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1.
Dasymetric Spatiotemporal Interpolation   总被引：2，自引：0，他引：2  
This research applies the principles of dasymetric mapping to spatiotemporal interpolation by extending the spatial concepts of zone and area to their temporal analogs of interval and duration, respectively. An example application of dasymetric spatiotemporal interpolation using crime event data is presented. Results indicate that dasymetric spatiotemporal interpolation significantly improves the accuracy of estimates over areal or duration weighting. In addition, even when dasymetric interpolation in either the spatial or temporal dimension is relatively weak, combining dasymetric estimation in both space and time dimensions simultaneously has the potential to amplify the accuracy of the overall dasymetric estimation.  相似文献   

2.
Fine-resolution population mapping using OpenStreetMap points-of-interest   总被引：1，自引：0，他引：1  
Data on population at building level is required for various purposes. However, to protect privacy, government population data is aggregated. Population estimates at finer scales can be obtained through areal interpolation, a process where data from a first spatial unit system is transferred to another system. Areal interpolation can be conducted with ancillary data that guide the redistribution of population. For population estimation at the building level, common ancillary data include three-dimensional data on buildings, obtained through costly processes such as LiDAR. Meanwhile, volunteered geographic information (VGI) is emerging as a new category of data and is already used for purposes related to urban management. The objective of this paper is to present an alternative approach for building level areal interpolation that uses VGI as ancillary data. The proposed method integrates existing interpolation techniques, i.e., multi-class dasymetric mapping and interpolation by surface volume integration; data on building footprints and points-of-interest (POIs) extracted from OpenStreetMap (OSM) are used to refine population estimates at building level. A case study was conducted for the city of Hamburg and the results were compared using different types of POIs. The results suggest that VGI can be used to accurately estimate population distribution, but that further research is needed to understand how POIs can reveal population distribution patterns.  相似文献   

3.
Novel digital data sources allow us to attain enhanced knowledge about locations and mobilities of people in space and time. Already a fast-growing body of literature demonstrates the applicability and feasibility of mobile phone-based data in social sciences for considering mobile devices as proxies for people. However, the implementation of such data imposes many theoretical and methodological challenges. One major issue is the uneven spatial resolution of mobile phone data due to the spatial configuration of mobile network base stations and its spatial interpolation. To date, different interpolation techniques are applied to transform mobile phone data into other spatial divisions. However, these do not consider the temporality and societal context that shapes the human presence and mobility in space and time. The paper aims, first, to contribute to mobile phone-based research by addressing the need to give more attention to the spatial interpolation of given data, and further by proposing a dasymetric interpolation approach to enhance the spatial accuracy of mobile phone data. Second, it contributes to population modelling research by combining spatial, temporal and volumetric dasymetric mapping and integrating it with mobile phone data. In doing so, the paper presents a generic conceptual framework of a multi-temporal function-based dasymetric (MFD) interpolation method for mobile phone data. Empirical results demonstrate how the proposed interpolation method can improve the spatial accuracy of both night-time and daytime population distributions derived from different mobile phone data sets by taking advantage of ancillary data sources. The proposed interpolation method can be applied for both location- and person-based research, and is a fruitful starting point for improving the spatial interpolation methods for mobile phone data. We share the implementation of our method in GitHub as open access Python code.  相似文献   

4.
To assess micro-scale population dynamics effectively, demographic variables should be available over temporally consistent small area units. However, fine-resolution census boundaries often change between survey years. This research advances areal interpolation methods with dasymetric refinement to create accurate consistent population estimates in 1990 and 2000 (source zones) within tract boundaries of the 2010 census (target zones) for five demographically distinct counties in the US. Three levels of dasymetric refinement of source and target zones are evaluated. First, residential parcels are used as a binary ancillary variable prior to regular areal interpolation methods. Second, Expectation Maximization (EM) and its data-extended version leverage housing types of residential parcels as a related ancillary variable. Finally, a third refinement strategy to mitigate the overestimation effect of large residential parcels in rural areas uses road buffers and developed land cover classes. Results suggest the effectiveness of all three levels of dasymetric refinement in reducing estimation errors. They provide a first insight into the potential accuracy improvement achievable in varying geographic and demographic settings but also through the combination of different refinement strategies in parts of a study area. Such improved consistent population estimates are the basis for advanced spatio-temporal demographic research.  相似文献   

5.
The US Census provides the primary source of spatially explicit social data, but changing block boundaries complicate analyses of housing growth over time. We compared procedures for reconciling housing density data between 1990 and 2000 census block boundaries in order to assess the sensitivity of analytical methods to estimates of housing growth in Oregon. Estimates of housing growth varied substantially and were sensitive to the method of interpolation. With no processing and areal‐weighted interpolation, more than 35% of the landscape changed; 75–80% of this change was due to decline in housing density. This decline was implausible, however, because housing structures generally persist over time. Based on aggregated boundaries, 11% of the landscape changed, but only 4% experienced a decline in housing density. Nevertheless, the housing density change map was almost twice as coarse spatially as the 2000 housing density data. We also applied a dasymetric approach to redistribute 1990 housing data into 2000 census boundaries under the assumption that the distribution of housing in 2000 reflected the same distribution as in 1990. The dasymetric approach resulted in conservative change estimates at a fine resolution. All methods involved some type of trade‐off (e.g. analytical difficulty, data resolution, magnitude or bias in direction of change). However, our dasymetric procedure is a novel approach for assessing housing growth over changing census boundaries that may be particularly useful because it accounts for the uniquely persistent nature of housing over time.  相似文献   

6.
Generating Surface Models of Population Using Dasymetric Mapping*   总被引：2，自引：0，他引：2  
Aggregated demographic datasets are associated with analytical and cartographic problems due to the arbitrary nature of areal unit partitioning. This article describes a methodology for generating a surface‐based representation of population that mitigates these problems. This methodology uses dasymetric mapping and incorporates areal weighting and empirical sampling techniques to assess the relationship between categorical ancillary data and population distribution. As a demonstration, a 100‐meter‐resolution population surface is generated from U.S. Census block group data for the southeast Pennsylvania region. Remote‐sensing‐derived urban land‐cover data serve as ancillary data in the dasymetric mapping.  相似文献   

7.
This article describes and compares six disaggregation methods used to produce a dasymetric population density grid of the European Union at a 100 m resolution. Population data were initially available at commune level. The main ancillary information source was CORINE land cover, a land cover map distributed by the European Environment Agency. Information from the Eurostat point survey, land use/cover area frame survey, was also integrated in the parameter estimation of some of the approaches tested. Accurate population data for 1 km cell grids were provided by the Statistical Offices of Austria, Denmark, Finland, the Netherlands, Northern Ireland, Estonia and Sweden. These data provided the basic reference to quantify the accuracy of each method. The best results were obtained with a modified version of the limiting variable method (Eicher, C. and Brewer, C., 2001. Dasymetric mapping and areal interpolation: implementation and evaluation. Cartography and Geographic Information Science, 28, 125–138) that could be implemented, thanks to the national reference grids. For other methods the parameters could be estimated without using the reference grids; among them a method based on logit regression gave the best results. Compared with the traditional choropleth maps that represent a homogeneous density in each commune, the accuracy improvement of the disaggregated maps ranged between 20% and 67% (between 46% and 67% for the best method).  相似文献   

8.
Land cover class composition of remotely sensed image pixels can be estimated using soft classification techniques increasingly available in many GIS packages. However, their output provides no indication of how such classes are distributed spatially within the instantaneous field of view represented by the pixel. Techniques that attempt to provide an improved spatial representation of land cover have been developed, but not tested on the difficult task of mapping from real satellite imagery. The authors investigated the use of a Hopfield neural network technique to map the spatial distributions of classes reliably using information of pixel composition determined from soft classification previously. The approach involved designing the energy function to produce a ‘best guess’ prediction of the spatial distribution of class components in each pixel. In previous studies, the authors described the application of the technique to target identification, pattern prediction and land cover mapping at the sub-pixel scale, but only for simulated imagery. We now show how the approach can be applied to Landsat Thematic Mapper (TM) agriculture imagery to derive accurate estimates of land cover and reduce the uncertainty inherent in such imagery. The technique was applied to Landsat TM imagery of small-scale agriculture in Greece and largescale agriculture near Leicester, UK. The resultant maps provided an accurate and improved representation of the land covers studied, with RMS errors for the Landsat imagery of the order of 0.1 in the new fine resolution map recorded. The results showed that the neural network represents a simple efficient tool for mapping land cover from operational satellite sensor imagery and can deliver requisite results and improvements over traditional techniques for the GIS analysis of practical remotely sensed imagery at the sub pixel scale.  相似文献   

9.
Why GPS makes distances bigger than they are   总被引：1，自引：0，他引：1  
Global navigation satellite systems such as the Global Positioning System (GPS) is one of the most important sensors for movement analysis. GPS is widely used to record the trajectories of vehicles, animals and human beings. However, all GPS movement data are affected by both measurement and interpolation errors. In this article we show that measurement error causes a systematic bias in distances recorded with a GPS; the distance between two points recorded with a GPS is – on average – bigger than the true distance between these points. This systematic ‘overestimation of distance’ becomes relevant if the influence of interpolation error can be neglected, which in practice is the case for movement sampled at high frequencies. We provide a mathematical explanation of this phenomenon and illustrate that it functionally depends on the autocorrelation of GPS measurement error (C). We argue that C can be interpreted as a quality measure for movement data recorded with a GPS. If there is a strong autocorrelation between any two consecutive position estimates, they have very similar error. This error cancels out when average speed, distance or direction is calculated along the trajectory. Based on our theoretical findings we introduce a novel approach to determine C in real-world GPS movement data sampled at high frequencies. We apply our approach to pedestrian trajectories and car trajectories. We found that the measurement error in the data was strongly spatially and temporally autocorrelated and give a quality estimate of the data. Most importantly, our findings are not limited to GPS alone. The systematic bias and its implications are bound to occur in any movement data collected with absolute positioning if interpolation error can be neglected.  相似文献   

10.
Abstract

Kriging is an optimal method of spatial interpolation that produces an error for each interpolated value. Block kriging is a form of kriging that computes averaged estimates over blocks (areas or volumes) within the interpolation space. If this space is sampled sparsely, and divided into blocks of a constant size, a variable estimation error is obtained for each block, with blocks near to sample points having smaller errors than blocks farther away. An alternative strategy for sparsely sampled spaces is to vary the sizes of blocks in such away that a block's interpolated value is just sufficiently different from that of an adjacent block given the errors on both blocks. This has the advantage of increasing spatial resolution in many regions, and conversely reducing it in others where maintaining a constant size of block is unjustified (hence achieving data compression). Such a variable subdivision of space can be achieved by regular recursive decomposition using a hierarchical data structure. An implementation of this alternative strategy employing a split-and-merge algorithm operating on a hierarchical data structure is discussed. The technique is illustrated using an oceanographic example involving the interpolation of satellite sea surface temperature data. Consideration is given to the problem of error propagation when combining variable resolution interpolated fields in GIS modelling operations.  相似文献   

11.
New expressions are derived for the standard errors in the eigenvalues of a cross-product matrix by themethod of error propagation.Cross-product matrices frequently arise in multivariate data analysis,especially in principal component analysis (PCA).The derived standard errors account for the variabilityin the data as a result of measurement noise and are therefore essentially different from the standarderrors developed in multivariate statistics.Those standard errors were derived in order to account for thefinite number of observations on a fixed number of variables,the so-called sampling error.They can beused for making inferences about the population eigenvalues.Making inferences about the populationeigenvalues is often not the purposes of PCA in physical sciences,This is particularly true if themeasurements are performed on an analytical instrument that produces two-dimensional arrays for onechemical sample:the rows and columns of such a data matrix cannot be identified with observations onvariables at all.However,PCA can still be used as a general data reduction technique,but now the effectof measurement noise on the standard errors in the eigenvalues has to be considered.The consequencesfor significance testing of the eigenvalues as well as the usefulness for error estimates for scores andloadings of PCA,multiple linear regression (MLR) and the generalized rank annihilation method(GRAM) are discussed.The adequacy of the derived expressions is tested by Monte Carlo simulations.  相似文献   

12.
A Point-Based Intelligent Approach to Areal Interpolation   总被引：1，自引：0，他引：1  
Areal interpolation is the data transfer from one zonal system to another. A survey of previous literature on this subject points out that the most effective methods for areal interpolation are the intelligent approaches, which often take two-dimensional (2-D) land use or one-dimensional (1-D) road network information as ancillary data to give insight on the underlying distribution of a variable. However, the 2-D or 1-D ancillary information is not always applicable for the variable of interest in a specific study area. This article introduces a point-based intelligent approach to the areal interpolation problem by using zero-dimensional (0-D) points as ancillary data that are locationally associated with the variable of interest. The connection between zonal variables and point locations can be modeled with a linear or a nonlinear exponential function, which incorporates the distribution of the variables in the transferring of the information from the source zone to the target zone. An experimental study interpolating the population data at a suburbanized area suggests that the proposed method is an attractive alternative to other areal interpolation solutions based on the evaluation of its resulting accuracy and efficiency.  相似文献   

13.
This paper describes four methods of rapidly mapping vegetation using satellite imagery, for use in updating the vegetation layer of the New Zealand Land Resource Inventory (NZLRI). The visual interpretation method was tested in a 500 km2 study area on the North Island west coast where 3 6 NZLRI vegetation classes occurred. Sixteen distinct groups of NZLRI vegetation classes were identified on Landsat Thematic Mapper imagery, and named “image classes”. Classes were identified by correlating ground data with image colour and texture and by using recognisable landform and cultural features. A limited number of vegetation changes have occurred since NZLRI mapping was first carried out. Updating the vegetation layer of the NZLRI requires recognising and mapping changes and modifying the database. Identifying distinctive groups of NZLRI vegetation classes on satellite imagery will facilitate this.  相似文献   

14.
人口密度空间化的一种方法   总被引：22，自引：2，他引：20  
人口密度空间化是地理学中一个重要的研究课题,但是传统方法直接生成的人口密度分布图具有不同区域间突变的缺点。该文中基于面积权重内插法与邻域平均法原理,以MapInfo为软件平台,在缺乏地形图、RS图片等资料的情况下,提出人口密度空间化的一种方法——网格单元面积权重内插法,并以丰县为研究区域进行例证。结果表明：该方法有效缓和了传统方法直接生成的人口密度图中的突变线,制作的人口密度Grid专题地图能够很好地反映人口密度的平均性,生成的人口密度三维可视化地图符合人口密度的空间分布特点。  相似文献   

15.
The criteria which may be employed when selecting an approach to a particular evapotranspiration mapping problem are discussed in the light of previous attempts at mapping evapotranspiration. Evapotranspiration mapping involves two main stages: firstly the derivation of point evapotranspiration estimates, and secondly the interpolation of isolines around these estimates. Many studies have emphasized the first stage, frequently applying estimation formulae to data from climate stations, and have given substantially less attention to the interpolation of isolines. In the present study, where potential evapotranspiration estimates were derived for only 70 stations over the area of the European Economic Community and where maps showing the general trends in potential evapotranspiration were required, the technique of isoline interpolation was of great importance. Two forms of polynomial trend surface analysis were applied to the point estimates and a technique employing a restricted use of all three dimensions of location was found to be appropriate for denning the position of the smoothed evapotranspiration isolines.  相似文献   

16.
This article describes a high-resolution land cover data set for Spain and its application to dasymetric population mapping (at census tract level). Eventually, this vector layer is transformed into a grid format. The work parallels the effort of the Joint Research Centre (JRC) of the European Commission, in collaboration with Eurostat and the European Environment Agency (EEA), in building a population density grid for the whole of Europe, combining CORINE Land Cover with population data per commune. We solve many of the problems due to the low resolution of CORINE Land Cover, which are especially visible with Spanish data. An accuracy assessment is carried out from a simple aggregation of georeferenced point population data for the region of Madrid. The bottom-up grid constructed in this way is compared to our top-down grid. We show a great improvement over what has been reported from commune data and CORINE Land Cover, but the improvements seem to come entirely from the higher resolution data sets and not from the statistical modeling in the downscaling exercise. This highlights the importance of providing the research community with more detailed land cover data sets, as well as more detailed population data. The dasymetric grid is available free of charge from the authors upon request.  相似文献   

17.
格网人口图的计算机制图方法   总被引：1，自引：0，他引：1  
本文以江苏为例,对约100幅地形图进行全盘采样,获得三万多居民地小方块数据,应用小方块与人口之间的密切关系,进一步获得三万多人口数据。在此基础上做出分别以格网分区图表法、格网分级比值法、等值线法表示的三幅江苏省人口密度图;以定位布点法表示的江苏省人口分布图。它们的共同特点是都以大量人口数据为基础编制而成。  相似文献   

18.
We examined the impact of temporal dependence between patterns of error in classified time-series imagery through a simulation modeling approach. This research extended the land-cover-change simulation model we previously developed to investigate: (1) the assumption of temporal independence between patterns of error in classified time-series imagery; and (2) the interaction of patterns of change and patterns of error in a post-classification change analysis. In this research, the thematic complexity of the classified land-cover maps was increased by increasing the number of simulated land-cover classes. Simulating maps with increased categorical resolution permitted the incorporation of: (1) higher-order, more complex spatial and temporal interactions between land-cover classes; and (2) patterns of error that better reproduce the complex error interactions that often occur in time-series classified imagery. The overall modeling framework was divided into two primary components: (1) generation of a map representing true change; and (2) generation of a suite of change maps that had been perturbed by specific patterns of error. All component maps in the model were produced using simulated annealing, which enabled us to create a series of map realizations with user-defined spatial and temporal patterns. Comparing the true map of change to the error-perturbed maps of change using accuracy assessment statistics showed that increasing the temporal dependence between classification errors did not improve the accuracy of resulting maps of change when the categorical scale of the land-cover classified maps was increased. The increased structural complexity within the time series of maps effectively inhibited the impact of temporal dependence. However, results demonstrated that there are interactions between patterns of error and patterns of change in a post-classification change analysis. These interactions played a major role in determining the accuracy associated with the maps of change.  相似文献   

19.
Influence of survey strategy and interpolation model on DEM quality   总被引：2，自引：0，他引：2  
Accurate characterisation of morphology is critical to many studies in the field of geomorphology, particularly those dealing with changes over time. Digital elevation models (DEMs) are commonly used to represent morphology in three dimensions. The quality of the DEM is largely a function of the accuracy of individual survey points, field survey strategy, and the method of interpolation. Recommendations concerning field survey strategy and appropriate methods of interpolation are currently lacking. Furthermore, the majority of studies to date consider error to be uniform across a surface. This study quantifies survey strategy and interpolation error for a gravel bar on the River Nent, Blagill, Cumbria, UK. Five sampling strategies were compared: (i) cross section; (ii) bar outline only; (iii) bar and chute outline; (iv) bar and chute outline with spot heights; and (v) aerial LiDAR equivalent, derived from degraded terrestrial laser scan (TLS) data. Digital Elevation Models were then produced using five different common interpolation algorithms. Each resultant DEM was differentiated from a terrestrial laser scan of the gravel bar surface in order to define the spatial distribution of vertical and volumetric error. Overall triangulation with linear interpolation (TIN) or point kriging appeared to provide the best interpolators for the bar surface. Lowest error on average was found for the simulated aerial LiDAR survey strategy, regardless of interpolation technique. However, comparably low errors were also found for the bar-chute-spot sampling strategy when TINs or point kriging was used as the interpolator. The magnitude of the errors between survey strategy exceeded those found between interpolation technique for a specific survey strategy. Strong relationships between local surface topographic variation (as defined by the standard deviation of vertical elevations in a 0.2-m diameter moving window), and DEM errors were also found, with much greater errors found at slope breaks such as bank edges. A series of curves are presented that demonstrate these relationships for each interpolation and survey strategy. The simulated aerial LiDAR data set displayed the lowest errors across the flatter surfaces; however, sharp slope breaks are better modelled by the morphologically based survey strategy. The curves presented have general application to spatially distributed data of river beds and may be applied to standard deviation grids to predict spatial error within a surface, depending upon sampling strategy and interpolation algorithm.  相似文献   

20.
Historical GIS has the potential to re‐invigorate our use of statistics from historical censuses and related sources. In particular, areal interpolation can be used to create long‐run time‐series of spatially detailed data that will enable us to enhance significantly our understanding of geographical change over periods of a century or more. The difficulty with areal interpolation, however, is that the data that it generates are estimates which will inevitably contain some error. This paper describes a technique that allows the automated identification of possible errors at the level of the individual data values.  相似文献   

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