The Reliability of Using the Iterative Proportional Fitting Procedure*

This paper demonstrates the utility of the iterative proportional fitting procedure (IPF) in generating disaggregated spatial data from aggregated data and evaluates the performance of the procedure. Estimates of individual level data created by IPF using data of equal-interval categories are reliable, but the performance of the estimation can be improved by increasing sample size. The improvement usually is enough to offset the increase in error created by other factors. If the two variables defining the cross-classification have a significant interaction effect and the number of categories in each variable is larger than two, then IPF is preferred over an independent model.     

A modified binary space partitioning tree for geographic information systems

We present a reactive data structure, that is, a spatial data structure with detail levels. The two properties, spatial organization and detail levels, are the basis for a geographic information system (GIS) with a multi-scale database. A reactive data structure is a novel type of data structure catering to multiple detail levels with rapid responses to spatial queries. It is presented here as a modification of the binary space partitioning tree that includes the levels of detail. This tree is one of the few spatial data structures that does not organize space in a rectangular manner. A prototype system has been implemented. An important result of this implementation is that it shows that binary space partitioning trees of real maps have O(n) storage space complexity in contrast to the theoretical worst case O(n² ), with n the number of line segments in the map.     

Comparison of existing methods for building triangular irregular network,models of terrain from grid digital elevation models

Abstract

Triangulated irregular networks (TINs) are increasingly popular for their efficiency in data storage and their ability to accommodate irregularly spaced elevation points for many applications of geographical information systems. This paper reviews and evaluates various methods for extracting TINs from dense digital elevation models (DEMs) on a sample DEM. Both structural and statistical comparisons show that the methods perform with different rates of success in different settings. Users of DEM to TIN conversion methods should be aware of the strengths and weaknesses of the methods in addition to their own purposes before conducting the conversion.     

Stochastic model-based methods for handling uncertainty in areal interpolation

Handling of uncertainty in the estimation of values from source areas to target areas poses a challenge in areal interpolation research. Stochastic model-based methods offer a basis for incorporating such uncertainty, but to date they have not been widely adopted by the GIS community. In this article, we propose one use of such methods based in the problem of interpolating count data from a source set of zones (parishes) to a more widely used target zone geography (postcode sectors). The model developed also uses ancillary statistical count data for a third set of areas nested within both source and target zones. The interpolation procedure was implemented within a Bayesian statistical framework using Markov chain Monte Carlo methods, enabling us to take account of all sources of uncertainty included in the model. Distributions of estimated values at the target zone level are presented using both summary statistics and as individual realisations selected to illustrate the degree of uncertainty in the interpolation results. We aim to describe the use of such stochastic approaches in an accessible way and to highlight the need for quantifying estimation uncertainty arising in areal interpolation, especially given the implications arising when interpolated values are used in subsequent analyses of relationships.     

Monitoring Mongolia Gobi dust transport using OMI data

The characteristics of long-distance dust transport from Asia to the United States over the Pacific Ocean are statistically analyzed using OMI AI (Ozone Monitoring Instrument Aerosol Index) data during 2005–2007. The results show that there is a high correlation of AI (the correlation coefficients are as high as 0.83 in March, 0.62 in April and 0.54 in May) between the Mongolia Gobi Desert and the west coast region of the United States (40°–50°N, 120°–130°W), indicating a strong source-receptor area relationship. Through calculating the lag correlation coefficient of the dust propagation time, we determined that the dust propagation time from the Mongolia Gobi Desert to the west coast of the United States is about 6–7 days at the 99% confidence level.     

Predicting demand for 311 non-emergency municipal services: An adaptive space-time kernel approach

Many cities in the United States and Canada offer a 311 helpline to their residents for submitting requests for non-emergency municipal services. By dialing 311, urban residents can report a range of public issues that require governmental attention, including potholes, graffito, sanitation complaints, and tree debris. The demand for these municipal services fluctuates greatly with time and location, which poses multiple challenges to effective deployment of limited resources. To address these challenges, this study uses a locally adaptive space-time kernel approach to model 311 requests as an inhomogeneous Poisson process and presents an analytical framework to generate predictions of 311 demand in space and time. The predictions can be used to optimally allocate resources and staff, reduce response time, and allow long-term dynamic planning. We use a bivariate spatial kernel to identify the spatial structure and weigh each kernel by corresponding past observations to capture the temporal dynamics. Short-term serial dependency and weekly temporality are modeled through the temporal weights, which are adaptive to local community areas. We also transform the computation-intensive parameter estimation procedure to a low dimensional optimization problem by fitting to the autocorrelation function of historical requests. The presented method is demonstrated and validated with sanitation service requests in Chicago. The results indicate that it performs better than common industry practice and conventional spatial models with a comparable computational cost.     

风沙物理学中两个焦点问题研究现状与未来研究思路刍议

风沙物理学经过数十年的发展与完善,可以说基本上自成体系。但由于学科的起步较晚,加之现象的复杂性,目前仍有很多重要的理论问题没能彻底解决,至少还未达成共识,成为学术界长期以来争论的焦点,从而影响了学科的继续发展。对“沙粒起动机制”和“风成沙纹的形成机理”两个焦点问题在进行研究现状剖析的基础上,浅析未来研究思路。提出沙粒起动主要驱动力是驻点升力的观点,以空气动力学理论为基础的沙粒起动机制研究将是未来该领域的发展趋势;关于沙纹的形成,认为沙粒粒径的不均匀性以及所导致的非平衡运动是前提和基础,风沙流运动过程中类似左右沙丘运动的蚀积转换规律是使沙纹能够维持其稳定形态的必要条件,而沙纹有规律、整齐划一的分布与排列可能与背风面气流小尺度的涡流有关。     

基于GIS的四射珊瑚分类信息系统

古生物学是一门古老的学科,在长期的研究中积累了大量的资料,如何充分利用这些宝贵 的资料,是人们关注的热点。计算机技术的发展,特别是近年来ＧＩＳ在各学科的应用,为古生物学研究提供了新的方法,为长期以来所积累的大量数据的分析与再利用提供了有效的研究手段。     

利津县努力争当服务经济建设排头兵

Oracle数据库管理系统已成为我国国家级和省级国土资源基础数据库建设的主流技术平台。该文就国家级和省级数据库的建设,提出了在Oracle数据库技术环境下,如何在物理上合理组织和布局各种类型的数据,如何设置和管理各衍生数据,如何实施数据完整性要求,其目的是实现国土资源基础数据的高效管理和可持续更新支持,更好地满足国土资源基础数据库之上各业务应用系统运转的要求。