Geography and Planning: Some Perspectives

This paper analyzes the migration of Puerto Rican-born women from the United States to Puerto Rico using longitudinal data. We hypothesize that sojourn length in the United States is a function of both structural (macro-level economic and cultural factors) and behavioral (micro-level life-cycle experiences and personal attributes) variables. We test these hypotheses by estimating a proportional hazards model. The parameter estimates of this model indicate that sojourn length in the United States, and thus the decision to return to Puerto Rico, is a function of wage trends and community characteristics on the mainland plus a number of individual attributes that include education, marriage, and childbirth.     

1977-2010年青海湖环湖区土地利用/覆盖变化与土地资源管理

青海湖流域是青海省主要牧场,也是青藏高原东北部重要的生态安全屏障.本文以1977、1987、2000、2004年和2010年遥感影像、MODIS NDVI为基础数据,通过数学模型、一元线性回归、景观格局指数的方法分析了青海湖环湖区土地利用/覆盖时空变化及景观格局特点,探讨了土地利用/覆盖变化的影响因素,最后提出青海湖环湖区土地资源管理建议.研究结果表明:近33年来青海湖环湖区土地利用/覆盖变化显著,草地、林地、水体等生态用地面积总体减少,耕地、建设用地、未利用地面积逐渐增加,土地利用/覆盖变化整体处于不平衡态,单向转换频繁;植被覆盖度总体微弱增加,变化趋势具有空间差异性;由于人类的定向选择,草地景观类型退化,景观格局趋向破碎化;土地利用/覆盖与景观格局变化是环湖区气温升高、降水增加、载畜量超载、旅游等因素共同作用的结果;基于土地利用/覆盖变化特点和影响因素,提出创建“生态友好”型土地资源管理模式,实现人地关系协调发展.     

A review on statistical models for identifying climate contributions to crop yields

Statistical models using historical data on crop yields and weather to calibrate relatively simple regression equations have been widely and extensively applied in previous studies, and have provided a common alternative to process-based models, which require extensive input data on cultivar, management, and soil conditions. However, very few studies had been conducted to review systematically the previous statistical models for indentifying climate contributions to crop yields. This paper introduces three main statistical methods, i.e., time-series model, cross-section model and panel model, which have been used to identify such issues in the field of agrometeorology. Generally, research spatial scale could be categorized into two types using statistical models, including site scale and regional scale (e.g. global scale, national scale, provincial scale and county scale). Four issues exist in identifying response sensitivity of crop yields to climate change by statistical models. The issues include the extent of spatial and temporal scale, non-climatic trend removal, colinearity existing in climate variables and non-consideration of adaptations. Respective resolutions for the above four issues have been put forward in the section of perspective on the future of statistical models finally.     

山岳型旅游目的地形象感知研究——以五台山风景名胜区为例

以山岳型旅游目的地五台山风景区为例,利用百度、Google以及国内各旅游网站收集游客记述五台山旅游形象的87篇网络游记和620条网上点评,运用质性研究之扎根理论的方法对五台山申遗后旅游形象的感知进行研究,以期为山岳型旅游目的地形象研究拓展方法和为其管理提供参考和依据.结果表明:1.从71篇网络游记和490条网络点评中提取出佛教胜地、静心拜佛、避暑胜地、建筑精湛、许愿还愿和朝台览胜6大积极感知因素;2.从226句负面评论中,归纳出五台山旅游形象的6个消极感知因素为旅游供给、旅游环境、旅游设施、旅游管理、旅游吸引和旅游服务;3.同时,典故传说、佛缘之地、民风淳朴亦为五台山旅游形象的积极感知因素.     

Evaluating the Temporal and Spatial Urban Expansion Patterns of Guangzhou from 1979 to 2003 by Remote Sensing and GIS Methods

China has experienced and is experiencing expeditious urban expansion in the recent decades, especially in the coastal areas and big cities. Rapid urban expansion and dramatic changes of landscape have caused great economic, environmental and social impacts consequently. It is crucial to understand urban temporal, spatial expansion patterns and their related effects. In this paper, urban expansion of Guangzhou, a rapid growing city in south‐east China, from 1979 to 2003 is studied temporally and spatially. Four time ranges including 1979–1990, 1990–1995, 1995–2000 and 2000–2003 are designed and the urban expansion area, expansion rate and the spatial expansion pattern are discussed by using remote sensing data and Geographical Information System (GIS) tool. Two transects are designed along two axes of Guangzhou expansion and the structural of urban expansion patches at different orientations are compared in order to quantitively understand the urban expansion of Guangzhou during the past 24 years. The gradient analysis integrating multi‐temporal data is performed in order to analyze and compare the spatial and temporal dynamics of urban expansion. Two indices of compactness and fractal dimensional index are used to describe the urban developing pattern in the study time durations. And the influence of different types of traffic roads to urban expansion is evaluated using the buffer analysis of GIS. The results show that: (1) temporally, urban area of Guangzhou increase 296.54 km² from 141.15 km² in 1979 to 437.70 km² in 2003 and the increasing rate is up to 210.08%; (2) spatially, Guangzhou has different urban expanding directions in different stages and the general expanding directions are towards northeast, north, southeast and north in four studied time ranges; (3) transportation lines play a very important role in urban expansion of Guangzhou, but different types of road have different impacts. National roads and highways exhibit stronger control to urban expansion than provincial roads; and (4) expansion of Guangzhou has gradually changed from a compact pattern to leapfrogging and disordering patterns.     

Residual drift demands in moment‐resisting steel frames subjected to narrow‐band earthquake ground motions

This paper presents the main results of the evaluation of residual inter‐story drift demands in typical moment‐resisting steel buildings designed accordingly to the Mexican design practice when subjected to narrow‐band earthquake ground motions. Analytical 2D‐framed models representative of the study‐case buildings were subjected to a set of 30 narrow‐band earthquake ground motions recorded on stations placed in soft‐soil sites of Mexico City, where most significant structural damage was found in buildings as a consequence of the 1985 Michoacan earthquake, and scaled to reach several levels of intensity to perform incremental dynamic analyses. Thus, results were statistically processed to obtain hazard curves of peak (maximum) and residual drift demands for each frame model. It is shown that the study‐case frames might exhibit maximum residual inter‐story drift demands in excess of 0.5%, which is perceptible for building's occupants and could cause human discomfort, for a mean annual rate of exceedance associated to peak inter‐story drift demands of about 3%, which is the limiting drift to avoid collapse prescribed in the 2004 Mexico City Seismic Design Provisions. The influence of a member's post‐yield stiffness ratio and material overstrength in the evaluation of maximum residual inter‐story drift demands is also discussed. Finally, this study introduces response transformation factors, T_p, that allow establishing residual drift limits compatible with the same mean annual rate of exceedance of peak inter‐story drift limits for future seismic design/evaluation criteria that take into account both drift demands for assessing a building's seismic performance. Copyright © 2013 John Wiley & Sons, Ltd.     

Intensity–duration–frequency curves exploiting neighbouring extreme precipitation data

ABSTRACT

Records of precipitation extremes are essential for hydrological design. In urban hydrology, intensity–duration–frequency curves are typically estimated from observation records. However, conventional approaches seldom consider the areal extent of events. If they do, duration-dependent area reduction factors are used, but precipitation is measured at only a few locations. Due to the high spatial variability of precipitation, it is relatively unlikely that a gauged observation network will capture the extremes that occur during a precipitation event. Therefore, the area reduction approach cannot be regarded as the reduction of an observed maximum. To investigate precipitation extremes, spatial aspects need to be considered using different approaches. Here, we both address the conventional practice of area reduction and consider a within-area chance of increased precipitation, defined as the maximum precipitation intensity observed in a cluster within a selected domain. The results show that (1) the risk of urban flooding is routinely underestimated in current design practice, and (2) traditional calculations underestimate extremes by as much as 30–50%. We show how they can be revised sensibly.     

中国生物质能产业发展面临的矛盾和挑战

本文在分析中国生物质能产业发展现状的基础上,认为当前中国生物质能产业发展受到资源家底不清、政策环境不完善和生态保护压力等因素制约,存在着产业发展总体水平低,产业体系不健全,生产成本高,产业技术水平低,行业发展无序等问题。结合这些问题,立足我国资源环境承载能力,适应市场需求变化和科技进步趋势,本文提出今后重点加强生物质能产业发展政策扶持,生物质能原料资源调查评估,生物质能转化利用技术开发和能源产业示范基地建设,以期促进生物质能产业健康快速发展。     

The aboveground biomass of desert steppe and its spatiotemporal variation in western Inner Mongolia

A precise understanding of the aboveground biomass of desert steppe and its spatio-temporal variation is important to understand how arid ecosystems respond to climate change and to ensure that scarce grassland resources are used rationally. On the basis of 756 ground survey quadrats sampled in western Inner Mongolia steppe in 2005–2011 and remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS)—the normalized difference vegetation index (NDVI) dataset for the period of 2001–2011—we developed a statistical model to estimate the aboveground biomass of the desert steppe and further explored the relationships between aboveground biomass and climate factors. The conclusions are as follows: (1) the aboveground biomass of the steppe in the research area was 5.27 Tg (1 Tg=10¹² g) on average over 11 years; between 2001 and 2011, the aboveground biomass of the western Inner Mongolia steppe exhibited fluctuations, with no significant trend over time; (2) the aboveground biomass of the steppe in the research area exhibits distinct spatial variation and generally decreases gradually from southeast to northwest; and (3) the important factor causing interannual variations in aboveground biomass is precipitation during the period from January to July, but we did not find a significant relationship between the aboveground biomass and the corresponding temperature changes. The precipitation in this period is also an important factor influencing the spatial distribution of aboveground biomass (R²=0.39, P<0.001), while the temperature might be a minor factor (R²=0.12, P<0.01). The uncertainties in our estimate are primarily due to uncertainty in converting the fresh grass yield estimates to dry weight, underestimates of the biomass of shrubs, and error in remote sensing dataset.