当前定量遥感的一个难点。与众多的陆面温度遥感模型相比,成熟的组分温度遥感模型相对较少。通过对近地面热红外辐射能量的线性展开,建立了MODIS多波段植被、土壤组分温度反演模型。该模型将组分温度与地表温度定量联系起来,模型中所涉及到的参数充分考虑到研究区湿地环境的特点。在计算组分温度时,首先利用单窗算法得到的MODIS陆面温度反演模型计算地表温度,然后由所建立的组分温度模型计算植被、土壤温度。选用2005年10月31日的鄱阳湖地区MODIS数据试验,与实测的植被、土壤温度相比,反演的组分温度的误差在15~21℃;通过对模型参数的敏感性分析,表明该模型具有一定的稳定性。实践证明,该方法能够有效实现组分温度的分离,是一种组分温度反演的较好方法。     

山东近岸黄海极值风速预测及防灾建议——基于极值分布和风向的预测

在总结有关海上大风预测研究成果的基础上,根据极值理论合理选取预测极值风速的极值分布计算模型:Gumbel分布和Poisson-Gumbel分布。根据山东近岸黄海26 a的风速观测资料,采用分风向统计数据和投影法处理数据,充分考虑风向和相邻风向的影响,形成十六个风向的年极值序列和过程极值序列样本;最后,用两种模型计算得到各个风向的极值风速预测结果,对比不考虑风向的计算结果,分析出黄海海域海洋风灾发生的时间规律和致灾风向,并对黄海海域的防风减灾提出合理建议。     

Screening and characterization of extremophiles in spacecraft assembly environment北大核心CSCD

Spacecrafts need to strictly control microorganisms before entering space flight. The Spacecraft Assembly, Integration, and Test Center (AITC) is an important environmental source for spacecrafts to carry microorganisms. The assembly clean room has characteristics of ventilation, dryness, and lack of nutrients that are not conducive to the growth and reproduction of microorganisms, except for extremophiles. In this study, based on the internal air and surface environment of the AITC in China, 13 strains of bacteria were identified by plate culture and 16S sequence analysis, and their extreme environmental tolerance, antibiotic resistance, and film-forming ability were tested. All these bacteria belonged to the Firmicutes and Proteobacteria phyla, and nine strains belonged to the Bacillus genus. All 13 strains of bacteria were salt-tolerant, acid-tolerant, and alkali-tolerant, and 69.2% of the bacteria survived heat shock at 80 ℃. Among these, one strain of Sphingomonas sp. JCM7513 isolated from the surface environment was insensitive to all the tested antibiotics and had strong drug resistance, while the other 12 strains were sensitive to most β-lactam antibiotics but had strong resistance to tetracyclic antibiotics and erythromycin. Most of the isolated bacteria exhibited strong biofilm-forming abilities. The study showed that there are a certain number of extremophiles in the spacecraft assembly environment. To protect spacecrafts from biological corrosion and planetary protection forward pollution, more effective monitoring and elimination methods are needed. © 2022 Science Press. All rights reserved.     

Transformation of rural communities: lessons from a local self-initiative for building resilience in the Solomon Islands

Solomon Islands is vulnerable to negative impacts from climate change, where people’s livelihoods and their well-being are threatened, especially the viability of isolated communities. Realising the increasing risks from climate change on communities, government, in partnership with aid-donor partners, has invested millions of dollars in climate change projects, through mitigation and adaptation strategies. As a form of adaptation, the government invests in programmes aimed at increasing the adaptive capacity of the vulnerable communities through landscape and seascape projects across the rural communities. Focusing on the “transformation concept” as a long-term adaptation strategy and enlargement of climate engineering and ecological resilience concepts, the paper discusses why building resilience from transformation of rural communities, as well as from landscape and seascape projects, would benefit communities and relevant authorities. This paper describes the findings of a study on two rural villages, Keigold and Mondo, from Ranogha Islands, Western Province, in Solomon Islands, where 80% of households decided to relocate from their old village “Mondo” to their new home “Keigold” after an earthquake in 2007, as part of a self-initiative. The reallocation process can be seen as a case of pro-active community transformation that provides valuable lessons to other rural communities that may be forced to move due to impacts from natural catastrophes, including those explained by climate change risks. Lessons from this experience suggest that policy-makers and non-government organisations should consider and empower local transformation initiatives as a way to building long-term adaptation to climate change.     

陕西2012年极端天气气候事件与气象灾害

利用极端天气气候事件监测系统监测结果,分析了陕西1981-2012年极端天气气候事件出现次数和强度,发现2012年陕西极端天气气候事件次数少于多年平均值,但华阴7月2-4日、佳县7月24-28日极端降水事件强度之大,为历史罕见,佳县27日降水量、26-28日3d降水量均超过百年一遇的水平,造成严重人员伤亡和经济损失.说明即便是在极端天气气候事件出现次数少,气候年景较好的年份,局地也会出现历史罕见的极端事件和灾害.此外,还分析了极端天气气候事件次数与灾情年景评估指数之间的相关性.     

Crop adaptation processes to extreme floods in Bangladesh: a case study

This paper investigates farmers’ crop adaptation processes in response to three recent devastating floods in Islampur, a case-study area in rural Bangladesh. The paper reports a multi-method research project which comprised a questionnaire survey, focus-group discussions and interviews with agricultural block supervisors. The author analyses three recent severe floods in Bangladesh, occurring in 1988, 1995 and 1998, and reviews the adaptation techniques and strategies embraced by the same group of farmers in order to survive the more devastating inundations that occur from time to time. The study concluded that vulnerable farmers are highly resilient and, with appropriate support, their adjustments can be sustainable. This enquiry showed that in the face of climate change both the inclusion of autonomous adaptations into planning and policy-making and the enhancement and support of community-based adaptation can be effective in ensuring the survival of riverine farming systems. This case study can be considered as a key reference case in regard to vulnerable locations in the Ganges–Brahmaputra–Meghna mega-delta basin, particularly in respect to Bangladesh.     

Heat-health warnings in regional Australia: examining public perceptions and responses

ABSTRACT

Heatwaves are an increasing environmental hazard and an important public health issue in Australia. Heat-health warnings are being adopted widely to promote protective behaviours, but there has been limited evaluation of public responses. This study used a household telephone survey to examine public attitudes and responses to heat-health warnings in regional areas in two Australian states, South Australia and Victoria. The results indicate a high level of recall of heat-health warnings and awareness about managing extreme heat. Respondents viewed heat-health warnings positively, but the effects on behaviour change were variable. Our findings suggest that the warnings may be reinforcing existing protective behaviours more than promoting change. Perceptions of heat risks were higher among women than men, but lower in older age groups. Evidence of this nature is important to identify ways to improve heat-health warnings and more effectively address the public health risks.     

Hierarchical modeling for extreme values observed over space and time

We propose a hierarchical modeling approach for explaining a collection of spatially referenced time series of extreme values. We assume that the observations follow generalized extreme value (GEV) distributions whose locations and scales are jointly spatially dependent where the dependence is captured using multivariate Markov random field models specified through coregionalization. In addition, there is temporal dependence in the locations. There are various ways to provide appropriate specifications; we consider four choices. The models can be fitted using a Markov Chain Monte Carlo (MCMC) algorithm to enable inference for parameters and to provide spatio–temporal predictions. We fit the models to a set of gridded interpolated precipitation data collected over a 50-year period for the Cape Floristic Region in South Africa, summarizing results for what appears to be the best choice of model.

基于RF-ELM模型的边坡稳定性预测研究

为实现对边坡稳定性的有效预测,将极限学习机算法与旋转森林算法相结合,并依据影响边坡稳定性的六项重要因素,建立了边坡稳定性预测的RF-ELM预测模型。该模型是以极限学习机算法为基分类器,以旋转森林算法为框架的集成学习模型,利用UCI数据库中三组数据集验证了该集成模型确实提高了ELM的预测性能。将RF-ELM模型应用于边坡稳定性的预测问题中,结合39组工程实例数据进行预测实验,结果表明该模型具有较高的预测精度,可有效的对边坡稳定性进行预测。     

Ranked set sample design for environmental investigations

Ranked set sampling can provide an efficient basis for estimating parameters of environmental variables, particularly when sampling costs are intrinsically high. Various ranked set estimators are considered for the population mean and contrasted in terms of their efficiencies and useful- ness, with special concern for sample design considerations. Specifically, we consider the effects of the form of the underlying random variable, optimisation of efficiency and how to allocate sampling effort for best effect (e.g. one large sample or several smaller ones of the same total size). The various prospects are explored for two important positively skew random variables (lognormal and extreme value) and explicit results are given for these cases. Whilst it turns out that the best approach is to use the largest possible single sample and the optimal ranked set best linear estimator (ranked set BLUE), we find some interesting qualitatively different conclusions for the two skew distributions