中国城乡家庭能源平等变化特征分析

能源转型是中国如期实现碳中和、碳达峰目标的必然路径,也是缩小城乡居民能源消费差距、实现能源平等的关键举措。基于2013年和2017年的家庭追踪调查数据,运用基尼系数、局部加权回归以及逐步回归等方法,在揭示中国城乡家庭能源平等的时空特征、能源转型效果基础上,定量评价影响地区间、城乡间家庭能源平等的驱动因素。结果表明：① 中国城乡家庭的能源消费水平总体呈明显不平等特征,但随着能源转型政策实施以及城乡融合进程加速,城乡家庭间能源不平等程度有所减小。② 对10609个城乡家庭样本、9类分区的比较显示,除长三角地区的家庭能源平等性较高外,其他地区均呈不同程度的非均衡性,尤其在云贵等西南地区的家庭能源不平等现象尤为突出。③ 家庭收入、家庭规模、城乡居住区位、气候条件以及现代化能源可获得性显著影响家庭能源支出,进而对区域间的家庭能源平等性造成影响,而当地的能源资源禀赋对家庭能源支出的影响并不显著。④ 尽管农村地区气态能源、电力资源普及有效推动了城乡家庭能源转型,但农村家庭需担负相较于城镇家庭居民更大的能源转型经济压力。     

岩石的脆性-延性转变及塑性流动网络

实验变形研究表明.随着矿物组成.粒度、温度、围压、应变率、液体介质等因素的变化岩石由脆性,半脆性,向半延性.延性转变,其中包括力学行为.微观机制和宏观结构的变化,而决定岩石脆性-延性转变的基本因素在于所含的粘塑性成分及其粘滞性.半延性流动具有共轭网络状的结构特征;延性流动则包括网络状流动和均匀流动两种宏观结构;半延性-延性流动网络以其近似正交性和非牛顿流动特性分别与半脆性破裂网络和均匀延性流动相区别.基于上述研究,可将地壳、上地幔划分为脆性-半脆性的中上地壳,半延性-延性网络状流动的岩石圈下层(含下地壳和岩石圈地幔)和均匀延性流动的软流圈.地壳多震层内的大型地震带及网络是岩石圈下层塑性流动网络的一种响应.     

热带气旋变性过程客观判别方法在“海马”变性过程中的应用

介绍了一种判别热带气旋变性过程的客观方法.此客观方法使用三个判别参数: 对流层低层热力非对称参数B、高低层的热成风、对变性过程进行诊断判别.此方法使用格点的数值预报产品,计算简单、使用方便,便于业务化.同时针对2004年影响我国的0421号热带风暴"海马",使用NCEP再分析资料对其变性过程进行了分析验证,结果表明:此客观方法所定义的三个判别参数B、、在"海马"的变性过程中有很好的指示作用.     

基于模糊贴近度的SAR影像变化检测方法研究

经典的基于比算子的差异图构造方法,主要是针对单一像素进行运算,因此影像噪声对差异图有一定程度的影响.将模糊贴近度应用于差异图的构造过程中,利用经典算子和模糊贴近度分别构造差异图;然后对差异图进行双边滤波和灰度过渡区域提取,从而确定影像分割阈值,得到两期影像变化结果;最后采用相关的参数指标对结果进行分析评价.结果 表明,...     

盘锦市湿地信息提取与动态变化监测

针对近年来盘锦市湿地动态变化信息相对匮乏的问题,提出了基于Landsat遥感影像,采用决策树模型进行湿地信息提取,运用景观生态学及转移矩阵模型进行湿地变化分析的湿地动态变化监测方法。在决策树分类技术支持下,实现光谱特征、环境特征和空间特征等多特征融合,完成研究区三期湿地信息提取。通过与地理国情监测数据对比分析,验证了实验提取结果满足湿地动态变化监测需求。实验结果表明,所提方法可以从空间格局、景观格局及空间演变特征上,对盘锦市湿地变化进行全面的定性和定量分析,研究结果可供盘锦市湿地的管理和保护工作参考。     

Regional Concentration and Region-Based Urban Transition: China's Mega-Urban Region Formation in the 1990S

Since 1978, China has experienced rapid continuous urban transformation, and many mega-urban regions have stood out. But how to measure mega-urban region formation and to what extent they have formed in China, are still questions that have not been fully answered. Using census data by county, this study illustrates China's intensifying population concentration and region-based urban transition in 1990s. By 2000, three geographically continuous regional concentrations had formed in China —Beijing-Tianjin-Tangshan (Jing-Jin-Tang), the Yangzi River Delta (YRD), and the Pearl River Delta (PRD). All were characterized by region-based urban transition, with their "remote rural areas"³ involved in economic transformation; elsewhere, population agglomeration and urban transformation still focused mainly on major cities and their peripheral zones. It is the coexistence of great global attraction and severe local challenges in these mega-urban regions that makes them distinct from other metropolitan areas.     

An extended cellular automaton using case‐based reasoning for simulating urban development in a large complex region

Rule‐based cellular automata (CA) have been increasingly applied to the simulation of geographical phenomena, such as urban evolution and land‐use changes. However, these models have difficulties and uncertainties in soliciting transition rules for a large complex region. This paper presents an extended cellular automaton in which transition rules are represented by using case‐based reasoning (CBR) techniques. The common k‐NN algorithm of CBR has been modified to incorporate the location factor to reflect the spatial variation of transition rules. Multi‐temporal remote‐sensing images are used to obtain the adaptation knowledge in the temporal dimension. This model has been applied to the simulation of urban development in the Pearl River Delta which has a hierarchy of cities. Comparison indicates that this model can produce more plausible results than rule‐based CA in simulating this large complex region in 1988–2002.     

Response to ‘Comments on “Combining spatial transition probabilities for stochastic simulation of categorical fields” with communications on some issues related to Markov chain geostatistics’

Li and Zhang (2012b Li, W. and Zhang, C. 2012b. Comments on ‘Combining spatial transition probabilities for stochastic simulation of categorical fields’ with communications on some issues related to Markov chain geostatistics. International Journal of Geographical Information Science, 26(10): 1725–1739. [Taylor & Francis Online] , [Google Scholar], Comments on ‘Combining spatial transition probabilities for stochastic simulation of categorical fields’ with communications on some issues related to Markov chain geostatics) raised a series of comments on our recent paper (Cao, G., Kyriakidis, P.C., and Goodchild, M.F., 2011 Cao, G., Kyriakidis, P.C. and Goodchild, M.F. 2011. Combining spatial transition probabilities for stochastic simulation of categorical fields. International Journal of Geographical Information Science, 25(11): 1773–1791. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar]. Combining spatial transition probabilities for stochastic simulation of categorical fields. International Journal of Geographical Information Science, 25 (11), 1773–1791), which include a notation error in the model equation provided for the Markov chain random field (MCRF) or spatial Markov chain model (SMC), originally proposed by Li (2007b Li, W. 2007b. Markov chain random fields for estimation of categorical variables. Mathematical Geology, 39(3): 321–335. [Crossref] , [Google Scholar], Markov chain random fields for estimation of categorical variables. Mathematical Geology, 39 (3), 321–335), and followed by Allard et al. (2011 Allard, D., D'Or, D. and Froideveaux, R. 2011. An efficient maximum entropy approach for categorical variable prediction. European Journal of Soil Science, 62: 381–393. [Crossref], [Web of Science ®] , [Google Scholar], An efficient maximum entropy approach for categorical variable prediction. European Journal of Soil Science, 62, 381–393) about the misinterpretation of MCRF (or SMC) as a simplified form of the Bayesian maximum entropy (BME)-based approach, the so-called Markovian-type categorical prediction (MCP) (Allard, D., D'Or, D., and Froideveaux, R., 2009 Allard, D., D'Or, D. and Froidevaux, R. 2009. Estimating and simulating spatial categorical data using an efficient maximum entropy approach, Avignon: Unité Biostatistique et Processus Spatiaux Institut National de la Recherche Agronomique. Technical Report No. 37 [Google Scholar]. Estimating and simulating spatial categorical data using an efficient maximum entropy approach. Avignon: Unite Biostatisque et Processus Spatiaux Institute National de la Recherche Agronomique. Technical Report No. 37; Allard, D., D'Or, D., and Froideveaux, R., 2011 Allard, D., D'Or, D. and Froideveaux, R. 2011. An efficient maximum entropy approach for categorical variable prediction. European Journal of Soil Science, 62: 381–393. [Crossref], [Web of Science ®] , [Google Scholar]. An efficient maximum entropy approach for categorical variable prediction. European Journal of Soil Science, 62, 381–393). Li and Zhang (2012b Li, W. and Zhang, C. 2012b. Comments on ‘Combining spatial transition probabilities for stochastic simulation of categorical fields’ with communications on some issues related to Markov chain geostatistics. International Journal of Geographical Information Science, 26(10): 1725–1739. [Taylor & Francis Online] , [Google Scholar], Comments on ‘Combining spatial transition probabilities for stochastic simulation of categorial fields’ with communication on some issues related to Markov chain geostatistics. International Journal of Geographical Information Science) also raised concerns regarding several statements Cao et al. (2011 Cao, G., Kyriakidis, P.C. and Goodchild, M.F. 2011. Combining spatial transition probabilities for stochastic simulation of categorical fields. International Journal of Geographical Information Science, 25(11): 1773–1791. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar], Combining spatial transition probabilities for stochastic simulation of categorical fields. International Journal of Geographical Information Science, 25 (11), 1773–1791) had made, which mainly include connections between permanence of ratios and conditional independence, connections between MCRF and Bayesian networks and transiograms as spatial continuity measures. In this response, all of the comments and concerns will be addressed, while also communicating with Li and other colleagues on general topics in Markov chain geostatistics.     

Interest in intermediate soft-classified maps in land change model validation: suitability versus transition potential

This study compares two types of intermediate soft-classified maps. The first type uses land use/cover suitability maps based on a multi-criteria evaluation (MCE). The second type focuses on the transition potential between land use/cover categories based on a multi-layer perceptron (MLP). The concepts and methodological approaches are illustrated in a comparable manner using a Corine data set from the Murcia region (2300 km², Spain) in combination with maps of drivers that were created with two stochastic, discretely operating, commonly used tools (MCE in CA_MARKOV and MLP in Land Change Modeler). The importance of the different approaches and techniques for the obtained results is illustrated by comparing the specific characteristics of both approaches by validating the suitability versus transition potential maps to each other using a Spearman correlation matrix and, between the Corine maps, using classical ROC (receiver operating characteristic) statistics. Then, we propose a new use of ROC statistics to compare these intermediate soft-classified maps with their respective hard-classified maps of the models for each category. The validation of these results can be beneficial in choosing a suitable model and provide a better understanding of the implications of the different modeling steps and the advantages and limitations of the modeling tools.     

Geopolitical Legacies and Central European Export Linkages: A Historical and Gravity Model Analysis of Hungary

This paper analyzes Hungary's export linkages of the interwar and Cold War periods using gravity model and historical analyses. Hungary is a useful example of former Soviet satellites because it combines relative political stability (since 1956) and experimentation with the New Economic Mechanism (NEM) during the 1970s and 1980s. Historical analysis reveals seven events since World War I that changed Hungary's trade patterns. Gravity model analysis for 1955, 1965, 1975, and 1985 shows the dramatic cleavage of the “Iron Curtain,” the effect of the NEM, and particularly strong and weak linkages for Hungarian trade that may result from historical legacies, complementarity, or specific political contacts.