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1.
Area-based tests for association between spatial patterns 总被引:2,自引:0,他引:2
Edge effects pervade natural systems, and the processes that determine spatial heterogeneity (e.g. physical, geochemical,
biological, ecological factors) occur on diverse spatial scales. Hence, tests for association between spatial patterns should
be unbiased by edge effects and be based on null spatial models that incorporate the spatial heterogeneity characteristic
of real-world systems. This paper develops probabilistic pattern association tests that are appropriate when edge effects
are present, polygon size is heterogeneous, and the number of polygons varies from one classification to another. The tests
are based on the amount of overlap between polygons in each of two partitions. Unweighted and area-weighted versions of the
statistics are developed and verified using scenarios representing both polygon overlap and avoidance at different spatial
scales and for different distributions of polygon sizes. These statistics were applied to Soda Butte Creek, Wyoming, to determine
whether stream microhabitats, such as riffles, pools and glides, can be identified remotely using high spatial resolution
hyperspectral imagery. These new “spatially explicit” techniques provide information and insights that cannot be obtained
from the spectral information alone.
Received 1 June 2001 / Accepted 25 October 2001 相似文献
2.
3.
W. Andrew Marcus 《Journal of Geographical Systems》2002,4(1):113-126
Maximum likelihood supervised classifications with 1-m 128 band hyperspectral data accurately map in-stream habitats in the
Lamar River, Wyoming with producer's accuracies of 91% for pools, 87% for glides, 76% for riffles, and 85% for eddy drop zones.
Coarser resolution 5-m hyperspectral data and 1-m simulated multiband imagery yield lower accuracies that are unacceptable
for inventory and analysis. Both high spatial resolution and hyperspectral coverage are therefore necessary to map microhabitats
in the study area. In many instances, the high spatial resolution hyperspectral (HSRH) imagery appears to map the stream habitats
with greater accuracy than our ground-based surveys, thus challenging classical approaches used for accuracy assessment in
remote sensing.
Received: 9 April 2001 / Accepted: 8 October 2001 相似文献
4.
Francesco Lagona 《Journal of Geographical Systems》2002,4(1):53-68
Markov Random Fields, implemented for the analysis of remote sensing images, capture the natural spatial dependence between
band wavelengths taken at each pixel, through a suitable adjacency relationship between pixels, to be defined a priori. In most cases several adjacency definitions seem viable and a model selection problem arises. A BIC-penalized Pseudo-Likelihood
criterion is suggested which combines good distributional properties and computational feasibility for analysis of high spatial
resolution hyperspectral images. Its performance is compared with that of the BIC-penalized Likelihood criterion for detecting
spatial structures in a high spatial resolution hyperspectral image for the Lamar area in Yellowstone National Park.
Received: 9 March 2001 / Accepted: 2 August 2001 相似文献
5.
Geostatistical incorporation of spatial coordinates into supervised classification of hyperspectral data 总被引:1,自引:0,他引:1
P. Goovaerts 《Journal of Geographical Systems》2002,4(1):99-111
This paper presents a methodology to incorporate both hyperspectral properties and spatial coordinates of pixels in maximum
likelihood classification. Indicator kriging of ground data is used to estimate, for each pixel, the prior probabilities of
occurrence of classes which are then combined with spectral-based probabilities within a Bayesian framework. In the case study
(mapping of in-stream habitats), accounting for spatial coordinates increases the overall producer's accuracy from 85.8% to
93.8%, while the Kappa statistic rises from 0.74 to 0.88. Best results are obtained using only indicator kriging-based probabilities,
with a stunning overall accuracy of 97.2%. Significant improvements are observed for environmentally important units, such
as pools (Kappa: 0.17 to 0.74) and eddy drop zones (Kappa: 0.65 to 0.87). The lack of benefit of using hyperspectral information
in the present study can be explained by the dense network of ground observations and the high spatial continuity of field
classification which might be spurious.
Received: 12 April 2001 / Accepted: 7 September 2001 相似文献
6.
Giuseppe Arbia 《Journal of Geographical Systems》2001,3(3):271-281
Economists have recently devoted an increasing attention to the issue of spatial concentration of economic activities. However,
surprisingly enough, most of the empirical work is still based on the computation of very basic statistical measures in which
the geographical characteristics of data play no role. By making use of a series of empirical examples we show that spatial
concentration consists of two different features that are rarely kept as separate in the statistical analysis: an a-spatial
concept of variability which is invariant to permutations, and the concept of polarization that refers to the geographical
position of observations.
Received: 8 August 2000 / Accepted: 20 June 2001 相似文献
7.
Mark L. Wilson 《Journal of Geographical Systems》2002,4(1):31-42
Many infectious diseases that are emerging or transmitted by arthropod vectors have a strong link to landscape features.
Depending on the source of infection or ecology of the transmitting vector, micro-habitat characteristics at the spatial scale
of square meters or less may be important. Recently, satellite images have been used to classify habitats in an attempt to
understand associations with infectious diseases. Whether high spatial resolution and hyperspectral (HSRH) images can be useful
in studies of such infectious diseases is addressed. The nature of questions that such studies address and the desired accuracy
and precision of answers will determine the utility of HSRH data. Need for such data should be based on the goals of the effort.
Examples of kinds of questions and applications are discussed. The research implications and public health applications may
depend on available analytic tools as well as epidemiological observations.
Received: 30 July 2001 / Accepted: 14 October 2001 相似文献
8.
From fields to objects: A review of geographic boundary analysis 总被引:12,自引:0,他引:12
Geographic boundary analysis is a relatively new approach unfamiliar to many spatial analysts. It is best viewed as a technique
for defining objects – geographic boundaries – on spatial fields, and for evaluating the statistical significance of characteristics
of those boundary objects. This is accomplished using null spatial models representative of the spatial processes expected
in the absence of boundary-generating phenomena. Close ties to the object-field dialectic eminently suit boundary analysis
to GIS data. The majority of existing spatial methods are field-based in that they describe, estimate, or predict how attributes
(variables defining the field) vary through geographic space. Such methods are appropriate for field representations but not
object representations. As the object-field paradigm gains currency in geographic information science, appropriate techniques
for the statistical analysis of objects are required. The methods reviewed in this paper are a promising foundation. Geographic
boundary analysis is clearly a valuable addition to the spatial statistical toolbox.? This paper presents the philosophy of,
and motivations for geographic boundary analysis. It defines commonly used statistics for quantifying boundaries and their
characteristics, as well as simulation procedures for evaluating their significance. We review applications of these techniques,
with the objective of making this promising approach accessible to the GIS-spatial analysis community. We also describe the
implementation of these methods within geographic boundary analysis software: GEM.
Received: 22 March 1999 / Accepted: 7 September 1999 相似文献
9.
Spatial statistical techniques for aggregating point objects extracted from high spatial resolution remotely sensed imagery 总被引:3,自引:0,他引:3
Trisalyn Nelson K. Olaf Niemann Michael A. Wulder 《Journal of Geographical Systems》2002,4(4):423-433
Using a local maximum filter, individual trees were extracted from a 1 m spatial resolution IKONOS image and represented
as points. The spatial pattern of individual trees was determined to represent forest age (a surrogate for forest structure).
Point attributes, based on the spatial pattern of trees, were generated via nearest neighbour statistics and used as the basis
for aggregating points into forest structure units. The forest structure units allowed for the mapping of a forested area
into one of three age categories: young (1–20 years), intermediate (21–120 years), and mature (>120 years). This research
indicates a new approach to image processing, where objects generated from the processing of image data (rather than pixels
or spectral values) are subjected to spatial statistical analysis to estimate an attribute relating an aspect of forest structure.
Received: 22 April 2002 / Accepted: 23 November 2002 相似文献
10.
Kieran P. Donaghy 《Journal of Geographical Systems》2001,3(3):257-270
This paper presents and demonstrates a general approach to solving spatial dynamic models in continuous space and continuous
time that characterize the behaviour of intertemporally and interspatially optimizing agents and estimating from discrete
data the parameters of such models. The approach involves the use of a projection method to solve the models and a quasi-Newton
algorithm to update quasi-FIML parameter estimates.
Received: 26 July 2000 / Accepted: 31 January 2001 相似文献
11.
植被净初级生产力NPP(Net Primary Production)遥感估算与分析,有赖于高时空分辨率的遥感数据,但目前中高分辨率的遥感数据受卫星回访周期及天气的影响,在中国南方地区难以获取连续时间序列的数据,从而影响了高精度的区域植被净初级生产力的遥感估算。为此,提出一种基于多源遥感数据时空融合技术与CASA模型估算高时空分辨率NPP的方法。首先,利用多源遥感数据,即Landsat8 OLI数据与MODIS13Q1数据,采用遥感数据时空融合方法,获得了时间序列的Landsat8 OLI融合数据;然后,基于Landsat8 OLI时空融合数据,并采用CASA模型,以长株潭城市群核心区为例,进行区域植被NPP的遥感估算。研究结果表明,基于时间序列Landsat融合数据估算的30m分辨率的NPP具有良好的空间细节信息,且估算值与实测值的相关系数达0.825,与实测NPP数据保持了较好的一致性。 相似文献
12.
In this paper we detail a multivariate spatial regression model that couples LiDAR, hyperspectral and forest inventory data to predict forest outcome variables at a high spatial resolution. The proposed model is used to analyze forest inventory data collected on the US Forest Service Penobscot Experimental Forest (PEF), ME, USA. In addition to helping meet the regression model's assumptions, results from the PEF analysis suggest that the addition of multivariate spatial random effects improves model fit and predictive ability, compared with two commonly applied modeling approaches. This improvement results from explicitly modeling the covariation among forest outcome variables and spatial dependence among observations through the random effects. Direct application of such multivariate models to even moderately large datasets is often computationally infeasible because of cubic order matrix algorithms involved in estimation. We apply a spatial dimension reduction technique to help overcome this computational hurdle without sacrificing richness in modeling. 相似文献
13.
Misspecifications in interaction model distance decay relations: A spatial structure effect 总被引:1,自引:0,他引:1
M. Tiefelsdorf 《Journal of Geographical Systems》2003,5(1):25-50
An exclusively statistical approach is proposed to address the spatial structure effects of general interaction models. It is shown that the spatial heterogeneity in the estimated region-specific distance decay
parameters may in part be due to the combination of two factors: (a) a functional mis-specification of the global distance
decay relationship; and (b) the heterogeneity in the region-specific conditional distance distributions. A properly specified
global distance decay function allows controlling for these spatially induced biases in the local distance decay parameters.
However, inherent multicollinearities between the set of region specific distance decay parameters and other estimated model
parameters prevent an unambiguous interpretation. A key conclusion is that a proper model specification, in particular, the
specification of the global distance decay relationship, is of paramount importance in interaction modeling and for accessibility
studies.
Received: September 2002 / Accepted: January 2003 相似文献
14.
ABSTRACT Spatial heterogeneity represents a general characteristic of the inequitable distributions of spatial issues. The spatial stratified heterogeneity analysis investigates the heterogeneity among various strata of explanatory variables by comparing the spatial variance within strata and that between strata. The geographical detector model is a widely used technique for spatial stratified heterogeneity analysis. In the model, the spatial data discretization and spatial scale effects are fundamental issues, but they are generally determined by experience and lack accurate quantitative assessment in previous studies. To address this issue, an optimal parameters-based geographical detector (OPGD) model is developed for more accurate spatial analysis. The optimal parameters are explored as the best combination of spatial data discretization method, break number of spatial strata, and spatial scale parameter. In the study, the OPGD model is applied in three example cases with different types of spatial data, including spatial raster data, spatial point or areal statistical data, and spatial line segment data, and an R “GD” package is developed for computation. Results show that the parameter optimization process can further extract geographical characteristics and information contained in spatial explanatory variables in the geographical detector model. The improved model can be flexibly applied in both global and regional spatial analysis for various types of spatial data. Thus, the OPGD model can improve the overall capacity of spatial stratified heterogeneity analysis. The OPGD model and its diverse solutions can contribute to more accurate, flexible, and efficient spatial heterogeneity analysis, such as spatial patterns investigation and spatial factor explorations. 相似文献
15.
Developing a bivariate spatial association measure: An integration of Pearson's r and Moran's I 总被引:1,自引:0,他引:1
Sang-Il Lee 《Journal of Geographical Systems》2001,3(4):369-385
This research is concerned with developing a bivariate spatial association measure or spatial correlation coefficient, which
is intended to capture spatial association among observations in terms of their point-to-point relationships across two spatial
patterns. The need for parameterization of the bivariate spatial dependence is precipitated by the realization that aspatial bivariate association measures, such as Pearson's correlation coefficient,
do not recognize spatial distributional aspects of data sets. This study devises an L statistic by integrating Pearson's r as an aspatial bivariate association measure and Moran's I as a univariate spatial association measure. The concept of a spatial smoothing scalar (SSS) plays a pivotal role in this task.
Received: 07 November 2000 / Accepted: 02 August 2001 相似文献
16.
We present a spatial decision support system for the non-profit sector, designed to assist planning in the area of home-delivered
services such as meals on wheels. Using data collected from existing programs, current and forecasted demographic data, and
a set of algorithmic tools, we provide a system for evaluating current meals on wheels facilities, and for making incremental
facility location decisions that satisfy coverage and equity requirements.
Received: 27 September 2000 / Accepted: 22 March 2001 相似文献
17.
可视化交互空间数据挖掘技术的探讨 总被引:12,自引:2,他引:10
随着地理信息获取技术飞速发展,使得当前存储在空间数据库中的空间数据的深度和广度得到了前所未有的发展,传统的空间统计方法和空间分析方法已经难以有效而迅速地处理和分析它们,如何有效而及时地分析和处理空间数据变得越来越迫切。空间数据挖掘作为上个世纪90年代逐步发展起来的新兴技术,逐渐在研究和实践中显示出它的优势。与此同时,地理可视化技术也逐步走向成熟,二者的结合催生出新型空间数据分析技术———可视化交互空间数据挖掘。本文就该技术的相关问题进行了一些研究探讨。 相似文献
18.
高光谱遥感目标探测主要利用目标和背景的光谱特征差异进行目标识别。一般情况下,影像的空间和光谱分辨率越高,探测效果越好。但多数情况下空间和光谱分辨率难以同时满足需求。针对该问题,本文利用Field Imaging Spectrometer System(FISS)地面高光谱成像仪器,通过在稀疏草地上布设人工绿色目标,研究了目标和背景光谱相似情况下,单一均匀背景下小目标探测问题,提出空间和光谱尺度定量分析方法,得到目标探测适用的空间和光谱尺度。结果表明:(1)利用FISS高光谱仪器进行人工目标探测,所需的空间分辨率约为目标尺寸的2倍以内;(2)当光谱分辨率优于40 nm时,目标和背景的两个主要特征:反射峰的位置和波段趋势差异均可被描述,在原始空间分辨率5倍(0.85 cm)以内,探测精度可以达到0.94以上。由于反射峰间距20 nm,当光谱分辨率低于40 nm时,该特征消失,造成探测精度的下降;(3)当光谱分辨率低于40 nm时,选取目标、背景光谱特征差异较大的波段可提高探测的有效性,在舍弃目标背景相似波段后,探测精度上升,得到本实验的最佳波段组合为红、绿、蓝、黄及红边波段。 相似文献
19.
Assessing representation error in point-based coverage modeling 总被引:2,自引:1,他引:2
Accurately representing geographic space in a digital environment continues to confound and challenge researchers. Carrying
out spatial analysis in a setting where geographic representation is subject to change poses problems to be addressed. In
this paper we examine spatial representation in the context of coverage-based location modeling. A geographic region can be
represented in a variety of ways. We present an evaluation of spatial representation in the location of facilities that provide
coverage oriented services. The analysis shows that the modeling results are sensitive to how spatial demand for service is
represented in a digital environment. We develop an approach for evaluating representational appropriateness. This research
contributes to spatial analysis integrated in geographic information system environment.
Received: 10 January 2001 / Accepted: 8 April 2002 相似文献
20.
Change detection thresholds for remotely sensed images 总被引:4,自引:0,他引:4
Peter A. Rogerson 《Journal of Geographical Systems》2002,4(1):85-97
The detection of change in remotely sensed images is often carried out by designating a threshold to distinguish between
areas of change and areas of no change. The choice of threshold is often arbitrary however. The purpose of this paper is to
offer a statistical framework for the selection of thresholds. The framework accounts for the facts that one carries out multiple
tests of the null hypothesis of no change, when searching for regions of change over an image with a large number of pixels.
Special attention is given to global spatial autocorrelation, which can affect the selection of appropriate threshold values.
Received: 8 March 2001 / Accepted: 12 October 2001 相似文献