基于GPS数据的城市居民通勤弹性研究——以北京市郊区巨型社区为例

通勤是居民出行行为的重要组成部分,受到地理、规划、交通等领域的广泛关注,已有对通勤的研究多利用问卷调查数据,定位技术与信息通信技术为个体行为时空数据的采集带来了新的契机。本研究关注个体在不同工作日中通勤的可变性,将活动弹性的概念引入对通勤行为的研究中,提出通勤弹性的概念,并界定了时间、空间、方式、路径4 个通勤弹性维度,通过探讨4 种弹性之间的相互作用关系,提出7 种基于弹性的理论通勤模式。研究以北京市天通苑与亦庄两个郊区巨型社区为案例,基于活动日志与GPS 定位数据相结合的为期一周的居民时空行为数据,分别利用传统方法和通勤弹性视角研究居民的通勤特征,验证通勤弹性现象的存在以及该视角透视城市居民通勤行为的合理性,并利用GIS 三维可视化技术对7 种理论通勤模式居民的活动—移动时空特征进行刻画,从而透视北京市郊区巨型社区居民的通勤特征及复杂模式,为北京市城市与交通问题的解决提供了独特的视角。     

基于近地层垂直速度能谱尺度特征确定复杂下垫面零平面位移

本文利用位于南京市郊区的南京大学仙林校区SORPES观测站多层湍流观测数据分析了湍流谱特征,以白天不稳定条件下垂直速度能谱谱峰对应的长度尺度也就是离地高度为判据,探讨了运用该方法确定复杂下垫面零平面位移的可行性。统计分析表明,该方法确定的长度尺度呈现出较为一致的概率分布形状,概率最大的长度尺度对应于离地高度,在复杂下垫面情况下这个高度就是零平面位移高度到观测高度之间的距离,将观测点的离地高度减去这个距离就能得到零平面位移。本文同时运用不稳定条件下垂直速度方差在近地层中的相似关系来确定零平面位移,并与谱方法得到的结果进行对比。结果表明,谱方法和方差法得到的零平面位移非常接近。     

城市化进程对重庆都市圈降水空间分布的影响

基于1969-2017年全国站点逐日降水资料、地形高度资料以及2017年全国常住人口数据,采用概率密度函数PDF法、最小二乘法、Mann-Kendall法和累积距平法等多种统计分析方法,结合中国地形多样性,从降水量的PDF特征、变化趋势和极端降水特征三个方面,分析了近49 a中国30°N带不同地形下大城市与其郊区的降水特征,结果表明：（1）中国30°N带降水的区域性和极端性明显,其中长江入海口代表站的年降水量PDF曲线最接近正态分布;极端降水阈值和极端降水强度基本为自西向东增加,且与地形高度呈反比关系;对于暴雨及以上等级的降水,代表站降水概率小但降水占比大。（2）降水的城市化效应明显,表现为代表站的日、月、季、年降水量PDF曲线普遍存在城郊差异,且日和年尺度的差异较月和季的尺度差异更明显;大城市代表站相对于其郊区代表站,前者年降水量普遍增加得快,且最小值大于后者;前者极端降水阈值、极端降水强度和年最大日降水量最大值普遍大于后者,且发生中雨及以上等级强降水的概率和占比较后者大。（3）代表站降水存在明显的年际变化和季节变化,存在一定的周变化;年降水量的突变时间集中发生在1980s中、后期以及1990s至2000s初;降水量的季节变化特征为夏季最多、冬季最少,其中江汉平原、长江中下游、长江入海口地形下夏季降水的城市化效应明显;大部分地形下工作日降水的城市化效应较休息日明显。

     

The effect of terrain factors on rice production: A case study in Hunan Province

Journal of Geographical Sciences - Rice (Oryza sativa L.) is the most important staple crop of China, and its production is related to both natural condition and human activities. It is fundamental...     

Modeling uncertainty of moving objects on road networks via space–time prisms

Moving objects produce trajectories, which are typically observed in a finite sample of time‐stamped locations. Between sample points, we are uncertain about the moving objects's location. When we assume extra information about an object, for instance, a (possibly location‐dependent) speed limit, we can use space–time prisms to model the uncertainty of an object's location.

Until now, space–time prisms have been studied for unconstrained movement in the 2D plane. In this paper, we study space–time prisms for objects that are constrained to travel on a road network. Movement on a road network can be viewed as essentially one‐dimensional. We describe the geometry of a space–time prism on a road network and give an algorithm to compute and visualize space–time prisms. For experiments and illustration, we have implemented this algorithm in MATHEMATICA.

Furthermore, we study the alibi query, which asks whether two moving objects could have possibly met or not. This comes down to deciding if the chains of space–time prisms produced by these moving objects intersect. We give an efficient algorithm to answer the alibi query for moving objects on a road network. This algorithm also determines where and when two moving objects may have met.     

Cartograms for Use in Forecasting Weather-Driven Natural Hazards

This paper evaluates the potential of using cartograms for visualizing and interpreting forecasts of weather-driven natural hazards in the context of global weather forecasting and early warning systems. The use of cartograms is intended to supplement traditional cartographic representations of the hazards in order to highlight the severity of an upcoming event. Cartogrammetric transformations are applied to forecasts of floods, heatwaves, windstorms and snowstorms taken from the European Centre for Medium-range Weather Forecasts (ECMWF) forecast archive. Key cartogram design principles in standard weather forecast visualization are tested. Optimal cartogram transformation is found to be dependent on geographical features (such as coastlines) and forecast features (such as snowstorm intensity). For highly spatially autocorrelated weather variables used in analysing several upcoming natural hazards such as 2m temperature anomaly, the visualization of the distortion provides a promising addition to standard forecast visualizations for highlighting upcoming weather-driven natural hazards.     

栅格数字地形分析中的尺度问题研究方法

栅格数字高程模型（DEM）固有的尺度特征给以栅格DEM为基本输入的数字地形分析带来各种尺度问题。对栅格数字地形分析中涉及的尺度进行梳理,以分辨率和分析窗口为重点,对栅格数字地形分析中的多尺度表达、尺度效应、适宜尺度选择、尺度转换等尺度问题及其相互关系进行阐述;分别介绍各类尺度问题的现有定量研究方法,尤其对尺度效应定量刻画和适宜尺度选择方法,根据不同方法计算定量指标所利用的信息类别进行分类归纳;最后讨论了其中有待进一步开展研究的几方面工作。     

Simulation on slope uncertainty derived from DEMs at different resolution levels： a case study in the Loess Plateau

Slope is one of the crucial terrain variables in spatial analysis and land use planning, especially in the Loess Plateau area of China which is suffering from serious soil erosion. DEM based slope extracting method has been widely accepted and applied in practice. However slope accuracy derived from this method usually does not match with its popularity. A quantitative simulation to slope data uncertainty is important not only theoretically but also necessarily to applications. This paper focuses on how resolution and terrain complexity impact on the accuracy of mean slope extracted from DEMs of different resolutions in the Loess Plateau of China. Six typical geomorphologic areas are selected as test areas, representing different terrain types from smooth to rough. Their DEMs are produced from digitizing contours of 1:10,000 scale topographic maps. Field survey results show that 5 m should be the most suitable grid size for representing slope in the Loess Plateau area. Comparative and math-simulation methodology was employed for data processing and analysis. A linear correlativity between mean slope and DEM resolution was found at all test areas, but their regression coefficients related closely with the terrain complexity of the test areas. If taking stream channel density to represent terrain complexity, mean slope error could be regressed against DEM resolution (X) and stream channel density (S) at 8 resolution levels and expressed as(0.0015S2 0.031S-0.0325)X-0.0045S2-0.155S 0.1625, with a R2 value of over 0.98. Practical tests also show an effective result of this model in applications. The new development methodology applied in this study should be helpful to similar researches in spatial data uncertainty investigation.     

Making a Mark: a computational and visual analysis of one researcher’s intellectual domain

Dr. David Mark is widely regarded as a path-breaking researcher in geographic information science. What are the structural and temporal characteristics of his intellectual contributions, as seen through the eyes of the broader academic community? Aiming to answer that question, this article presents a scientometric analysis of publications that have been cited alongside David Mark’s papers. In deliberate contrast to the widespread focus on using citation data to condense scientific impact into a handful of indicators, the methodological contribution of this study lies in its mix of computational and visualization approaches. In the search for latent domain structures, state-of-the-art practices in information science, bibliometrics, and network visualization are combined and extended. An initial network of 50,000+ publications and 4,000,000+ document co-citations undergoes a series of transformations reducing it to 9000 publications that are then clustered in a two-stage process, leading to 678 communities whose co-citation linkages are used to delineate 19 super-communities. To enable replication of this approach for other studies, much focus in this article is on detailed discussion of that workflow as well as on highlighting the reasoning behind the choices made among data sources and analytical methods. The topical evolution of David Mark’s domain of influence is explored in some detail, based on tabular and graphic representations of extracted community structures. Results confirm not only the enormous overall breadth of his influence but also how lasting and recurrent it has been in some areas.     

福建省复杂地形下旬平均气温分布式模拟

为建立高时空分辨率的福建省复杂地形下气温栅格数据集,利用福建省及其周边33个常规气象站观测资料,基于数字高程模型（DEM）数据,综合考虑海拔、太阳总辐射、地表长波有效辐射对旬平均气温的影响,模拟了福建省复杂地形下旬均温的空间分布。结果表明：1）常规站验证结果显示：各旬气温绝对误差平均值（MAE）最小为0.46℃,最大为2.3℃,全年平均为0.87℃;加密站验证结果显示,MAE最大为2.3℃,最小0.5℃,全年平均为0.96℃。2）模拟结果能反映旬均温的宏观分布规律与局地细节特征。宏观范围内,旬均温受纬度影响较大,由北至南气温逐渐升高,沿海地区旬均温整体高于内陆,山区旬均温明显较低;局地范围内,各坡向上气温差异显著,海拔越高、坡度越大,差异越明显;地形因子对旬平均温的影响具有季节差异,具体表现为冬季时地形因子对旬均温的影响最大,秋季次之,春夏季节中地形因子对旬均温的影响最弱。