A geostatistical approach to the change-of-support problem and variable-support data fusion in spatial analysis

A key issue to address in synthesizing spatial data with variable-support in spatial analysis and modeling is the change-of-support problem. We present an approach for solving the change-of-support and variable-support data fusion problems. This approach is based on geostatistical inverse modeling that explicitly accounts for differences in spatial support. The inverse model is applied here to produce both the best predictions of a target support and prediction uncertainties, based on one or more measurements, while honoring measurements. Spatial data covering large geographic areas often exhibit spatial nonstationarity and can lead to computational challenge due to the large data size. We developed a local-window geostatistical inverse modeling approach to accommodate these issues of spatial nonstationarity and alleviate computational burden. We conducted experiments using synthetic and real-world raster data. Synthetic data were generated and aggregated to multiple supports and downscaled back to the original support to analyze the accuracy of spatial predictions and the correctness of prediction uncertainties. Similar experiments were conducted for real-world raster data. Real-world data with variable-support were statistically fused to produce single-support predictions and associated uncertainties. The modeling results demonstrate that geostatistical inverse modeling can produce accurate predictions and associated prediction uncertainties. It is shown that the local-window geostatistical inverse modeling approach suggested offers a practical way to solve the well-known change-of-support problem and variable-support data fusion problem in spatial analysis and modeling.     

Drainage skeletonization from flow-accumulated area without the use of threshold

This study presents a method of automatic drainage skeletonization from flow-accumulated area without the use of threshold which conserves drainage geometry at chosen digital elevation model (DEM) scale. To get all possible drainage at the chosen scale, stream order raster is generated by incorporating flow accumulation and flow direction raster derived from corresponding DEM. This allows generation of drainage network without the use of threshold. Resultant stream order raster, termed as raw stream order raster (RSOR), is tested against threshold defined stream order raster to evaluate its efficiency. Use of RSOR allows extraction of stream heads to greater stream head extent. Again, DEM downscaling takes care of overestimation in number of streams. So, the proposed technique is effective in controlling two basic aspects of drainage characteristics – stream number and extent. In our case, drainage estimated from re-sampled medium-scale DEM has the closest matching with that of the reference topographical map.     

一种抗切割处理的栅格地理数据水印算法

本文提出了一种基于精度特征的栅格地理数据盲水印算法。首先,分析了栅格地理数据切割处理的特征及其对常规水印算法产生的影响,在此基础上,结合栅格地理数据精度特点,依据栅格地理数据的有效位平面生成水印信息位,而后,采用量化思想将水印信息嵌入对应的可变位平面。实验表明,所提出的水印算法在保证栅格地理数据精度的基础上,对于任意尺寸的数据都有较好的适用性,同时,对于任意强度的切割处理,该算法都体现了良好的鲁棒性。     

Monitoring vegetation dynamics with medium resolution MODIS-EVI time series at sub-regional scale in southern Africa

Currently there is a lack of knowledge on spatio-temporal patterns of land surface dynamics at medium spatial scale in southern Africa, even though this information is essential for better understanding of ecosystem response to climatic variability and human-induced land transformations. In this study, we analysed vegetation dynamics across a large area in southern Africa using the 14-years (2000–2013) of medium spatial resolution (250 m) MODIS-EVI time-series data. Specifically, we investigated temporal changes in the time series of key phenometrics including overall greenness, peak and timing of annual greenness over the monitoring period and study region. In order to specifically capture spatial and per pixel vegetation changes over time, we calculated trends in these phenometrics using a robust trend analysis method. The results showed that interannual vegetation dynamics followed precipitation patterns with clearly differentiated seasonality. The earliest peak greenness during 2000–2013 occurred at the end of January in the year 2000 and the latest peak greenness was observed at the mid of March in 2012. Specifically spatial patterns of long-term vegetation trends allowed mapping areas of (i) decrease or increase in overall greenness, (ii) decrease or increase of peak greenness, and (iii) shifts in timing of occurrence of peak greenness over the 14-year monitoring period. The observed vegetation decline in the study area was mainly attributed to human-induced factors. The obtained information is useful to guide selection of field sites for detailed vegetation studies and land rehabilitation interventions and serve as an input for a range of land surface models.     

All Equal-Area Map Projections Are Created Equal,But Some Are More Equal Than Others

High-resolution regional and global raster databases are currently being generated for a variety of environmental and scientific modeling applications. The projection of these data from geographic coordinates to a plane coordinate system is subject to significant areal error. Sources of error include users selecting an inappropriate projection or incorrect parameters for a given projection, algorithmic errors in commercial geographic information system (GIS) software, and errors resulting from the projection of data in the raster format. To assess the latter type of errors, the accuracy of raster projection was analyzed by two methods. First, a set of 12 one-degree by one-degree quadrilaterals placed at various latitudes was projected at several raster resolutions and compared to the projection of a vector representation of the same quadrilaterals. Second, several different raster resolutions of land cover data for Asia were projected and the total areas of 21 land cover categories were tabulated and compared. While equal-area projections are designed to specifically preserve area, the comparison of the results of the one-degree by one-degree quadrilaterals with the common equal area projections (e.g., the Mollweide) indicates a considerable variance in the one-degree area after projection. Similarly, the empirical comparison of land cover areas for Asia among various projections shows that total areas of land cover vary with projection type, raster resolution, and latitude. No single projection is best for all resolutions and all latitudes. While any of the equal-area projections tested are reasonably accurate for most applications with resolutions of eight-kilometer pixels or smaller, significant variances in accuracies appear at larger pixel sizes.     

一种基于SPA的多数据流同异反分析法

提出了一种分析多数据流变化趋势的新方法。该方法引入集对分析思想,使用峰值数据进行分析,计算简单、数据量小。实验表明,峰值的变化趋势较能真实地反映数据流的变化趋势;同时,本方法对解决样本点个数不一致的问题是有效的。     

在SuperMap平台下的栅格数据矢量化

将静态的纸张和影像地图及传统的各类地理信息转化为数字时代的电子信息,其中的关键环节是怎样将栅格数据矢量化。通过在国产软件SuperMap环境下进行栅格数据矢量化过程,详细描述了栅格数据、矢量数据、坐标系、投影坐标系、地图配准和镶嵌等专业基础知识在实际中的应用。     

ArcGIS SDE在地理国情普查中的应用

主要介绍ArcSDE的基本概况,根据地理国情普查过程中栅格数据及地理数据库存储量大的特点,讨论了ArcSDE在地理国情普查生产中的应用。     

第三次全国国土调查土地利用矢量数据栅格化方法

第三次全国国土调查县级土地利用图斑层包含利用类型、耕地类型、坡度等级、种植属性等多属性信息,将县级土地利用矢量数据集成栅格化形成全国无缝的多尺度、多专题栅格产品存在一定技术难度。本文针对第三次全国国土调查土地利用栅格产品应用需求,探讨了多属性综合编码、全国基础地理网格框架、栅格化产品数据模型、矢量栅格化等技术方法,建立了全国土地利用栅格产品生产流程,开展了全国多尺度、多专题土地利用栅格产品生产验证。结果表明:本文方法能够实现第三次全国国土调查土地利用矢量图斑多属性信息集成栅格化和全国多尺度、多专题土地利用栅格产品工程化生产,可为今后的国土调查土地利用栅格产品生产和共享应用提供支撑。     

全国土地利用动态监测结果栅格数据矢量化

为了有效地管理和使用国土资源大调查中的土地利用动态监测成果数据 ,将监测成果及时有效地应用于日常的土地管理和规划中 ,需要建立动态监测数据库。本文阐述了在建立数据库过程中 ,如何将动态监测成果的栅格数据矢量化以及如何将栅格数据和矢量数据统一到一个地理数据库系统中的方法     

Ontology‐based Qualitative Feature Analysis: Bays as a Case Study

A methodology for analyzing geographic data using the techniques of: (1) qualitative geometric abstraction; and (2) ontological analysis of geographic features is described. The first technique is a bottom‐up approach to extract qualitative spatial relations from geographic representations (raster or vector) while the second technique is a top‐down approach to determine which qualitative relations can possibly hold between the parts of the geographic features. The process of analyzing geographic data includes the extraction of both the features and the qualitative relations among features. These qualitative relations are then used to classify the geographic features within the “space” of ontological possibilities. In this article bays in Wisconsin and their cartographic representation are used as a running example and the subject of a case study.     

Analysis of geographical disparities in temporal trends of health outcomes using space–time joinpoint regression

Analyzing temporal trends in health outcomes can provide a more comprehensive picture of the burden of a disease like cancer and generate new insights about the impact of various interventions. In the United States such an analysis is increasingly conducted using joinpoint regression outside a spatial framework, which overlooks the existence of significant variation among U.S. counties and states with regard to the incidence of cancer. This paper presents several innovative ways to account for space in joinpoint regression: (1) prior filtering of noise in the data by binomial kriging and use of the kriging variance as measure of reliability in weighted least-square regression, (2) detection of significant boundaries between adjacent counties based on tests of parallelism of time trends and confidence intervals of annual percent change of rates, and (3) creation of spatially compact groups of counties with similar temporal trends through the application of hierarchical cluster analysis to the results of boundary analysis. The approach is illustrated using time series of proportions of prostate cancer late-stage cases diagnosed yearly in every county of Florida since 1980s. The annual percent change (APC) in late-stage diagnosis and the onset years for significant declines vary greatly across Florida. Most counties with non-significant average APC are located in the north-western part of Florida, known as the Panhandle, which is more rural than other parts of Florida. The number of significant boundaries peaked in the early 1990s when prostate-specific antigen (PSA) test became widely available, a temporal trend that suggests the existence of geographical disparities in the implementation and/or impact of the new screening procedure, in particular as it began available.     

一种彩色栅格地图注记识别方法

栅格地图中的注记包含了丰富的地理位置信息,传统的栅格地图注记识别方法在识别过程中将注记和其对应的地理要素相分离,因此难以处理倾斜注记和弯曲注记。以连通域单元为基本处理对象,提出了一种基于几何特征的彩色栅格地图注记识别方法。首先利用连通域单元的方向、尺寸、密度、邻域四个特征提取注记像素集合,然后通过地理要素中心线对非水平注记进行方向确定,最后对注记进行聚类和重新排列,完成注记识别。通过对GoogleMap（谷歌地图）瓦片中的注记进行提取和识别实验,证明了该方法的合理性和有效性。     

Coupling land use allocation models with raster GIS

As geographic information systems (GIS) have moved from information storage and retrieval operations towards more decision support functions, there is a need for more integration of spatial analytical modules that can assist in locational decisions. This paper presents a methodology for coupling land use allocation models with a raster GIS. For raster systems, the integration of any decision module has been limited by the size of raster datasets that may contain hundreds of thousands of pixels. Therefore, decision heuristics have been used rather than exact methods such as mathematical programming models. For the problem of land use allocation, the special structure of the generalized assignment problem is used here to handle large scale datasets. The advantage of the mathematical programming approach is the additional information associated with the dual variables and opportunity costs that can be used in subsequent sensitivity analyses. Received: 7 April 1998/Accepted: 2 October 1998     

Large area forest inventory using Landsat ETM+: A geostatistical approach

Large area forest inventory is important for understanding and managing forest resources and ecosystems. Remote sensing, the Global Positioning System (GPS), and geographic information systems (GIS) provide new opportunities for forest inventory. This paper develops a new systematic geostatistical approach for predicting forest parameters, using integrated Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images, GPS, and GIS. Forest parameters, such as basal area, height, health conditions, biomass, or carbon, can be incorporated as a response variable, and the geostatistical approach can be used to predict parameter values for uninventoried points. Using basal area as the response and Landsat ETM+ images of pine stands in Georgia as auxiliary data, this approach includes univariate kriging (ordinary kriging and universal kriging) and multivariable kriging (co-kriging and regression kriging). The combination of bands 4, 3, and 2, as well as the combination of bands 5, 4, and 3, normalized difference vegetation index (NDVI), and principal components (PCs) were used in this study with co-kriging and regression kriging. Validation based on 200 randomly sampling points withheld field inventory was computed to evaluate the kriging performance and demonstrated that band combination 543 performed better than band combination 432, NDVI, and PCs. Regression kriging resulted in the smallest errors and the highest R-squared indicating the best geostatistical method for spatial predictions of pine basal area.     

基于XML的分布式WebGIS模型研究

随着Internet网络、计算机分布式计算技术的飞速发展以及地理信息系统应用的普及,分布式WebGIS已经成为一种必然的要求。介绍了一种基于XML的分布式WebGIS模型,根据用户不同的请求分别提供栅格地图、矢量地图和元数据服务。     

Reducing Linear and Perimeter Measurement Errors in Raster-based Data

An important issue in cartography and GIS is determining the appropriate resolution or cell size when converting vector data to raster. The general consensus is to make the cell size as small as possible to resolve geographic features and provide the most accurate estimates of measurements. Finer resolution results in more accurate estimates of polygon area; however, the raster data structure introduces an artifact that causes errors in the estimation of the length of linear features and of the perimeter of polygon features to increase with increasing resolution. Over-estimation as high as 41 percent is theoretically possible and was found to be around 26 percent for representative polygon maps. A method is described that uses a correction coefficient to reduce overestimation error to less than 3 percent.     

Modeling Situation Factors Used in MCE Procedures for Raster GIS

Multi‐criteria evaluation (MCE) procedures are widely used in raster‐based geographic information systems (GIS) to perform a variety of land use siting applications. Many of the criteria used in an MCE analysis are based on spatial relationships or situation characteristics. Situation factors measure the accessibility that each raster cell is to resources or land uses that generate spatial externalities for the activity being sited. This accessibility can be measured either in terms of distance to the nearest target cell containing resources or the overall level of resource availability as measured by a spatial interaction model. This paper examines the spatial structure of these situation factors to identify the set of critical target cells for which distance estimates are most sensitive. Critical target cells are especially important in the case of positive externalities in which an activity would be inclined to locate near these cells to use or consume the resources there. Critical target cells are useful for evaluating the utility of the final site selection with respect to resource/activity ratios.     

Assessing Raster GIS Approximation for Euclidean Shortest Path Routing

Identifying a route that avoids obstacles in continuous space is important for infrastructure alignment, robotic travel, and virtual object path planning, among others, because movement through space is not restricted to a predefined road or other network. Vector and raster GIS (geographic information system) solution approaches have been developed to find good/efficient routes. On the vector side, recent solution approaches exploit spatial knowledge and utilize GIS functionality, offering significant computational advantages in finding an optimal solution to this path routing problem. Raster‐based shortest path techniques are widely applied in route planning for wayfinding, corridor alignment, robotics and video gaming to derive an obstacle avoiding path, but represent an approximation approach for solving this problem. This research compares vector and raster approaches for identifying obstacle‐avoiding shortest paths/routes. Empirical assessment is carried out for a number of planning applications, highlighting representational issues, computational requirements and resulting path efficiency.     

Automated Extraction of Natural Drainage Density Patterns for the Conterminous United States through High-Performance Computing

Hydrographic networks form an important data foundation for cartographic base mapping and for hydrologic analysis. Drainage density patterns for these networks can be derived to characterize local landscape, bedrock and climate conditions, and further inform hydrological and geomorphological analysis by indicating areas where too few headwater channels are represented. Natural drainage density patterns are not consistently available in existing hydrographical data bases for the United States because compilation and capture criteria historically varied, along with climate, during the period of data collection over the various terrain types throughout the country. This paper demonstrates an automated workflow that is being tested in a high-performance computing environment by the U.S. Geological Survey (USGS) to map natural drainage density patterns at the 1:24,000-scale (24K) for the conterminous United States. Hydrographic network drainage patterns may be extracted from elevation data to guide corrections for existing hydrographic network data. The paper describes three stages in this workflow including data pre-processing, natural channel extraction, and generation of drainage density patterns from extracted channels. The workflow is implemented in parallel fashion by simultaneously executing procedures on multiple subbasin watersheds within the U.S. National Hydrography Dataset (NHD). Pre-processing defines parameters needed for the extraction process. Extraction proceeds in standard fashion: filling sinks, developing flow direction and weighted flow accumulation rasters. Drainage channels with assigned Strahler stream order are extracted within a subbasin and simplified. Drainage density patterns are then estimated with 100-m resolution and subsequently smoothed with a low-pass filter. The extraction process is found to be of better quality in higher slope terrains. Concurrent processing through the high-performance computing environment is shown to facilitate and refine the choice of drainage density extraction parameters and more readily improve extraction procedures than conventional processing.