物理海洋传感器现状及未来发展趋势

文中对目前我国物理海洋要素观测传感器技术发展现状进行了分析。在国家科技计划支持下,我国的物理海洋观测传感器技术取得了快速发展,但与国际上先进的传感器技术水平相比,国内具有自主知识产权的传感器仍有较大差距。随着未来海洋观测需求的不断发展,小型、轻重量、低功耗、高精度、高灵敏、智能化新型传感器必将是今后5~10年研究与开发的重点。     

刍议《重庆历史地图集》第二卷的编制

以《重庆历史地图集》第二卷编制的具体情况为例,对图集的开本设计、内容结构设计、封面和版式设计、整体设计、创新源,以及图集编制取得的经验进行了论述,为以后类似图集的编制提供参考。     

Innovation for sustainable energy from a pro-poor perspective

The development and transfer of clean energy technologies to achieve universal energy access is challenging due to the inherent complexities of the energy sector, and the energy governance and financial systems in developing economies. Innovation is an essential part of successfully addressing these difficulties. Duplicating the energy infrastructure models of developed countries will not be sufficient to meet the needs of poor consumers. To the extent that innovation can accelerate energy access, it is important to understand the specific types of innovations that are necessary and how they might be facilitated. The general features of existing international clean energy innovation systems, which are predominantly driven by the markets and emissions reduction mechanisms of developed and rapidly growing emerging economies, are reviewed and the alignment of these systems to the innovation processes required to extend energy access globally is evaluated. Drawing on the innovation policy literature, the attributes of effective international and domestic energy innovation systems that are pro-poor and the associated policy approaches are identified.     

论新时期地质资料档案管理服务模式的创新

在社会知识经济、信息管理高速发展的新时期,地质资料档案管理工作的内容与模式也发生了巨大的转变。本文将从地质资料档案管理特点、创新服务模式的必然性、实现创新的具体措施等几个方面阐述新时期地质资料档案管理服务模式,充分发挥地质资料档案对社会经济建设的作用。     

海洋科技创新与海洋经济发展的协调关系及其影响机理研究

为深入揭示海洋科技创新与海洋经济发展的协调关系及其影响机理,促进我国海洋科技和海洋经济的高质量和可持续发展,文章构建海洋科技创新和海洋经济发展2个系统的评价指标体系,以辽宁为实例,利用协调度模型分析二者的协调度及其演化趋势,进一步利用结构方程模型构建海洋科技创新影响海洋经济发展的驱动路径,以此分析其影响因素和影响效应,并提出对策建议。研究结果表明:1997-2016年辽宁海洋科技创新与海洋经济发展的协调关系分为中度失调衰退、严重失调衰退、中度协调发展和良好协调发展4个主要阶段;海洋科技创新通过海洋资源水平、海洋经济规模和海洋经济结构对海洋经济发展产生直接效应,同时通过海洋经济规模对地区经济发展产生间接效应,即海洋科技创新对海洋经济发展和地区经济发展均产生显著的促进作用;未来应统筹海洋科技与海洋经济的协调发展,扩大海洋科技的投入和产出,积极培育海洋科研人才和新兴海洋产业,注重提高对外开放程度和发展港口经济。     

Assessing integration of intensity,polarimetric scattering,interferometric coherence and spatial texture metrics in PALSAR-derived land cover classification

Synthetic aperture radar (SAR) is an important alternative to optical remote sensing due to its ability to acquire data regardless of weather conditions and day/night cycle. The Phased Array type L-band SAR (PALSAR) onboard the Advanced Land Observing Satellite (ALOS) provided new opportunities for vegetation and land cover mapping. Most previous studies employing PALSAR investigated the use of one or two feature types (e.g. intensity, coherence); however, little effort has been devoted to assessing the simultaneous integration of multiple types of features. In this study, we bridged this gap by evaluating the potential of using numerous metrics expressing four feature types: intensity, polarimetric scattering, interferometric coherence and spatial texture. Our case study was conducted in Central New York State, USA using multitemporal PALSAR imagery from 2010. The land cover classification implemented an ensemble learning algorithm, namely random forest. Accuracies of each classified map produced from different combinations of features were assessed on a pixel-by-pixel basis using validation data obtained from a stratified random sample. Among the different combinations of feature types evaluated, intensity was the most indispensable because intensity was included in all of the highest accuracy scenarios. However, relative to using only intensity metrics, combining all four feature types increased overall accuracy by 7%. Producer’s and user’s accuracies of the four vegetation classes improved considerably for the best performing combination of features when compared to classifications using only a single feature type.     

组合导航中一种新息自适应卡尔曼滤波算法

全球定位系统/航位推算组合导航定位中,由于目标运动的不确定性,GPS接收机与DR器件接收的数据存在噪声,使预置目标运动模型通常很难得到较高跟踪精度,针对应用常规卡尔曼滤波进行组合导航解算由于噪声统计特性未知而引起滤波不稳定的问题,本文提出了一种基于新息序列的量测计算进行自适应估计的卡尔曼滤波算法。该算法通过对新息方差强度进行极大似然估计,将新息计算引入卡尔曼滤波器的增益计算,达到控制发散的目的。最后对改进的算法与一般卡尔曼滤波算法做了对比仿真试验分析,结果表明了改进算法的有效性。     

Climate policy innovation in the South – Domestic and international determinants of renewable energy policies in developing and emerging countries

This article attempts to disentangle the determinants of the adoption of renewable energy support policies in developing and emerging countries. By analyzing policies already implemented in industrialized countries, we focus on the diffusion but not the invention of climate-relevant policies. We look at four different types of policies (renewable energy targets, feed-in tariffs, other financial incentives and framework policies) and consider both domestic factors and international diffusion mechanisms utilizing a discrete-time events history model with a logit link on a self-compiled dataset of grid-based electricity policy adoption in 112 developing and emerging countries from 1998 to 2009. In general, we find stronger support for the domestic determinants of policy adoption, but also substantial influence of international factors. Countries with a larger population and more wealth have a higher probability of adopting renewable energy policies. Only in some specific cases do natural endowments for producing renewable energy encourage governments to adopt policies, and hydro power resources even correlate negatively with the adoption of targets. Among the international determinants, emulation from colonial peers and membership within the EU seem to facilitate policy adoption. International climate finance is less relevant, as the Global Environmental Facility and the Clean Development Mechanism may only increase the adoption of frameworks and targets, but they have no influence on tariffs and incentives.     

The adoption of sustainable innovations: Driven by symbolic and environmental motives

Critical to the environmental success of sustainable innovations is the adoption by consumers. The consensus is that instrumental shortcomings of sustainable innovations inhibit their adoption. However, we argue that the adoption of sustainable innovations does not exclusively depend on their instrumental attributes. In addition, people may be motivated to adopt sustainable innovations because of their positive environmental and symbolic attributes, that is, they benefit the environment and can be used to signal positive characteristics to oneself and others. We studied the significance of instrumental, environmental and symbolic attributes for the adoption of two sustainable innovations: electric cars (Study 1) and local renewable energy systems (Study 2), following two methods. Results showed that when asked directly, participants claimed that instrumental and environmental attributes are most important for their decision to adopt sustainable innovations, while symbolic attributes were rated as less important. Interestingly, evaluations of the symbolic and environmental attributes of sustainable innovations, but not evaluations of their instrumental attributes, predicted different indicators of adoption (i.e., interest in, the acceptability of, and intention to adopt these sustainable innovations), suggesting that the significance of symbolic motives for adopting sustainable innovations may not be recognized by consumers. Moreover, favorable evaluations of symbolic attributes particularly enhanced interest in and acceptability of sustainable innovation when participants evaluated the instrumental attributes more negatively, but not when instrumental attributes were evaluated relatively positively. This suggests that the instrumental drawbacks of sustainable innovations may sometimes strengthen their positive signal, which can promote interest in sustainable innovations.     

Can Protection Motivation Theory predict pro-environmental behavior? Explaining the adoption of electric vehicles in the Netherlands

Scholars have proposed that the Protection Motivation Theory provides a valuable framework to explain pro-environmental choices, by employing a wide set of predictors, such as the costs and benefits of current (maladaptive) behavior as well as prospective adaptive behavior. However, no comprehensive empirical tests of the Protection Motivation Theory in the slow onset environmental risk domain have been published yet to our knowledge. This paper aims at closing this gap. We first conceptualized the Protection Motivation Theory for the use in this environmental domain. Next, we present results of a questionnaire study among a large representative sample of Dutch drivers that showed that the Protection Motivation Theory is a relevant theory for modeling different indicators of full electric vehicle adoption. Notably, all theoretical antecedents proved to be significant predictors of different adoption indicators. Respondents were particularly more likely to adopt an electric vehicle when they perceived the negative consequences caused by conventional vehicles as more severe, and when they expected electric vehicles to decrease these consequences. The most important barriers for electric vehicle adoption were perceived high monetary and non-monetary costs of electric vehicles, and benefits associated with the use of a conventional vehicle. Interestingly, we found that environmental risks are more prominent in predicting close adoption indicators; while energy security risks are more prominent in predicting distant adoption indicators. As expected, our findings suggest that both collective concerns and individual concerns predict different indicators of adoption. Individual concerns (in particular perceived costs of driving an electric vehicle) played a more prominent role when predicting close measures of adoption, while collective concerns (e.g., perceived severity of environmental and energy security risks) played a somewhat more prominent role when predicting distant measures of adoption. Implications for research and practice are provided.