共查询到20条相似文献，搜索用时 31 毫秒
1.
《The Professional geographer》2013,65(4):607-623
The concept of spatial scale is fundamental to geography, as are the problems of integrating data obtained at different scales. The availability of GIS has provided an appropriate environment to re-scale data prior to subsequent integration, but few tools with which to implement the re-scaling. This sparsity of appropriate tools arises primarily because the nature of the spatial variation of interest is often poorly understood and, specifically, the patterns of spatial dependence and error are unknown. Spatial dependence can be represented and modelled using geostatistical approaches providing a basis for the subsequent re-scaling of spatial data (e.g., via spatial interpolation). Geostatistical techniques can also be used to model the effects of re-scaling data through the geostatistical operation of regularization. Regularization provides a means by which to re-scale the statistics and functions that describe the data rather than the data themselves. These topics are reviewed in this paper and the importance of the spatial scale problems that remain is emphasized. 相似文献
2.
Modeling Short-Term Spatial and Temporal Variability of Groundwater Level Using Geostatistics and GIS 总被引：1，自引：0，他引：1
Deepesh Machiwal Amit Mishra Madan K. Jha Arun Sharma S. S. Sisodia 《Natural Resources Research》2012,21(1):117-136
Continuous depletion of groundwater levels from deliberate and uncontrolled exploitation of groundwater resources lead to
the severe problems in arid and semi-arid hard-rock regions of the world. Geostatistics and geographic information system
(GIS) have been proved as successful tools for efficient planning and management of the groundwater resources. The present
study demonstrated applicability of geostatistics and GIS to understand spatial and temporal behavior of groundwater levels
in a semi-arid hard-rock aquifer of Western India. Monthly groundwater levels of 50 sites in the study area for 36-month period
(May 2006 to June 2009; excluding 3 months) were analyzed to find spatial autocorrelation and variances in the groundwater
levels. Experimental variogram of the observed groundwater levels was computed at 750-m lag distance interval and the four
most-widely used geostatistical models were fitted to the experimental variogram. The best-fit geostatistical model was selected
by using two goodness-of-fit criteria, i.e., root mean square error (RMSE) and correlation coefficient (r). Then spatial maps of the groundwater levels were prepared through kriging technique by means of the best-fit geostatistical
model. Results of two spatial statistics (Geary’s C and Moran’s I) indicated a strong positive autocorrelation in the groundwater levels within 3-km lag distance. It is emphasized that the
spatial statistics are promising tools for geostatistical modeling, which help choose appropriate values of model parameters.
Nugget-sill ratio (<0.25) revealed that the groundwater levels have strong spatial dependence in the area. The statistical
indicators (RMSE and r) suggested that any of the three geostatistical models, i.e., spherical, circular, and exponential, can be selected as the
best-fit model for reliable and accurate spatial interpolation. However, exponential model is used as the best-fit model in
the present study. Selection of the exponential model as the best-fit was further supported by very high values of coefficient
of determination (r
2 ranging from 0.927 to 0.994). Spatial distribution maps of groundwater levels indicated that the groundwater levels are strongly
affected by surface topography and the presence of surface water bodies in the study area. Temporal pattern of the groundwater
levels is mainly controlled by the rainy-season recharge and amount of groundwater extraction. Furthermore, it was found that
the kriging technique is helpful in identifying critical locations over the study area where water saving and groundwater
augmentation techniques need to be implemented to protect depleting groundwater resources. 相似文献
3.
Geostatistics applies statistics to quantitatively describe geological sites and assess the uncertainty due to incomplete sampling. Strong assumptions are required regarding the location independence of statistical parameters to construct numerical models with geostatistical tools. Most geological data exhibit large-scale deterministic trends together with short-scale variations. Such location dependence violates the common geostatistical assumption of stationarity. The trend-like deterministic features should be modeled prior to conventional geostatistical prediction and accounted for in subsequent geostatistical calculations. The challenge of using a trend in geostatistical simulation algorithms for the continuous variable is the subject of this paper. A stepwise conditional transformation with a Gaussian mixture model is considered to provide a stable and artifact-free numerical model. The complex features of the regionalized variable in the presence of a trend are removed in the forward transformation and restored in the back transformation. The Gaussian mixture model provides a seamless bin-free approach to transformation. Data from a copper deposit were used as an example. These data show an apparent trend unsuitable for conventional geostatistical algorithms. The result shows that the proposed algorithm leads to improved geostatistical models. 相似文献
4.
空间尺度转换数据精度评价的准则和方法 总被引：2，自引：0，他引：2
空间尺度问题是地理学、生态学和水文学等多个学科的基础科学问题之一。空间数据尺度转换是将数据从一个空间尺度转换到另一个空间尺度的过程, 它是尺度科学研究的重要内容之一。对尺度转换后的成果数据深入分析, 提炼尺度转换成果数据精度评价的原则、指标以及模型方法, 这对正确选择和应用尺度转换成果数据具有重要意义。在详细评述尺度和尺度转换研究概念、内容和主要进展的基础上, 本文主要从数据处理、地图学角度出发, 提出了空间数据尺度转换精度评价的3 项基本准则, 即保持构成信息守恒、保持面积信息守恒、保持区域空间格局和形态信息守恒。继而据此将当前常见的指标进行了梳理和归并;根据上述准则和指标, 结合GIS 方法、常规统计方法、地统计方法等, 给出了上述评价指标的计算模型及其应用方法和典型案例。最后指出, 在实际应用中需结合研究目标, 针对性选择尺度转换效应函数, 通过开展模型模拟和对比分析, 最终确定合适的尺度转换方法。 相似文献
5.
《The Journal of geography》2012,111(5):206-213
Abstract The concept of scale is fundamental to geography, yet the definitions for “scale” and related spatial terms can be confusing to those working in other spatial science disciplines. This is particularly true in the emerging multidisciplinary world of integrated remote sensing and geographic information systems, or IGIS's, where data of different types and at various spatial and temporal scales are combined to support complex space-time data analyses. Without a basic lexicon of accepted scale terms, working within an IGIS can breed confusion in the interpretation of data and the models that result from an IGIS construct. This paper provides some terminologies of scale that can be used as a framework for a multidisciplinary lexicon of accepted scaling terms and describes their relationships to an IGIS. It also illustrates how scaling terms can be potentially misunder stood when applied to geographic techniques that are used in disciplines related to geography. 相似文献
6.
There are 71 surface sediment samples collected from the eastern Beibu Gulf. The moment parameters (i.e. mean size, sorting and skewness) were obtained after applying grain size analysis. The geostatistical analysis was then applied to study the spatial autocorrelation for these parameters; while range, a parameter in the semivariogram that meters the scale of spatial autocorrelation, was estimated. The results indicated that the range for sorting coefficient was physically meaningful. The trend vectors calculated from grain size trend analysis model were consistent with the annual ocean circulation patterns and sediment transport rates according to previous studies. Therefore the range derived from the semivariogram of mean size can be used as the characteristic distance in the grain size trend analysis, which may remove the bias caused by the traditional way of basing on experiences or testing methods to get the characteristic distance. Hence the results from geostatistical analysis can also offer useful information for the determination of sediment sampling density in the future field work. 相似文献
7.
土地利用/覆盖变化空间变异特征与遥感影像空间分辨率的选取——以北京地区为例 总被引：1，自引：0，他引：1
遥感数据为土地利用/覆盖变化提供了海量数据来源,如何选择合适空间分辨率的遥感影像进行特定地区的土地利用/覆盖变化研究,成为土地利用/覆盖变化研究的一个重要内容。地统计学方法已经广泛应用与遥感图像处理以及土地覆盖分类研究中,但应用于土地利用/覆盖变化的研究还比较缺乏。北京地区为研究区,运用遥感和地统计分析方法对该区土地利用/覆盖变化的空间结构的变异特征和合理的遥感影像数据源的选取问题做了初步探讨。研究表明地统计学方法能够揭示土地利用/覆盖变化的空间变异特征,有助于选择有效的遥感影像数据进行不同地区的土地利用/覆盖变化分析。 相似文献
8.
地统计法在粒径趋势分析中的应用:以北部湾东部为例(英文) 总被引：4，自引：1，他引：3
There are 71 surface sediment samples collected from the eastern Beibu Gulf. The moment parameters (i.e. mean size, sorting
and skewness) were obtained after applying grain size analysis. The geostatistical analysis was then applied to study the
spatial autocorrelation for these parameters; while range, a parameter in the semivariogram that meters the scale of spatial
autocorrelation, was estimated. The results indicated that the range for sorting coefficient was physically meaningful. The
trend vectors calculated from grain size trend analysis model were consistent with the annual ocean circulation patterns and
sediment transport rates according to previous studies. Therefore the range derived from the semivariogram of mean size can
be used as the characteristic distance in the grain size trend analysis, which may remove the bias caused by the traditional
way of basing on experiences or testing methods to get the characteristic distance. Hence the results from geostatistical
analysis can also offer useful information for the determination of sediment sampling density in the future field work. 相似文献
9.
10.
黄河三角洲多尺度土壤盐分的空间分异 总被引：20，自引：5，他引：15
本文利用多尺度采样数据,探索了两个深度土壤盐分的空间分异,分析了不同尺度、深度土壤盐分的变异系数和空间相关性(结构方差与基台值之比)的变化,揭示了形成这种空间变异的地貌因素,最后利用普通克立格(ordinary kriging)方法对土壤盐分的分布进行了估测。分析发现,研究区土壤盐分的空间变异具有三个尺度。随着采样间隔的增加和区域的扩大,盐分分布空间相关性增强,且下层比上层具有更高的空间相关性。地貌因素(微地貌类型、坡度和高程)均具有较高的空间相关性,当与地貌因素关系密切时,该尺度及深度的土壤盐分空间相关性就大;反之,则小,这时可能主要受具有较小空间相关性其他因子的影响(如人为活动)。最后对合理的土壤采样提出了建议。 相似文献
11.
地理尺度转换若干问题的初步探讨 总被引：69，自引：18，他引：51
大量研究证实,地理学研究对象格局与过程及其时空特征均是尺度依存的,随着研究工作的不断深入,尺度问题越来越展示出其重要性。针对地理学各个分支学科都不同程度存在诸如概念模糊、转换模式不统一、转换效果评价缺乏客观标准等与尺度相关问题,本文对一些有关尺度转换的议题进行了探讨。在评述了尺度及其转换研究的地理学意义后,着重阐述了地理学尺度研究理论框架的内容和对象,提出了地理科学中需要解决的10个关键尺度问题,并给出了初步的解决方案。 相似文献
12.
我国落叶松林生产力的空间变化特征 总被引：1，自引：1，他引：1
落叶松林在我国有着广泛的分布。其空间差异也比较大。采用地统计学方法对我国落叶松林生产力的空间特征进行了分析。结果表明。落叶松种群和群落地理替代作用明显；落叶松林生产力空间异质性较大。其变化与空间尺度密切相关；地理位置、海拔高度等是影响落叶松林生产力的重要因素；在天然落叶松林的管理和保护以及人工落叶松林的发展上应考虑其空间特征。 相似文献
13.
Fine scale disaster response and recovery data suitable for spatial analysis are still relatively rare. This is unfortunate as insight into spatial patterns of recovery could be invaluable in predicting the reestablishment of homes, streets and neighborhoods. The purpose of this paper is to show how fine scale geographic data can be collected in near real-time for the intermediate phase between response and recovery. These data will initially be used to assess the degree of damage (with relation to the Enhanced F scale) while also establishing a baseline for subsequent recovery monitoring. A spatial video system is used to collect data from the post-disaster landscape of Tuscaloosa which was hit by a large tornado in April 2011. This video, once processed, can be viewed within a Geographic Information System which combines street-level images with exact location. These data can be used to support ongoing recovery efforts, while also archiving a dataset suitable for the spatial analysis of the changing post-disaster landscape. 相似文献
14.
Drumond David Alvarenga Rolo Roberto Mentzingen Costa João Felipe Coimbra Leite 《Natural Resources Research》2019,28(1):145-152
Experimental variograms are crucial for most geostatistical studies. In kriging, for example, the variography has a direct influence on the interpolation weights. Despite the great importance of variogram estimators in predicting geostatistical features, they are commonly influenced by outliers in the dataset. The effect of some randomly spatially distributed outliers can mask the pattern of the experimental variogram and produce a destructuration effect, implying that the true data spatial continuity cannot be reproduced. In this paper, an algorithm to detect and remove the effect of outliers in experimental variograms using the Mahalanobis distance is proposed. An example of the algorithm’s application is presented, showing that the developed technique is able to satisfactorily detect and remove outliers from a variogram.
相似文献15.
土地变化科学中的尺度问题与解决途径 总被引：10，自引：1，他引：9
尺度问题是土地变化科学中的关键问题。总结国内外近10年来土地变化研究中尺度问题的进展表明:土地变化研究中的尺度问题多集中于数据处理、格局与过程的表征、驱动力的影响、模型运用、生态环境效应以及土地政策与可持续管理等方面。尺度问题主要产生于地理现象的异质性、地理系统的等级性、响应与反馈的非线性、干扰因素的影响及主观认识的局限等。土地变化中尺度问题研究的一般途径为尺度选择-尺度分析-尺度综合;尺度选择时应该以问题为指向,数据为基础,选择适宜的尺度;尺度分析中需要从更大尺度和更小尺度同时开展分析,找出重要的变化动态,防止信息的遗漏或夸大;尺度综合是认识全球与地方关系的纽带,可将其分为尺度上推和尺度下推,在尺度综合中方法是主导,目标是寻找各尺度之间的"连通性"。模型有助于深刻理解土地利用系统动态,发展嵌套式模型是目前尺度综合研究中的重要内容。 相似文献
16.
17.
《Urban geography》2013,34(7):635-647
Traditional measures of segregation, such as the index of dissimilarity, have been criticized as aspatial in nature. Spatial measures of segregation have been proposed, but they are difficult to use. Based on the idea that segregation implies a spatial separation of ethnic groups, the degree of spatial correlation among groups can reflect the level of segregation. This paper suggests that several geostatistical measures, especially the standard deviational ellipse, are effective tools for capturing the spatial characteristics of a population group. By comparing the ellipses of different groups, measures of segregation can be derived. The paper demonstrates this approach to measuring segregation by way of both a simulation and a case study. [Key words: spatial segregation, geostatistics, deviational ellipses, spatial correspondence/correlation.] 相似文献
18.
Elizabeth A. Wentz Donna J. Peuquet Sharolyn Anderson 《International journal of geographical information science》2013,27(9):1309-1325
The availability of spatial data on an unprecedented scale as well as advancements in analytical and visualization techniques gives researchers the opportunity to study complex problems over large urban and regional areas. Nevertheless, few individual data sets exist that provide both the requisite spatial and/or temporal observational frequency to truly facilitate detailed investigations. Some data are collected frequently over time but only at a few geographic locations (e.g., weather stations). Similarly, other data are collected with a high level of spatial resolution but not at regular or frequent time intervals (e.g., satellite data). The purpose of this article is to present an interpolation approach that leverages the relative temporal richness of one data set with the relative spatial richness of another to fill in the gaps. Because different interpolation techniques are more appropriate than others for specific types of data, we propose a space–time interpolation approach whereby two interpolation methods – one for the temporal and one for the spatial dimension – are used in tandem to increase the accuracy results. We call our ensemble approach the space–time interpolation environment (STIE). The primary steps within this environment include a spatial interpolation processor, a temporal interpolation processor, and a calibration processor, which enforces phenomenon-related behavioral constraints. The specific interpolation techniques used within the STIE can be chosen on the basis of suitability for the data and application at hand. In this article, we first describe STIE conceptually including the data input requirements, output structure, details of the primary steps, and the mechanism for coordinating the data within those steps. We then describe a case study focusing on urban land cover in Phoenix, Arizona, using our working implementation. Our empirical results show that our approach increased the accuracy for estimating urban land cover better than a single interpolation technique. 相似文献
19.
山东省人口空间分布格局的多尺度分析 总被引：4，自引：3，他引：1
人口空间分布具有一定的尺度依赖性,从不同尺度上对人口空间分布格局进行分析,可以更确切、真实地揭示人口的空间分布规律,为制定区域发展规划、灾害评价、环境保护等提供科学依据。本文以山东省为研究区,运用空间自相关方法和统计相关分析方法,比较市级、县级、1 km三个尺度上人口分布的空间自相关性及其与环境—经济因子的统计相关性,试图探讨不同尺度下人口的空间分布模式及影响(指示)因素,从不同尺度揭示人口的空间分布格局特征。结果表明:①从不同尺度对人口的空间分布格局进行分析,可以得到从宏观到微观不同详细程度的信息。从市级尺度分析,可以得到山东省整体的人口空间分布特征;从县级尺度分析,可以得到山东省各市内部的人口空间分布特征;从1 km尺度分析,可以得到山东省各县内部的人口空间分布特征。②不同尺度上,人口的空间分布格局特征不同。市级和县级尺度上,人口分布受环境—经济因子的影响表现出与一些因子显著相关,而受空间集聚的作用较小;1 km尺度上,人口分布与环境—经济因子的相关性较小,而主要受空间集聚的作用,在县内部,人口往往集中分布于某一区域,呈现出典型的集聚分布模式。 相似文献
20.
空间自相关的可塑性面积单元问题效应 总被引：13，自引：3，他引：10
可塑性面积单元问题(modifiable areal unit problem,MAUP) 效应是对空间数据分析结果产生不确定性影响的主要原因之一,在空间自相关分析中也不例外.本文分别利用网格模拟数据和中国人均GDP实例数据为数据源,以全局Moran's I 系数来探究空间自相关统计中的MAUP效应,分析结果表明,变量的空间自相关程度依赖于空间的粒度大小与单元的划分方法,但空间单元的变化与自相关性并不存在某种函数关系.因此,在进行空间自相关研究时必须选择合适的地理单元的粒度大小和分区.最后本文给出一种基于地统计内插方法来降低MAUP对空间自相关分析影响. 相似文献