MaskMy.XYZ: An easy‐to‐use tool for protecting geoprivacy using geographic masks

Geographic masks are techniques used to protect privacy when publishing sensitive data in maps, but are not well adopted among researchers and may be difficult to execute for some GIS users. We developed a client‐side web application called MaskMy.XYZ that makes geographic masking easy to perform. It executes donut geomasking, a well‐known geographic mask, on thousands of points in seconds, and visualizes the original and masked point patterns in an integrated web map for visual comparison. MaskMy.XYZ also features metrics for both privacy protection and information loss, and allows users to rapidly and iteratively adjust masking parameters based on these metrics. The user interface was designed to prioritize usability, and clear documentation has been included to educate users about geographic masks, which is otherwise only found in niche literatures. By developing this application, we hope that geographic masks will be more widely adopted such that privacy is better protected in research.     

Implementation of novel polygon-based obfuscation methods to improve privacy of agricultural data

Geoprivacy protection is a significant concern when sharing data. To support sustainable land management by leveraging existing agricultural data, research is needed to identify how the polygon nature of static field parcels can be obfuscated to allow data sharing among individuals and organizations. In this study, five adaptive polygon-based obfuscation methods including PN*Rand, PDonut-k, PDensity-k, PAHilb, and PDonut_AHilb methods were developed and applied on the Irish Nutrient Management Planning Online (NMP Online) agricultural dataset. The polygon-based obfuscation methods introduced in this study were designed with the consideration of properties of spatial polygon objects including the spatial coordinates, shape and size of the polygon, topology, and spatial relationship between adjacent polygons that can be used to identify real-world objects. These methods were developed to guarantee that there is no false-identification and non-unique obfuscation which is important for static polygon objects in terms of accuracy and privacy protection. Qualitative approaches were developed to identify the optimal values of inner and outer radii of donut shape based on k-anonymity satisfaction and subsequently obtain the optimal value of k-anonymity. Several evaluation methods were implemented to compare the methods performance. Density-based methods particularly PDonut-AHilb provide the best trade-off between field parcel confidentiality and spatial pattern preservation and should be considered for researchers and practitioners obfuscating polygon data.     

Spatial Information Divergence: Using Global and Local Indices to Compare Geographical Masks Applied to Crime Data

Advances in Geographic Information Science (GISc) and the increasing availability of location data have facilitated the dissemination of crime data and the abundance of crime mapping websites. However, data holders acknowledge that when releasing sensitive crime data there is a risk of compromising the victims' privacy. Hence, protection methodologies are primarily applied to the data to ensure that individual privacy is not violated. This article addresses one group of location protection methodologies, namely geographical masks that are applicable for crime data representations. The purpose is to identify which mask is the most appropriate for crime incident visualizations. A global divergence index (GDi) and a local divergence index (LDi) are developed to compare the effects that these masks have on the original crime point pattern. The indices calculate how dissimilar the spatial information of the masked data is from the spatial information of the original data in regards to the information obtained via spatial crime analysis. The results of the analysis show that the variable radius mask and the donut geomask should be primarily used for crime representations as they produce less spatial information divergence of the original crime point pattern than the alternative local random rotation mask and circular mask.     

GIS中平面面位误差环的解析模型

本文基于随机场理论,导出了随机面元的分布函数和概率密度函数。为了衡量随机面元的位置不确定性,将点位误差椭圆和线位误差带进一步扩展到面位误差环指标。根据推求包括线的原理,导出了多边形面位误差环边界线的解析表达式,并分析了面位误差环的构成机理,证明了误差环边界线为连续闭合曲线的结论。最后通过实例绘制了面位误差环的可视化图形。     

Positioning Disaster Relief Teams Given Dynamic Service Demand: A Hybrid Agent‐Based and Spatial Optimization Approach

During extreme events, like hurricanes, it is essential to position relief services for non‐evacuees throughout the affected region in optimal locations. While previous research has explored a variety of spatial optimization models to accomplish such a task, most work assumes that the population with demand is relatively static. However, this assumption neglects to account for potential feedbacks in the relief distribution system. For example, a population's behavior can both affect and be affected by the placement of relief services, resulting in a dynamic spatial distribution of demand. This article presents a hybrid modeling approach that utilizes GIS data with agent‐based and spatial optimization models to position emergency relief teams in Bay County, Florida during a hurricane event. Non‐evacuating household agents choose to remain at home or seek shelter, while relief team agents are periodically repositioned to account for changes in the spatial distribution of household agents. A total of 220 simulations are run to explore a variety of scenarios. Results show different repositioning timing strategies and the magnitude of the feedback effect drastically changes the level of access households have to relief teams. Ultimately, this work demonstrates the importance of accounting for behavioral and spatial dynamics in disaster relief distribution systems.     

Spatial microsimulation modeling for residential energy demand of England in an uncertain future

High quality infrastructure is crucial to economic success and the sustainability of society. Infrastructures for services, such as transport, energy, and water supply, also have long lead times, and therefore require effective long-term planning. In this paper, we report on work undertaken as part of the UK Infrastructure Transitions Research Consortium to construct long-term models of demographic change which can help to inform infrastructure planning for transport, energy, and water as well as IT and waste. A set of demographic microsimulation models (MSM), which are spatially disaggregate to the geography of UK Local Authorities, provides a high level of detail for understanding the drivers of changing patterns of demand. However, although robust forecasting models are required to support projections based on the notion of ‘predict-and-provide,’ the potential for behavioral adaptation is also an important consideration in this context. In this paper, we therefore establish a framework for linkage of a MSM of household composition, with behavior relating to the consumption of energy. We will investigate variations in household energy consumption within and between different household groups. An appropriate range of household types will be defined through the application of decision trees to consumption data from a detailed survey produced by the UK Department of Energy and Climate Change. From this, analysis conclusions will be drawn about the impact of changing demographics at both household and individual level, and about the potential effect of behavioral adjustments for different household groups.     

基于楼盘表和户型图的分层分户模型建设

随着智慧城市建设的不断升级,城市管理向精细化和智能化方向快速发展.分层分户模型可以承载更复杂、更立体、更详细、更精确的信息,以供全面综合管理、大数据分析和应急指挥使用.本文以"数字郑州三维地理信息及应用服务系统"项目建设实际情况为背景,探索和实现了在SuperMap GIS平台环境下,基于楼盘表提供的层户信息与户型图提供的分户信息,通过数字线划图进行建筑底面定位,利用地名地址将楼盘表和户型图与数字线划图进行关联挂接,并根据LiDAR点云数据的高度信息,快速自动化地建设郑州市800 km2内所有建筑物的分层分户模型的技术方法.进一步探索了通过模型成果与房管信息和公安户籍信息挂接,建立"以图管房、以房管人"的新管理模式,有效提升了政府管理和决策水平.本文提出的方法技术路线先进,实操性强,具有重要的应用推广价值.     

How do people perceive the disclosure risk of maps? Examining the perceived disclosure risk of maps and its implications for geoprivacy protection

ABSTRACT

This research examines how people subjectively perceive the disclosure risk of a map using original data collected in an online survey with 856 participants. The results indicate that perceived disclosure risk increases as the amount of locational information displayed on a map increases. Compared to point-based maps, perceived disclosure risk is significantly lower for kernel density maps, convex hull maps, and standard deviational ellipse maps. The results also revealed that perceived disclosure risk is affected by map scale and the presence of information of other people on a map. For geomasking methods, perceived disclosure risk decreases as aggregation level increases and as relocation distance increases. However, aggregation methods (point to polygon) are more effective in preventing the re-identification of individuals when compared to relocation methods (point to point). Lastly, the perceived disclosure risk of a map that displays socially-vulnerable people is significantly higher than that of a map that displays non-vulnerable groups. Specifically, a map displaying the private locations of elementary school students has the highest perceived disclosure risk. Based on the results, a set of geoprivacy protection guidelines for mapping people’s private locations to minimize people’s perceived disclosure risk is proposed. Implications for mapping infectious diseases like the COVID-19 are also discussed.     

Bootstrap方法在遥感线性BRDF模型反演中的应用

在遥感反演中,通常假设反演参数和模型误差的先验分布服从正态分布,这个假设通常不太符合实际。为此,本文提出由Bootstrap方法估计反演参数和模型误差的先验分布的方案。同时对先验数据按照地物分类,统计假设检验表明将先验知识分类的合理性。最后,以RossThick-LiTransit核组合的线性核驱动BRDF模型为例,用NOAA-AVHRR观测数据对使用Bootstrap方法的反演算法进行试验,并与正态假设下的Tikhonov正则化反演和Bayes反演结果比较,说明对先验知识分类和使用Bootstrap方法的遥感反演方法能明显减小参数反演结果的不确定性,提高其可信度。     

Exploring the Impact of Non-normality on Spatial Non-stationarity in Geographically Weighted Regression Analyses: Tobacco Outlet Density in New Jersey

The principal rationale for applying geographically weighted regression (GWR) techniques is to investigate the potential spatial non-stationarity of the relationship between the dependent and independent variables—i.e., that the same stimulus would provoke different responses in different locations. The calibration of GWR employs a geographically weighted local least squares regression approach. To obtain meaningful inference, it assumes that the regression residual follows a normal or asymptotically normal distribution. In many classical econometric analyses, the assumption of normality is often readily relaxed, although it has been observed that such relaxation might lead to unreliable inference of the estimated coefficients' statistical significance. No studies, however, have examined the behavior of residual non-normality and its consequences for the modeled relationships in GWR. This study attempts to address this issue for the first time by examining a set of tobacco-outlet-density and demographic variables (i.e., percent African American residents, percent Hispanic residents, and median household income) at the census tract level in New Jersey in a GWR analysis. The regression residual using the raw data is apparently non-normal. When GWR is estimated using the raw data, we find that there is no significant spatial variation of the coefficients between tobacco outlet density and percentage of African American and Hispanics. After transforming the dependent variable and making the residual asymptotically normal, all coefficients exhibit significant variation across space. This finding suggests that relaxation of the normality assumption could potentially conceal the spatial non-stationarity of the modeled relationships in GWR. The empirical evidence of the current study implies that researchers should verify the normality assumption prior to applying GWR techniques in analyses of spatial non-stationarity.     

An empirical test of household identification risk in geomasked maps

ABSTRACT

Geomasking techniques displace point data to new locations in order to protect privacy while maintaining overall spatial distributions. If the end users of geomasked data are unaware that the data are masked, there is a risk that they will incorrectly associate individuals at the new locations with the masked data attributes. The probability of correct and false household identification depends on human understanding of whether maps contain masked coordinates and the spatial relationships of the points to contextual geographic data. Using a map-based experiment, this study finds that confidence in performing a household identification is substantially lowered when masked points are situated equidistantly between residential parcels. Despite initial notifications that data are masked, map users often report confidence in assigning masked points to specific households. Only map users who receive frequent notifications that the points are masked have reduced confidence in associating them with particular households, thereby lowering identification risk.     

High-rate precise point positioning (PPP) to measure seismic wave motions: an experimental comparison of GPS PPP with inertial measurement units

High-rate GPS has been widely used to construct displacement waveforms and to invert for source parameters of earthquakes. Almost all works on internal and external evaluation of high-rate GPS accuracy are based on GPS relative positioning. We build an experimental platform to externally evaluate the accuracy of 50-Hz PPP displacement waveforms. Since the shake table allows motion in any of six degrees of freedom, we install an inertial measurement unit (IMU) to measure the attitude of the platform and transform the IMU displacements into the GPS coordinate system. The experimental results have shown that high-rate PPP can produce absolute horizontal displacement waveforms at the accuracy of 2–4 mm and absolute vertical displacement waveforms at the sub-centimeter level of accuracy within a short period of time. The significance of the experiments indicates that high-rate PPP is capable of detecting absolute seismic displacement waveforms at the same high accuracy as GPS relative positioning techniques, but requires no fixed datum station. We have also found a small scaling error of IMU and a small time offset of misalignment between high-rate PPP and IMU displacement waveforms by comparing the amplitudes of and cross-correlating both the displacement waveforms.     

地理信息隐私保护法律问题探析

地理信息市场化过程中存在隐私法律问题。本文以美国隐私保护法律体系为视角,分析美国与欧盟关于隐私法律保护法律模式的差异,研究安全港框架及相关原则对数据跨境流转的作用。通过比较法研究,旨在对我国地理信息市场化法律制度的构建有所启发。     

美国地理信息系统隐私法律述评

地理信息系统存在隐私问题。本文梳理美国的隐私保护法律体系,分析美国与欧盟关于隐私法律保护法律模式的差异,研究安全港框架及相关原则对数据跨境流转的作用,期望对我国地理信息系统的法律制度构建有比较法意义。     

Extreme value theory-based integrity monitoring of global navigation satellite systems

Measurements consistency-based Receiver Autonomous Integrity Monitoring (RAIM) is the main technique for monitoring the integrity of global satellite navigation systems at the user-level. Existing RAIM algorithms utilize two tests, in the position domain a test for RAIM availability and in the measurement domain a test for failure detection. These tests involve the computation of three parameters: test statistic, decision threshold, and protection level. The test statistic is based on the actual measurements in the form of the sum of the squared errors (SSE). The decision threshold is chosen on the basis of the statistical characteristics of the SSE including the assumption that the errors are normally distributed. However, in practice residual, error distributions exhibit heavier tails than predicted by the Gaussian model. Therefore, this paper challenges the normality assumption of the residual navigation errors in three ways. First, real data are used to assess its impact on the traditional RAIM algorithm. Second, extreme value theory is applied to the tails, and the generalized extreme value (GEV) distribution is derived to capture residual navigation errors. Third, the performance of the traditional RAIM approach is compared with that employing the GEV distribution. The results demonstrate that the GEV model is a more accurate representation of the distribution of residual navigation errors than the conventional Gaussian model and should be used in the development of integrity monitoring algorithms.     

The Development of a Web‐based Demographic Data Extraction Tool for Population Monitoring

The Internet contains a great wealth of information available online. People search engines, such as WhitePages ( http://www.whitepages.com ), gather personal‐level demographic data, including full name, address, age and household members. Requiring only a surname and locational reference (e.g. city or postal code) as the minimum search criteria, such people search engines can be perceived as a gigantic database of demographic records. The objective of this article is to outline the development of a web‐based demographic data extraction tool for population monitoring. In this study, a web prototype was developed to extract web demographics of the Vietnamese‐American (VA) population in Texas, an ethnic minority with unique migration history, from WhitePages. After post‐processing, the personal‐level demographic data represent 40.3% of 202,003 VA in Texas reported by the American Community Survey (ACS) 2009. While all enumeration strategies, the web approach included, have their own strengths and weaknesses, this study suggests an alternative approach that is complementary to existing enumeration strategies. More research and development are needed to validate the accuracy of web demographics and further enhance data navigation and extraction rules. The utilization and release of web demographics must be cautious with regards to privacy and integrity of personal identity.     

基于手机数据的城市内部就业人口流动特征及形成机制分析——以武汉市为例

城市内部就业人口流动作为城市群体的主要移动形式,分析其特征及形成机理对城市规划、交通预测等具有重要意义。基于武汉市手机信令数据,识别职住人口分布与流动,构建城市内部就业流动网络。运用网络分析、可达性计算、逻辑回归等方法,分析城市内部就业流动的特征及其形成机制。研究表明,武汉市内部就业流动在数量上分布不均衡,大量就业流动集中于少数街道间。在空间上,就业流动随距离、可达时间增加而减少,并依地形、文化形成若干联系紧密的就业社区;以就业流出地居住人口、流入地工作人口度量的就业势能是驱动就业流动的最主要因素,而文化差异、空间不邻近、可达性差阻碍就业流动的发生。此外,不同产业特色对就业流动影响不同,商业、科教阻碍就业外流,工业吸引外来就业。     

Entropy error model of planar geometry features in GIS

Positional error of line segments is usually described by using “g-band”, however, its band width is in relation to the confidence level choice. In fact, given different confidence levels, a series of concentric bands can be obtained. To overcome the effect of confidence level on the error indicator, by introducing the union entropy theory, we propose an entropy error ellipse index of point, then extend it to line segment and polygon, and establish an entropy error band of line segment and an entropy error donut of polygon. The research shows that the entropy error index can be determined uniquely and is not influenced by confidence level, and that they are suitable for positional uncertainty of planar geometry features.     

基于资源卫星数据面向对象法的红树林提取研究

利用无人机在研究区域内采集了红树林分类的训练样本点,基于资源三号高分影像对红树林进行分类。首先采用面向对象的方法,建立决策树对保护区内红树林进行提取。之后基于面向对象法对红树林区域进行种间分类,分析保护区内红树林种群空间分布格局。研究表明,红树林种间分类精度达到76.67%,总体Kappa系数为0.68,结果具有高度一致性。本文为红树林自然保护区的管理提供理论支撑,为红树林湿地保护和生态恢复提供科学依据。     

结合先验概率估计的GF-3影像水体概率估计方法

综合SAR(synthetic aperture radar)影像的统计模型假设与k-means聚类算法,提出了一种结合水体分布先验概率估计的水体概率估计方法。首先,用贝叶斯推断对研究区域后向散射系数做统计模型假设。随后,结合聚类算法对像元作分类,估计水体分布先验概率,结合统计分布直方图使用非线性最小二乘拟合完成模型参数估计。试验选取了高分三号(GF-3)多种工作模式数据,并用高分一号(GF-1)影像进行验证。结果表明,该方法可有效实现SAR影像的高精度水体概率估计。