2022冬奥会背景下北京区域居民参与冰雪运动消费调查

运用文献资料、问卷调查和数理统计、应用因子分析方法,结合北京区域滑雪场空间分布情况,对比居民冰雪运动参与倾向和频率,发现北京区域居民参与冰雪运动及消费的主要影响因素为性别、年龄、距离、收入水平和政策红利;分析得出雪场密度和区域经济水平、性别等对参与冰雪运动消费特征的影响。归纳4个主要影响北京区域居民参与冰雪运动的公共因子,分别是冰雪运动基础因子、冰雪运动信息因子、冰雪运动距离因子以及冰雪运动友谊因子。提出不断提升冰雪运动产品服务质量,出台鼓励性冰雪运动消费政策,完善冰雪运动消费环境,创新冰雪运动消费内容,逐步扩大冰雪消费规模等建议。     

基于因子分析和聚类分析的公众雾霾敏感度差异研究 ——以西安市为例

为研究公众的雾霾敏感度,以西安市13个区为案例地,运用因子分析法对公众的敏感度进行降维,引入潜在冲突指数(PCI)分析公众雾霾敏感度各维度的内部差异,并对公众进行分类。结果表明:(1)公众的雾霾敏感度可分为5个维度,分别是防护行为、降霾行为、雾霾关注度、生活影响感知和健康影响感知;(2)公众在防护行为、降霾行为、生活影响感知和健康影响感知方面意见一致,且敏感度较高;在雾霾关注度方面,公众之间的分歧较大,雾霾关注度小的公众敏感度较低;(3)基于以上5个维度,将公众分为防护敏感群体、关注度敏感群体、健康敏感群体和环保敏感群体。     

A GIS Approach to Exploring Monetary Value on Enclosure Era Property-Related Maps

Historical enclosure era property-related maps can tell us a great deal about the life and times of communities in the past. This study offers a unique approach to studying the historical landscape by applying GIS techniques to the examination of an eighteenth-century English village. Using novel GIS applications relying on historical maps, the study explores various aspects of the village’s physical and social characteristics. In doing so, the study forges effective linkages between cultural and landscape variables to reveal aspects of the historical landscape in eighteenth-century Britain previously inaccessible to researchers. This, in turn, provides a much more comprehensive and sophisticated template for future use by historical geographers in a number of contexts.     

Fuzzy logic and multi-criteria methods for groundwater potentiality mapping at Al Fo’ah area,the United Arab Emirates (UAE): an integrated approach

This study has modified an approach based on fuzzy logic in a GIS and multi-criteria decision making (MCDM) for groundwater potentiality mapping in Al Fo’ah area, the United Arab Emirates. The proposed approach uses nine groundwater conditioning factors recognized by local hydrology experts. Each factor and class of each factor was given a weight and score based on its level of contributions to groundwater accumulation using analytical hierarchy process and MCDM. Our results revealed that the areas of very high harbouring groundwater are located at the foot of the Oman mountains and occupies an area of about 8.46 km² (4%) of the study area. We validated our results using the Relative Operating Characteristics. The area under the curve showed a ratio of 0.8957 (of 89.57%). The modified approach is timely and economically effective and can be applied in semi-arid regions to help hydrologists.     

Discovering spatial and temporal patterns from taxi-based Floating Car Data: a case study from Nanjing

Floating Car Data (FCD) refers to the trajectories of vehicles equipped with Global Positioning System-enabled devices that automatically record location-related data within a short time interval. As taxies in Chinese cities continually drive along the streets seeking passengers, FCD can easily traverse the entire street network in a city on a daily basis. Taking advantage of this situation, this study extracted passenger pickup and drop-off locations from FCD sourced from 6445 taxis over a 2-week period in Nanjing, China to discover human behavioral patterns and the dynamics behind them. In this study, road nodes are converted to the points, based on which Thiessen polygons are generated to divide the study area into small areas with the goal of exploring the spatial distribution of pickup and drop-off locations. Moran’s I index is used to calculate the spatial autocorrelation of the spatial distribution of pickup and drop-off locations, and hot spot analysis is used to identify statistically significant spatial clusters of hot and cold spots. The spatial and temporal patterns of FCD in the study area are investigated, and the results show that: (1) the temporal patterns show a strong daily rhythm, (2) the spatial patterns show that the number of pickup and drop-off locations gradually diminish from the downtown areas to the outer suburbs, (3) the spatiotemporal patterns exhibit large differences over time, and (4) the driving forces explored by regression models indicate that population density and transportation density are consistent with the population distribution, but per capita disposable income is not consistent with the population distribution.     

Fishing in the Amazonian Forest: A Gendered Social Network Puzzle

We employ social network analysis (SNA) to describe the structure of subsistence fishing social networks and to explore the relation between fishers’ emic perceptions of fishing expertise and their position in networks. Participant observation and quantitative methods were employed among the Tsimane’ Amerindians of the Bolivian Amazon. A multiple-regression quadratic assignment procedure was used to explore the extent to which gender, kinship, and age homophilies influence the formation of fishing networks. Logistic regressions were performed to determine the association between fishers’ expertise, their sociodemographic identities, and network centrality. We found that fishing networks are gendered and that there is a positive association between fishers’ expertise and centrality in networks, an association that is more striking for women than for men. We propose that a social network perspective broadens understanding of the relations that shape the intracultural distribution of fishing expertise, as well as natural resource access and use.     

跨区域线性文化遗产类旅游资源价值评价——以长安-天山廊道路网中国段为例

跨区域线性文化遗产是一类特殊的旅游资源。基于其特殊性,以其各遗产点的价值评价作为整个遗产的价值评价;借助层次分析法、菲什拜因-罗森伯格模型,通过设定评分标准与评价等级,构建跨区域线性文化遗产旅游资源价值评价模型;实证分析认为提出的方法与模型能较准确地评价资源价值,长安-天山廊道路网中国段各遗产点价值均在优良等级及以上,其中27.3%为五级（特品级）资源,59.1%为四级资源,13.6%为三级资源,在旅游开发中应采取领先开发或重点开发、分区开发及加强遗产点历史文化挖掘与宣传普及等策略。     

Analysis of the coupled relationship between grain yields and agricultural labor changes in China

In this paper we establish a model that expresses the coupled relationship between grain yield and agricultural labor changes in China, and present a preliminary discussion of the coupled processes involved in changes in these factors at the county level. Thus, we develop two coefficients on the basis of county-level statistical data for grain yield and agricultural labor for the years 1991, 2000, and 2010, namely, the grain-labor elasticity coefficient (GLEC) and the agricultural labor-transfer effect coefficient (ALTEC). The results of this study show that during the transformation process of agricultural development in China, different kinds of coupled relationships between grain yield and agricultural labor changes co-existed at the same time. For example, between 1991 and 2010, counties characterized by three different coupled modes (i.e., increasing grain yield and decreasing agricultural labor, increasing grain yield and agricultural labor, and decreasing grain yield and agricultural labor) account for 48.85%, 29.11%, and 19.74% of the total across the study area, respectively. Interestingly, a coupled relationship between increasing grain yield and decreasing agricultural labor is mainly concentrated in the traditional farming areas of China, while a coupled relationship between increasing grain yield and agricultural labor is primarily concentrated in pastoral areas and agro-pastoral ecotones in underdeveloped western China. At the same time, a coupled relationship between decreasing grain yield and agricultural labor is concentrated in areas that have experienced a rapid development transition in agriculture, especially the developed southeastern coast of China. The results of this study also show that between 1991 and 2010, 1961 counties experienced a decline in the proportion of agricultural labor; of these, 1452 are also characterized by increasing grain yield, 72.38% of the total. This coupled relationship between grain yield and changes in the proportion of agricultural labor shows a stepped fluctuation and has continually strengthened over time. Data show that mean values for the GLEC and ALTEC increased from–0.25 and–2.93 between 1991 and 2000 to–0.16 and–1.78 between 2000 and 2010, respectively. These changes in GLEC and ALTEC illustrate that the influence of agricultural labor changes on increasing grain yields has gradually diminished. Finally, the results of this study reveal that the ‘Hu Huanyong Line’ is a significant boundary sub-dividing this coupled relationship between grain yield and changes in agricultural labor.     

Characterizing mixed-use buildings based on multi-source big data

To-date few research has successfully integrated big data from multiple sources to characterize urban mixed-use buildings. In this paper, we introduce a probabilistic model to integrate multi-source and geospatial big data (social network data, taxi trajectories, Points of Interest and remote sensing images) to characterize urban mixed-use buildings. The usefulness of our model is demonstrated with a case study of the Tianhe District in megacity Guangzhou, China. The model predicted building functions at 85% accuracy based on ground truth data from field surveys. We further explored the spatial patterns of the identified building functions. Most mixed-use buildings are located along major streets. Our proposed model can identify mixed-use buildings in a city; information is useful for planning evaluation and urban policymaking.     

Empirical calibration of climate policy using corporate solvency: a case study of the UK’s carbon price support

Emission reductions improve the chances that dangerous anthropogenic climate change will be averted, but could also cause some firms financial distress. Corporate failures, especially if they are unnecessary, add to the social cost of abatement. Social value can be permanently destroyed by the dissolution of organizational capital, deadweight losses paid to liquidators, and unemployment. This article proposes using measures of corporate solvency as an objective tool for policy makers to calibrate the optimal stringency of climate change policies, so that they can deliver the least loss of corporate solvency for a given level of emission reductions. They could also be used to determine the generosity of any compensation to address losses to corporate solvency. We demonstrate this approach using a case study of the UK’s Carbon Price Support (a carbon tax).

Key policy insights

• Solvency metrics could be used to empirically calibrate the optimal stringency of climate policies.

• An idealized solvency trajectory for firms affected by climate change policy would cause corporate solvency to initially decline – approaching but not exceeding ‘distressed’ levels – and then gradually improve to a new ‘steady state’ once the low-carbon transition had been achieved.

• In terms of the UK’s Carbon Price Support, corporate solvency of energy-intensive industries was found to be stable subsequent to its introduction. Therefore, the available evidence does not support its later weakening.