Exploring the spatiotemporal behavior of Helsinki’s housing prices with fractal geometry and co-integration

Fractal geometry and co-integration are combined for exploring spatial morphological aspects of quarterly dwelling prices in Helsinki’s region from 1977 to 2011. Curves of fractal scaling behavior are first employed to measure the fractal dimensions of high- and low-price/m² spatial clusters at multiple scales. Subsequently, the fractal dimensions at indicative neighborhood and citywide scales are modeled with vector error correction specifications. The results identify long-run joint equilibria between the fractal geometries of high- and low-price/m² clusters at both spatial scales. High-price/m² clusters exhibit consistently higher fractal dimensions than their low-value counterparts at the neighborhood scale, while this long-run relation is reversed at the citywide scale. Short-run disequilibria and subsequent adjustments are also scale sensitive. The fractal geometry of high-price/m² clusters leads the dynamics at the neighborhood scale, while low-price/m² clusters lead at the citywide scale. The system’s responses to exogenous shocks take longer time to stabilize at the neighborhood scale compared to the citywide scale, but in both scales the non-stationary nature of fractal behavior is evident. These elements indicate that a closer look on spatial economic behavior at more than one spatial and temporal scale at a time can reveal non-trivial information in the context of urban research and policy analysis.     

城市交通网络分形维数的不确定性估计、控制与分析

长度-半径维数模型作为描述城市交通网络复杂不确定性现象的一种分形分维方法,其自身存在的不确定性往往被忽视,且相关研究更是鲜见报道。故针对该模型在分形维数测算全过程中存在的不确定性问题,本文率先开展了系统剖析、定量估计和质量控制研究。首先对数据源、矢量化处理、测算中心、尺度选择、以及分维数模型估计等一系列环节进行了不确定性估计与分析,其中首次给出了分形维数在一定置信水平下的不确定性度量区间,并依据误差传播理论对误差的传递和累积进行了描述;然后着重提出了基于LMed S(Least Median of Squares)的质量控制方法。最后通过对拉萨市的算例实验表明:道路的矢量化过程、测算中心和测算尺度的选择都会导致分维的不确定性;并在对数据质量进行控制的基础上,通过置信区间对长度-半径维数模型的不确定性进行了在一定概率水平下的首次度量;同时结合区域现状对研究结果给出了合乎实际的解释。本文在描述表征不确定性问题的分形几何和分形维数的基础上,系统地揭示了其自身不确定性的本质,不仅进一步丰富了分形分维理论,为控制其质量奠定理论基础,而且可为城市交通网络分形维数的地学应用提供可靠的科学依据。     

度量映射方法在河流分维测算中的应用

应用TM卫星图像数据，根据对黑龙江省阿什河约80km河段、松花江及嫩江约2300km河段的分维研究。证明了在度量数列满足持邻性和等比收敛性的条件下。可以应用度量映射方法计算随机分形集的分维。研究表明，黑龙江省阿什河河段（约80km）的分维比松花江和嫩江河段（约2300km）的分维高；曲线的分维一定要与标度的变化区间联系起来，否则分维将失去可比性；河流的分维不仅与标度有关，还与矢量化时原图像的分辨率有关。     

影像纹理的多标度分形分析

引入目前在分形几何中发展起来的多标度分形理论，发展了影像纹理的多标度分形分析，能够描述纹理结构更多的分形特征，反映影像纹理的局部分维差别，抑制目前仅基于整体分维计算存在的不同分形同分维之弊端，实现影像纹理的多分辨率分析。尽管分维测度是纹理的一个非常重要的特征，但单纯的仅基于分维测度的分析，并不足以表征所有的纹理信息。     

Modelling of differential single difference receiver clock bias for precise positioning

A receiver hardware delay should be seriously considered for time-transfer and determination of ionospheric delay corrections for wide area differential GPS positioning. A receiver hardware delay does not generally effect the common geo-position application, as suitable differences of observations are used, or equivalently, clock error parameters are introduced, epoch-wise, that also absorb the delays. This paper investigates the behavior of inter-frequency (or observation-type) receiver hardware delays by using a single difference (SD) model, which estimates the receiver delay along with the receiver clock error (and SD ambiguities of a reference satellite with carrier phase observations) for zero and short baselines. The purpose of this paper is to model the between-observation-type delays for the purpose of precise positioning, under practical circumstances. The focus is on data series of differential SD receiver clock biases, since they reflect the behavior of receiver hardware delays with time. A simple linear regression of the data series is employed to study the behavior, and test statistics are employed to assess both the significance of the parameters and the observations fit for the linear regression. The statistical analysis results indicate that almost all inter-observation type receiver delays can be modeled as the sum of a constant (offset) and a constant rate of change (slope). The analysis shows that the differential receiver delay is generally at the mm- to cm-level on phase, while at the dm-level on code for the equipment used in the experiments.     

Multiscale Terrain and Topographic Modelling with the Implicit TIN

It is often assumed that real land surfaces demonstrate the statistically self-affine scaling behaviour of fractional Brownian surfaces. Tests of this assumption against empirical data, however, show many deviations. Estimates of fractal properties vary between methods and over different scale ranges. So far, this empirical evidence has come from the analysis of variograms for DEMs representing areas up to tens of kilometres in diameter. Here we report results obtained by using variograms to analyse land surface DEMs at the continental scale, with a grid resolution of 30 arc seconds. Results reveal variogram curvature and breaks of slope, but also linear sections over distance lags of hundreds of kilometres. The estimated mean fractal dimension calculated from these sections is 2.66, substantially higher for all continents at these broad scales (around 200 km) than values calculated at the erosional landscape scale (around 200 m). Thus the land surface is not self-affine, and it is not clear that it follows any simple multifractal model. At the longest wavelengths, patterns found in the variograms appear to be related to broad tectonic features of the Earth's surface. For the reader to assess their quality and generality, estimates of fractal dimension should always be accompanied by statements of the scale range covered and the goodness of fit to a log-linear relationship.     

THE MULTIFRACTAL CHARACTER OF LINEAMENT DENSITY ON THE KOLA PENINSULA

Analysis of data on the lineament network of the Kola Peninsula obtained through interpretation of space images at different scales provides an indication of the multifractality of lineament densities and the possibility of the geologic interpretation of the spectrum of fractal dimensions. The invariance of the distribution of densities of images of the lineament network at small and large scales reveals the scaling properties of these structural elements, and objectively reflects the heterogeneity of the geologic medium.     

基于分形插值的桥梁桥墩沉降预测

基于某跨海大桥桥墩的沉降资料,使用重标极差(R/S)分析方法说明桥墩沉降的非线性下隐藏的持续性特征,并计算其分形维数,证明该沉降时间序列具有分形特性。由此通过历史数据建立迭代函数系统,经分形插值方法求取吸引子,并在吸引子基础上进行延拓,建立基于分形插值的预测模型,并将此算法应用于桥墩沉降数据的预测中。算例结果表明,分形插值理论具有较高的预测精度,可满足实际应用要求。     

Evaluation of the impact of atmospheric pressure loading modeling on GNSS data analysis

In recent years, several studies have demonstrated the sensitivity of Global Navigation Satellite System (GNSS) station time series to displacements caused by atmospheric pressure loading (APL). Different methods to take the APL effect into account are used in these studies: applying the corrections from a geophysical model on weekly mean estimates of station coordinates, using observation-level corrections during data analysis, or solving for regression factors between the station displacement and the local pressure. The Center for Orbit Determination in Europe (CODE) is one of the global analysis centers of the International GNSS Service (IGS). The current quality of the IGS products urgently asks to consider this effect in the regular processing scheme. However, the resulting requirements for an APL model are demanding with respect to quality, latency, and—regarding the reprocessing activities—availability over a long time interval (at least from 1994 onward). The APL model of Petrov and Boy (J Geophys Res 109:B03405, 2004) is widely used within the VLBI community and is evaluated in this study with respect to these criteria. The reprocessing effort of CODE provides the basis for validating the APL model. The data set is used to solve for scaling factors for each station to evaluate the geophysical atmospheric non-tidal loading model. A consistent long-term validation of the model over 15 years, from 1994 to 2008, is thus possible. The time series of 15 years allows to study seasonal variations of the scaling factors using the dense GNSS tracking network of the IGS. By interpreting the scaling factors for the stations of the IGS network, the model by (2004) is shown to meet the expectations concerning the order of magnitude of the effect at individual stations within the uncertainty given by the GNSS data processing and within the limitations due to the model itself. The repeatability of station coordinates improves by 20% when applying the effect directly on the data analysis and by 10% when applying a post-processing correction to the resulting weekly coordinates compared with a solution without taking APL into account.     

改进分形海面模型散射信号的分形特性分析

针对分形海面模型的功率谱在空间波数小于基波波数时不能满足正幂率的问题,提出一种统计模型和归一化带限Weierstrass分形模型相结合的1维海面模型,确定了表面功率谱的闭式解,表面功率谱和有关文献的数据进行了对比。在满足Kirchhoff近似的条件下推导该模型电磁散射系数的闭式解,计算了散射系数随时间变化的Hurst指数,进而求得其分形维数。从数值仿真结果可知,表面功率谱和PM谱、南海的实测数据都拟合得很好,验证了模型的有效性,海面所接收信号随时间变化是分形的,并且其分形维数与分形海表面的分形维数几乎相等。     

扩展分维模型在地图曲线自动综合中的应用

为了改进目前采用的单一分维值方法无法充分描述地图曲线的空间形态特征,导致综合结果产生偏差,探讨了在扩展分维模型条件下经过改进的地图曲线自动综合算法.     

Ecosystem functional assessment based on the “optical type” concept and self-similarity patterns: An application using MODIS-NDVI time series autocorrelation

Remote sensing (RS) time series are an excellent operative source for information about the land surface across several scales and different levels of landscape heterogeneity. Ustin and Gamon (2010) proposed the new concept of “optical types” (OT), meaning “optically distinguishable functional types”, as a way to better understand remote sensing signals related to the actual functional behavior of species that share common physiognomic forms but differ in functionality. Whereas the OT approach seems to be promising and consistent with ecological theory as a way to monitor vegetation derived from RS, it received little implementation.This work presents a method for implementing the OT concept for efficient monitoring of ecosystems based on RS time series. We propose relying on an ecosystem's repetitive pattern in the temporal domain (self-similarity) to assess its dynamics. Based on this approach, our main hypothesis is that distinct dynamics are intrinsic to a specific OT. Self-similarity level in the temporal domain within a broadleaf forest class was quantitatively assessed using the auto-correlation function (ACF), from statistical time series analysis. A vector comparison classification method, spectral angle mapper, and principal component analysis were used to identify general patterns related to forest dynamics. Phenological metrics derived from MODIS NDVI time series using the TIMESAT software, together with information from the National Forest Map were used to explain the different dynamics found.Results showed significant and highly stable self-similarity patterns in OTs that corresponded to forests under non-moisture-limited environments with an adaptation strategy based on a strong phenological synchrony with climate seasonality. These forests are characterized by dense closed canopy deciduous forests associated with high productivity and low biodiversity in terms of dominant species. Forests in transitional areas were associated with patterns of less temporal stability probably due to mixtures of different adaptation strategies (i.e., deciduous, marcescent and evergreen species) and higher functional diversity related to climate variability at long and short terms. A less distinct seasonality and even a double season appear in the OT of the broadleaf Mediterranean forest characterized by an open canopy dominated by evergreen-sclerophyllous formations. Within this forest, understory and overstory dynamics maximize functional diversity resulting in contrasting traits adapted to summer drought, winter frosts, and high precipitation variability.     

应用时间序列方法作大坝变形预报

本文首先介绍时序分析的三个基本模型——ARMA模型、AR模型和MA模型,以及各模型的统计性质。然后以某大坝1715廊道的激光视准线观测位移值(已利用倒垂观测把相对位移化为绝对位移)为例,着重叙述大坝变形分析的建模过程,得到了一个AR(2)模型并对大坝变形作了预报,结果具有相当好的预报精度。从而说明,时序分析法将是大坝变形分析的一个有力工具。     

遥感尺度内涵及遥感像元尺度效应分析的改进分形方法

本文首先分析了遥感影像尺度的三层次内涵。重点针对遥感像元尺度,分析了遥感像元尺度效应及其分形机理,由于现有分形方法没有考虑影像本身尺度(空间分辨率),造成尺度间分形维数的比较时像元尺度效应变化难以有效反映,本文针对此问题提出了基于表面积的加窗分形布朗运动和加窗双层地毯两种改进分形方法。为验证改进分形方法的可靠性,采用了不同像元尺度下系列监督分类进行验证。试验结果表明,每种地物的分维数都随着空间分辨率的降低或像元尺度的缩小,呈总体下降趋势,在某些特征尺度上会出现预示着某些地物结构的拐点,这些拐点对观测该区域地物具有一定指示意义。系列监督分类精度也一定程度上证明了以上两种改进分形方法在分析尺度效应中的可行性。因此本文的方法对于分析遥感像元尺度效应和探索地物尺度聚合规律具有一定的理论意义。     

A time‐geographic approach to quantifying wildlife–road interactions

Recent advances in time geography offer new perspectives for studying animal movements and interactions in an environmental context. In particular, the ability to estimate an animal's spatial location probabilistically at temporal sampling intervals between known fix locations allows researchers to quantify how individuals interact with one another and their environment on finer temporal and spatial scales than previously explored. This article extends methods from time geography, specifically probabilistic space–time prisms, to quantify and summarize animal–road interactions toward understanding related diurnal movement behaviors, including road avoidance. The approach is demonstrated using tracking data for fishers (Martes pennanti) in New York State, where the total probability of interaction with roadways is calculated for individuals over the duration tracked. Additionally, a summarization method visualizing daily interaction probabilities at 60 s intervals is developed to assist in the examination of temporal patterns associated with fishers’ movement behavior with respect to roadways. The results identify spatial and temporal patterns of fisher–roadway interaction by time of day. Overall, the methodologies discussed offer an intuitive means to assess moving object location probabilities in the context of environmental factors. Implications for movement ecology and related conservation planning efforts are also discussed.     

基于高斯模型的样本缺失GPS时间序列重构方法

缺失样本的存在会造成GPS时间序列速度估计的不确定性,从而影响GPS时间序列的应用。针对该问题本文提出一种基于高斯模型的样本缺失GPS时间序列重构方法,首先利用高斯概率密度函数对GPS时间序列的先验分布进行建模,在此基础上构建全概率贝叶斯统计模型,采用期望最大(Expectation Maximization,EM)算法对模型参数(隐变量)进行迭代更新并计算其最大似然估计值,最终完成信号重构。分别对随机缺失和分段连续缺失两种情况进行实验分析,结果表明所提方法相对于传统插值方法可以获得更好的重构性能。     

支持向量机在建筑物变形监测中的应用探讨

论述了支持向量机的回归算法和基于时间序列支持向量回归的建筑物变形预测方法,并用MATLAB6.5工具箱编制基于时间序列支持向量回归程序,建立了基于时间序列支持向量回归模型。最后以实例数据讨证基于时间序列支持向量机回归模型的预测方法。研究表明:用时间序列支持向量回归模型建立的建筑物变形监测的预测模型是可行的和有效的。     

GPS position time-series analysis based on asymptotic normality of M-estimation

The efficacy of robust M-estimators is a well-known issue when dealing with observational blunders. When the number of observations is considerably large—long time series for instance—one can take advantage of the asymptotic normality of the M-estimation and compute reasonable estimates for the unknown parameters of interest. A few leading M-estimators have been employed to identify the most likely functional model for GPS coordinate time series. This includes the simultaneous detection of periodic patterns and offsets in the GPS time series. Estimates of white noise, flicker noise, and random walk noise components are also achieved using the robust M-estimators of (co)variance components, developed in the framework of the least-squares variance component estimation (LS-VCE) theory. The method allows one to compute confidence interval for the (co)variance components in asymptotic sense. Simulated time series using white noise plus flicker noise show that the estimates of random walk noise fluctuate more than those of flicker noise for different M-estimators. This is because random walk noise is not an appropriate noise structure for the series. The same phenomenon is observed using the results of real GPS time series, which implies that the combination of white plus flicker noise is well described for GPS time series. Some of the estimated noise components of LS-VCE differ significantly from those of other M- estimators. This reveals that there are a large number of outliers in the series. This conclusion is also affirmed by performing the statistical tests, which detect (large) parts of the outliers but can also leave parts to be undetected.     

地图信息衰减中关键比例尺的研究

提出了一种基于分维扩展理论的关键比例尺确定方法，认为地图目标的自相似性是随着比例足的变化呈衰减趋势变化，可以反映在图面信息量的变化上，并借助分维扩展中的反“S”曲线模型来确定两个已知比例尺之间的关键比例尺。