Evaluating data stability in aggregation structures across spatial scales: revisiting the modifiable areal unit problem

ABSTRACT

Socioeconomic and health analysts commonly rely on areally aggregated data, in part because government regulations on confidentiality prohibit data release at the individual level. Analytical results from areally aggregated data, however, are sensitive to the modifiable areal unit problem (MAUP). Levels of aggregation as well as the arbitrary and modifiable sizes, shapes, and arrangements of zones affect the validity and reliability of findings from analyses of areally aggregated data. MAUP, long acknowledged, remains unresolved. We present an exploratory spatial data analytical approach (ESDA) to understand the scalar effects of MAUP. To characterize relationships between data aggregation structures and spatial scales, we develop a method for statistically and visually exploring the local indicators of spatial association (LISA) exhibited between a variable and itself across varying levels of aggregation. We demonstrate our approach by analyzing the across-scale relationships of aggregated 2010 median income for the State of Pennsylvania and 2005–2009 cancer diagnosis rates for the State of New York between county–tract, tract–block group, and county–block group level US census designated enumeration units. This method for understanding the relationship between MAUP and spatial scale provides guidance to researchers in selecting the most appropriate scales to aggregate, analyze, and represent data for problem-specific analyses.     

遥感数据时空尺度对地理要素时空变化分析的影响

地理要素的时空变化分析对于了解和掌握地表的规律性有着重要的作用。利用地面站点观测、实地调查等传统方式获取数据,对地理要素进行时空变化分析是最常用的方法。但该类方法往往表现的是"点尺度"观测,不能在大尺度情况下准确地反映地表的时空变化信息。遥感卫星能以一定的时间间隔获得空间连续的对地"面尺度"观测数据,然而其特定的空间和时间分辨率使其获取的地表信息仍十分有限。同时地表的空间异质性和个别地表短时间内的快速变化,使得利用遥感数据对地理要素进行时空变化分析时,时空变化分析结果会随观测尺度而发生改变。本文从空间尺度和时间尺度两方面综述遥感数据时空尺度对地理要素的时空变化分析产生的影响和原因,并针对这些问题总结了减小时空尺度对结果不确定性影响的现行方法。可以通过多源遥感协同观测和反演、尺度转换、空间建模等方法减小空间尺度引起的不确定性;通过联合多时相遥感数据的方法减小时间尺度引起的不确定性。在实际应用中,应根据所观测地理要素的实际情况,综合分析选择合适的方法。     

利用ECMWF和GPS估计大气可降水量

河南连续运行参考系统(Continuously Operating Reference Stations,CORS)有63个测站,但仅有6个测站安装有气象传感器,而且数据极其不完整,而气象数据对于(Global Positioning System,GPS)反演水汽十分重要.针对这一问题,研究了利用欧洲中期天气预报中心...     

A spatiotemporal analysis of aggregate labour force behaviour by sex and age across the European Union

This study investigates the causes of variation in age-specific male and female labour force participation rates using annual data from 154 regions across ten European Union member states for the period 1983–1997. Regional participation rates appear to be strongly correlated in time, weakly correlated in space and to parallel their national counterparts. An econometric model is designed consistent with these empirical findings. To control for potential endogeneity of the explanatory variables, we use an instrumental variables estimation scheme based on a matrix exponential spatial specification of the error terms. Many empirical studies of aggregate labour force behaviour have ignored population distribution effects, relying instead on the representative-agent paradigm. In order for representative-agent models to accurately describe aggregate behaviour, all marginal reactions of individuals to changes in aggregate variables must be identical. It turns out that this condition cannot apply to individuals across different sex/age groups.

卫星动态观测数据揭示中国地表色调分布及时序变化特征

本文对2001年—2010年的MODIS光谱反射率数据进行时空聚类,得到2001年—2010年8天合成的色调信息,并初步分析了中国地表色调的时空分布格局及变化趋势,得出以下主要结论:(1)中国地表主色调主要由代表植被的绿色、裸土的褐色、裸土与植被混合的黄色、水体的蓝色以及冰雪的白色这5种颜色组成。分布在西北地区的褐色在一年中4个季节都为主色调。NDVI值较低的绿色光谱簇在春秋冬3个季节都为主色调,分布在南方的热带、亚热带针叶林以及灌木区。NDVI值较高的绿色光谱簇只在夏季一个季节为主色调,分布在长江中下游、华南、西南以及东北部分地区。永久白色主要分布在西藏、青海、四川等多年积雪地区。(2)黄淮海平原农业区色调在一年中呈现褐色—绿色—褐色—绿色—褐色的变化,与第一轮生长—间歇—第二轮生长物候历一致。长江中下游以及华南水稻播种和插秧时节有独特的光谱簇,呈现出植被与水体混合的特征。从华南地区、长江中下游地区到河北、陕西、甘肃、宁夏再到黑龙江,从南到北呈现出作物播种时间推迟、收割时间提早、生长期变短的现象。(3)甘肃北部、四川北部、山西北部、河北北部是年际主色调在绿色和黄色之间变化最为频繁的区域。这些年际主色调变化频繁区域也是中国绿度变化最显著的区域,也是在LUCC分类中易产生错误的地区。     

精密单点定位中附加先验电离层改正的内插方法研究

在精密单点定位技术中,外部提供给接收机更多的先验信息能使其定位精度和实时性得到提高。依靠增强站网内插出流动站的电离层延迟进行非差非组合精密单点定位时,其提供的改正达到精度要求势必使待估参数减少,模型强度变强,定位精度高。本文对比了内插电离层改正的精度,探讨了内插模型,提出了平面双样条内插模型。实验结果表明:在内插模型合适的情况下,电离层延迟精度可达到精密单点定位的要求。      

Exploring the spatiotemporal relationships between search flows and travel flows

Numerous studies attempted to associate search engine data with travel behaviors. However, most existing studies focus on the destinations of search and travel, while ignoring the origins, which embed critical information of where the search requests were initiated and where the travelers came from. In this study, we explore the relationships between two types of intercity origin–destination flow data, namely travel flows and search flows, which, respectively, record the number of travelers and search requests from one city towards another. By comparing the two flows during holiday and non-holiday, we examine their complex spatiotemporal relationships from multiple perspectives, including time-lag effect, distance decay effect, spatial autocorrelation, network community, cities' rankings, and important factors of search and travel activities. The findings can deepen our understanding of search and travel behaviors, hence they can help decision makers to develop targeted strategies to enhance city's attractiveness, improve transportation infrastructure, and promote tourism.     

冠层光能利用率的叶绿素荧光光谱探测

设计了玉米生长期日变化试验,同步获取玉米冠层光谱和通量观测数据,探究从植被发射荧光光谱角度实现植被光能利用率可靠反演的可能性。运用涡度相关法获取群体生态系统净生产力(NEP),通过呼吸作用拟合得到冠层总初级生产力(GPP);在此基础上结合吸收光合有效辐射(APAR)获取冠层光能利用率(LUE);同时,利用叶绿素荧光光谱分离算法,提取了光合作用叶绿素荧光绝对强度和相对强度。结论表明,植被发射荧光光谱与光合有效辐射(PAR)显著正相关,760nm波段荧光与PAR的复相关系数R2在0.99以上;叶绿素荧光绝对强度与NEP和GPP显著正相关,荧光和NEP对环境日变化具有类似的响应特征;688nm和760nm植被发射的叶绿素荧光相对强度与LUEGPP存在可靠负相关关系,即叶绿素荧光强度越大,光能利用率越低。同时,通过比较几种植被指数与各种光合参量的相关性表明,叶绿素荧光能够更好的跟踪植被光合状态的变化,更适宜于植被光能利用率的探测。     

利用高光谱数据对作物群体叶绿素密度估算的研究

叶绿素是农作物生长中重要的因素。叶绿素含量既表明作物生长的状况,又表征了作生的生产能力。而叶绿素密度（单位面积农作物的叶绿绿素含量）是估计农作物群体生产力的重要指标。对早播稻、晚播稻和玉米的多时相的群体光谱测量数据和相应的叶片叶绿素密度的测量数进行了相关分析,结果表明早播、晚播稻和玉米的群体光谱的反射率数据以及其导数光谱数据绿素密度具有委好多的相关性,并且可以对这几种农作物建立统一的线性回归关系。     

Estimating single-tree branch biomass of Norway spruce by airborne laser scanning

The use of forest biomass for bioenergy purposes, directly or through refinement processes, has increased in the last decade. One example of such use is the utilization of logging residues. Branch biomass constitutes typically a considerable part of the logging residues, and should be quantified and included in future forest inventories. Airborne laser scanning (ALS) is widely used when collecting data for forest inventories, and even methods to derive information at the single-tree level has been described. Procedures for estimation of single-tree branch biomass of Norway spruce using features derived from ALS data are proposed in the present study. As field reference data the dry weight branch biomass of 50 trees were obtained through destructive sampling. Variables were further derived from the ALS echoes from each tree, including crown volume calculated from an interpolated crown surface constructed with a radial basis function. Spatial information derived from the pulse vectors were also incorporated when calculating the crown volume. Regression models with branch biomass as response variable were fit to the data, and the prediction accuracy assessed through a cross-validation procedure. Random forest regression models were compared to stepwise and simple linear least squares models. In the present study branch biomass was estimated with a higher accuracy by the best ALS-based models than by existing allometric biomass equations based on field measurements. An improved prediction accuracy was observed when incorporating information from the laser pulse vectors into the calculation of the crown volume variable, and a linear model with the crown volume as a single predictor gave the best overall results with a root mean square error of 35% in the validation.     

Fuzzy ARTMAP算法在城市不透水面估算中的应用研究

为了克服线性光谱混合分析模型的缺陷,兼顾Landsat ETM+和Quickbird遥感数据多源信息及Fuzzy ARTMAP神经网络自适应学习的优势,提出了利用Fuzzy ARTMAP方法来估算城市不透水面覆盖度(ISP)。以武汉市为例,结果表明,与线性光谱混合分析模型相比,基于Fuzzy ARTMAP神经网络方法估算结果精度较高,与实际城市不透水面覆盖度分布范围一致。     

利用时空立方体挖掘小微地震时空演变模式

挖掘分析小微地震的时空演变模式,可为地震灾害的分析与预报提供辅助决策参考。本文以四川地区的地震监测数据为基础,利用时空立方体融合地震点的空间、时间与属性数据,基于时空热点统计分析方法挖掘小微地震的时空冷热点分布模式。试验结果表明:在试验数据的时域内,四川地区小微地震的热点模式主要表现为连续热点、逐渐减少热点和振荡热点。冷点模式主要是连续冷点,且冷点覆盖范围比热点覆盖范围广。基于时空立方体的时空热点分析方法能够发挥时空统计学的优势,可有效挖掘分析小微地震的时空演变趋势。     

空间尺度与语义尺度联合控制下的地理国情地图综合

地理国情数据具有精度高、数据量大、语义信息丰富的基本特征,是地图产品表达与服务应用的基础数据.为应对多层次服务、多领域应用、多粒度表达与分析的需求,在基础调查数据基础上,通过尺度变换获得多比例尺表达的数据版本很有必要.地理国情地图综合属于专题地图综合范畴,与以实现空间特征简化为目的的普通地图综合相比,其地图综合要更多地关注语义特征的概括,并强调综合结果语义特征的一致.因此,空间特征约束与语义特征约束联合控制将成为地理国情地图综合的主要特点.论文以现有地图综合理论及方法为基础,根据地理国情数据特点及综合需求,对专题地图综合理论和方法进行拓展,针对地理国情数据尺度变换的综合规则构建、综合操作算法设计、综合结果质量评价等问题进行研究,为工程化应用中快速、高效、准确地实施数据多尺度变换提供技术支撑.     

GIS中缓冲区分析后的误差估计

缓冲区操作是GIS空间分析中的一个重要部分。由于GIS中的点、线、面存在定位误差，导致了以此为依据的缓冲区域也存在相应的定位不确定性。根据误差的基本特性，应用误差传播定律，导出了因点、线、面的定位不确定性所引起的缓冲区域的不确定面积估计，并给出实例进行了分析。     

《国家普通地图集》色标的研究

本文根据《国家普通地图集》总设计书的要求,重点探讨了该图集总体色标的设计原则、制印工艺方案及质量检测方法。实验结果证明:新设计的色标及制印工艺,具有科学性强、通用性好及新颖不俗的特点,受到地图专家们的一致好评。     

Induced earthquakes and house prices: the role of spatiotemporal and global effects

Journal of Geographical Systems - This paper contributes to the existing literature on the explanation of housing prices. First, our proposed methodology accounts for cross-sectional dependence,...     

Revealing the spatiotemporal characteristics of the general public's panic levels during the pandemic crisis in China

The existing crisis management research mostly reveals the patterns of the public's panic levels from the perspectives of public management, sociology, and psychology, only a few studies have revealed the spatiotemporal characteristics. Therefore, this study investigates the spatial distribution and temporal patterns and influencing factors on the general public's panic levels using the Baidu Index data from a geographic perspective. The results show that: (1) The public's panic levels were significantly correlated with the spatial distance between the epicenter and the region of investigation, and with the number of confirmed cases in different regions when the pandemic began to spread. (2) Based on the spatial distance between the epicenter and the region, the public's panic levels in different regions could be divided into three segments: core segment (0–500 km), buffer segment (500–1300 km), and peripheral segment (>1300 km). The panic levels of different people in the three segments were consistent with the Psychological Typhoon Eye Effect and the Ripple Effect can be detected in the buffer segment. (3) The public's panic levels were strongly correlated with whether the spread of the infectious disease crisis occurred and how long it lasted. It is suggested that crisis information management in the future needs to pay more attention to the spatial division of control measures. The type of crisis information released to the general public should depend on the spatial relationship associated with the place where the crisis breaks out.     

Inferring the home locations of Twitter users based on the spatiotemporal clustering of Twitter data

Residential locations play an important role in understanding the form and function of urban systems. However, it is impossible to release this detailed information publicly, due to the issue of privacy. The rapid development of location‐based services and the prevalence of global position system (GPS)‐equipped devices provide an unprecedented opportunity to infer residential locations from user‐generated geographic information. This article compares different approaches for predicting Twitter users' home locations at a precise point level based on temporal and spatial features extracted from geo‐tagged tweets. Among the three deterministic approaches, the one that estimates the home location for each user by finding the weighted most frequently visited (WMFV) cluster of that user always provides the best performance when compared with the other two methods. The results of a fourth approach, based on the support vector machine (SVM), are severely affected by the threshold value for a cluster to be identified as the home.     

Data matching of building polygons at multiple map scales improved by contextual information and relaxation

The aim of matching spatial data at different map scales is to find corresponding objects at different levels of detail (LODs) that represent the same real-world phenomena. This is a prerequisite for integrating, evaluating and updating spatial data collected and maintained at various scales. However, matching spatial data is not straightforward due to the ambiguities caused by problems like many-to-many correspondence, non-systematic displacement and different LODs between data sets. This paper proposes an approach to matching areal objects (e.g. buildings) based on relaxation labeling techniques widely applied in pattern recognition and computer vision. The underlying idea is to utilize contextual information (quantified by compatibility coefficient) in an iterative process, where the ambiguities are reduced until a consistent matching is achieved. This paper describes (1) a domain-specific extension to previous relaxation schemes and (2) a new compatibility coefficient that exploits relative relationships between areal object pairs in spatial data. Our approach were validated through extensive experiments using building data sets at 1:10k and 1:50k as an example. Our contextual approach showed superior performance against a non-contextual approach in general and especially in ambiguous situations. The proposed approach can also be applied to matching other areal features and/or for a different scale range.