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Peter Foley 《International journal of geographical information science》2013,27(4):633-661
Geographically weighted spatial statistical methods are a family of spatial statistical methods developed to address the presence of non-stationarity in geographical processes, the so-called spatial heterogeneity. While these methods have recently become popular for analysis of spatial data, one of their characteristics is that they produce outputs that in themselves form complex multi-dimensional spatial data sets. Interpretation of these outputs is therefore not easy, but is of high importance, since spatial and non-spatial patterns in the results of these methods contain clues to causes of underlying non-stationarity. In this article, we focus on one of the geographically weighted methods, the geographically weighted discriminant analysis (GWDA), which is a method for prediction and analysis of categorical spatial data. It is an extension of linear discriminant analysis (LDA) that allows the relationship between the predictor variables and the categories to vary spatially. This produces a very complex data set of GWDA results, which include on top of the already complex discriminant analysis outputs (e.g. classifications and posterior probabilities) also spatially varying outputs (e.g. classification function parameters). In this article, we suggest using geovisual analytics to visualise results from LDA and GWDA to facilitate comparison between the global and local method results. For this, we develop a bespoke visual methodology that allows us to examine the performance of global and local classification method in terms of quality of classification. Furthermore, we are also interested in identifying the presence (or absence) of non-stationarity through comparison of the outputs of both methods. We do this in two ways. First, we visually explore spatial autocorrelation in both LDA and GWDA misclassifications. Second, we focus on relationships between the classification result and the independent variables and how they vary over space. We describe our visual analytic system for exploration of LDA and GWDA outputs and demonstrate our approach on a case study using a data set linking election results with a selection of socio-economic variables. 相似文献
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Patterns of plant diversity were examined across 24 ironstone ranges in arid south western Australia. The high levels of beta diversity displayed between ranges primarily resulted from high turnover of perennial species and was not influenced by the lower species richness on the more arid ranges. The variance in composition of the vegetation across the ranges was evenly distributed between the broad spatial pattern and environmental factors measuring climate gradients, local site variables and soil chemistry. In contrast broad scale spatial and climatic gradients were most important in explaining the variance in perennial species richness. Ranges along the boundary of the Arid Zone appear to have acted as refugia during the climatic cycles of the Tertiary with several hotspots of species endemism and taxa with distributions centered on these ranges. On the more arid ranges these specialist ironstone taxa are largely absent. The variation in richness of these specialists taxa was strongly influenced by patterns in soil chemistry in addition to the broad scale spatial and climate gradients. The concentration of the ironstone specialist taxa is largely coincidental with the most prospective areas for iron ore mining and this will provide considerable challenges in conserving these unique ecosystems. 相似文献
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产业地理集中、产业集聚与产业集群:测量与辨识 总被引：29，自引：4，他引：25
本文综述了产业地理集中、产业地理集聚以及产业集群的测量与辨识方法。传统的测量 产业地理集中方法包括集中系数、变差系数、赫芬代尔系数、赫希曼- 赫芬代尔系数、信息熵、锡尔 系数以及基尼系数等, 这些系数测量产业总体地理集中程度, 没有考虑企业规模分布对产业地理 集中的影响。基于企业区位选择模型, 经济学家发展了测量产业地理集聚的指数, 控制产业内企 业规模分布对产业地理集中的影响。无论地理集中指数还是地理集聚系数都以行政单元为基础, 仅描述单一空间尺度上的产业区位模式。Ripley 的K 函数通过计算某个企业一定距离内的邻居 企业个数来测量产业的地理集聚程度, 可同时反映产业在不同空间尺度的集聚程度。相互联系的 一群企业在地理空间上的集聚构成了产业集群, 产业集群的辨识不仅要测量产业间联系, 也要考 虑产业地理临近性。区位商和标准化区位商法、空间相关与产业联系法、因子分析和聚类分析等 多元统计方法以及基于投入产出关系的图谱分析方法等可以用来作为辨识区域产业集群手段。 相似文献
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Kathleen C. Parker 《自然地理学》2013,34(4):320-333
Breeding bird censuses from 132 homogeneous sites representing a variety of habitats throughout North America are analyzed and a bird species diversity model based on environmental characteristics and sampling procedures is presented. Bivariate regression models relate the number of bird species detected in a site (NSPECIES) to plot size, latitude, and the number of bird pairs encountered during censusing. These models consistently overestimate NSPECIES in desert shrublands, grasslands, tundra, and scrub and underestimate NSPECIES in forested habitats, which indicates that the effects of the environmental and methodological variables on NSPECIES vary with respect to habitat. The expansion method of regression analysis is used to generate a multivariate model that accounts for this spatial variation in the influence of the independent variables on NSPECIES. With the exception of temperate wetlands, which have the third highest mean value for NSPECIES of nine habitat groups, forested sites and woodlands have higher mean NSPECIES values than more open habitats. Use of the expansion method to account for spatial variation in the effects exerted by independent variables introduces a geographically realistic element often lacking in broad-scale models. (Key words: avian diversity, sampling intensity, multiple regression analysis, vegetation structure, habitat types.) 相似文献
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自然地理要素空间插值的几个问题 总被引：77，自引：8，他引：69
资源管理、灾害管理、生态环境治理以及全球变化研究的需要强化了部分自然地理要素空间插值研究的重要性。这些要素空间插值的核心是建立充分逼近要素空间分布特征的函数方程。对于给定的区域与要素样本值 ,插值函数可以有多种模型形式。各类模型的精度受其理论基础、模型算法、时空尺度效应、样本数据属性等因素的综合影响。通过对国际主要插值研究成果进行分析 ,文章认为各类模型插值精度的差异缘于模型对插值要素空间变异性与空间相关性的反映 ,具体应用中 ,只有对已知样本数据进行变异性与相关性分析才能选出适当的插值方法。 相似文献
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Changshan Wu 《Applied geography (Sevenoaks, England)》2012,32(2):746-756
Understanding housing submarket structure is of crucial importance to both public and private agencies. It can also help current and future homeowners make informed decisions on their residential choices. Current research on submarket focuses on comparative analyses of different classification techniques. Few studies, however, have examined the function of spatial contiguity on housing submarket classification. To address this issue, this paper developed a spatially constrained data-driven submarket classification methodology to obtain spatially integrated housing market segments. Specifically, a data-driven model based on principal component analysis and cluster analysis was developed for delineating housing submarkets. Within the model, a number of location attributes were used for principal component analysis, and the geographic locations of houses were also incorporated in the cluster analysis. The performance of this method was compared with other unconstrained data-driven techniques and a priori classifications using three measurements: substitutability, spatial integrity, and similarity. Results indicate that spatially contiguous submarkets can be obtained without compromising housing hedonic model accuracy and attribute homogeneity. 相似文献
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Abstract factor analyses were performed on databases consisting of simulated samples from aqueousequilbria.The program COMPLEX was used to generate equilibrium species in a system of three reactantmetals and five reactant bases.Reactant concentrations and pH were drawn from random-normaldistributions so that sample data vectors comprised a multivariate log-normal distribution of equilibriumconcentrations.In addition,sample groups were created containing different distributions for pH andreactant concentrations.Equilibrium species were shown to contain variance contributed by change in pH among samples aswell as change in reactant concentrations.Factor modelling revealed the qualitative relationships amongthe species and how the relationships change with pH.Factors also revealed those reactants containingvariance in the data matrix.In some cases,reactant variance obscured relationships between pH and theequilibrium species.Since factor modelling of a simulated data matrix revealed the expected chemical equilibriuminteractions,a potentially powerful tool exists for investigating the effects of outliers and error. 相似文献
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Cale A. C. Gushulak Kathleen R. Laird Joseph R. Bennett Brian F. Cumming 《Journal of Paleolimnology》2017,58(2):231-241
There has been much debate over the relative importance of environmental selection and spatial variation on community organization in microorganisms. To assess the importance of environmental or spatial variables in diatom species assemblages in Gall Lake, northwest Ontario, 41 surface-sediment samples were collected in a two-dimensional gridded pattern along and across depth contours. A depth-constrained cluster analysis separated the diatom flora into three communities: a shallow-water benthic zone (B1); a deeper-water benthic zone (B2); and a planktonic zone (P). Redundancy analysis (RDA) confirmed that water depth was a major predictor of variation in the flora. Further RDAs and variation partitioning using orthogonal polynomials and Moran’s eigenvector maps showed that spatial location had minimal effect on the diatom assemblages. Principal components analysis grouped the diatom flora not only by assemblage, but also by water depth, regardless of two-dimensional spatial separation, suggesting the importance of the environmental gradients associated with lake depth. These findings indicate that environment is a more important explanatory variable than spatial variables for diatoms within lakes, suggesting dispersal plays a limited role in intra-lake diatom distributions. 相似文献
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气候变化和人类活动通过改变物种生境而影响物种多样性。小白额雁是长江流域中下游的一种具有较高生态价值的食草型濒危候鸟,受气候变化和人类活动威胁。本文以小白额雁为代表性物种,定量分析了气候变化对长江流域中下游候鸟潜在生境及适宜性空间分布格局的影响。采用Maxent模型模拟了当前情景和全球环流模型(GCMs)气候场景下小白额雁潜在生境及其适宜性分布。研究结果表明,小白额雁分布特征与其栖息地周边植物分布呈显著相关关系;运用Maxent模型模拟小白额雁六种主要食源植物的分布特征,并将其结果作为环境变量,将显著改善小白额雁潜在生境及其适宜性模型的模拟性能;在两种典型浓度情景(RCP 2.6和RCP8.5)下,2070年小白额雁潜在生境适宜性面积将下降。为应对气候变化对小白额雁的影响,应采取更加合理的管理措施和保护政策,包括调整保护区的大小、形状和用途。 相似文献
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遥感图像纹理信息提取方法综述 总被引：1，自引：0，他引：1
纹理是遥感图像的重要特征，它提示了图像中辐射亮度值空间变化的重要信息。要利用图像空间信息提高分类精度，合理而有效地度量纹理至关重要。目前遥感图像纹理信息提取方法主要有：统计描述法、小波变换法、分维分形法和地统计学4类。分别就各种方法的优缺点、适用领域和应用情况进行了阐述，最后展望了遥感图像纹理信息提取方法的发展方向和研究热点。 相似文献
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Na Zhang Hongyan Zhang 《International journal of geographical information science》2013,27(9):1525-1543
Scale variance is highly sensitive to multi-scale patterns of variables, which is advantageous in identifying spatial hierarchy and characteristic scale(s). However, the significance of peak(s) in scale variance cannot be statistically tested, and different spatial patterns may be obtained when different zoning systems are used to calculate scale variance. To address these two problems, this study compared the scale levels with peaks in scale variance and the scale levels at which there were breaks in the nature of spatial autocorrelation as identified by shifts in Moran's I scalogram. The estimates for three simulated landscapes showed that accordance between scale levels identified employing the two methods can be used to evaluate the significance of peaks in scale variance and choose a more reasonable zoning system. The approach of scale variance analysis coupled with Moran's I scalogram was also applied to the Xilin River Basin of Inner Mongolia, China. The most vital characteristic scale (64 × 32 km) identified for the growing-season net ecosystem productivity (NEP) of the basin was validated by other spatial pattern analysis methods such as semi-variogram, Moran's I correlogram, and wavelet variance analyses, and the directionality of the chosen zoning systems was found to be similar to the orientation of actual dominant vegetation type patches. The results demonstrate that Moran's I scalogram can be used to improve the interpretation of the results of scale variance analysis and increase the reliability of scale variance analysis for landscapes having a repetitive patch pattern or gradient variation and that the proposed approach is suitable for identifying the hierarchy and the characteristic scales of patterns or processes. In summary, this study used a simple approach to solve two problems in scale variance analysis, thereby improving the methodology and enhancing the theoretical basis of multi-scale analysis. 相似文献
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Gentile Francesco Ficetola Anna Bonardi Caspar A. Mücher Niels L.M. Gilissen Emilio Padoa-Schioppa 《International journal of geographical information science》2014,28(8):1723-1739
At the local spatial scale, land-use variables are often employed as predictors for ecological niche models (ENMs). Remote sensing can provide additional synoptic information describing vegetation structure in detail. However, there is limited knowledge on which environmental variables and how many of them should be used to calibrate ENMs. We used an information-theoretic approach to compare the performance of ENMs using different sets of predictors: (1) a full set of land-cover variables (seven, obtained from the LGN6 Dutch National Land Use Database); (2) a reduced set of land-cover variables (three); (3) remotely sensed laser data optimized to measure vegetation structure and canopy height (LiDAR, light detection and ranging); and (4) combinations of land cover and LiDAR. ENMs were built for a set of bird species in the Veluwe Natura 2000 site (the Netherlands); for each species, 26–214 records were available from standardized monitoring. Models were built using MaxEnt, and the best performing models were identified using the Akaike’s information criterion corrected for small sample size (AICc). For 78% of the bird species analysed, LiDAR data were included in the best AICc model. The model including LiDAR only was the best performing one in most cases, followed by the model including a reduced set of land-use variables. Models including many land-use variables tended to have limited support. The number of variables included in the best model increased for species with more presence records. For all species with 33 records or less, the best model included LiDAR only. Models with many land-use variables were only selected for species with >150 records. Test area under the curve (AUC) scores ranged between 0.72 and 0.92. Remote sensing data can thus provide regional information useful for modelling at the local and landscape scale, particularly when presence records are limited. ENMs can be optimized through the selection of the number and identity of environmental predictors. Few variables can be sufficient if presence records are limited in number. Synoptic remote sensing data provide a good measure of vegetation structure and may allow a better representation of the available habitat, being extremely useful in this case. Conversely, a larger number of predictors, including land-use variables, can be useful if a large number of presence records are available. 相似文献
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China’s Qinghai-Tibetan Plateau (QTP) is an important area for bird conservation, with many endemic and Threatened species. Colonial burrowing mammals play an important role in structuring bird communities in arid grasslands around the world. On the QTP, the plateau pika Ocho tona curzoniae builds colonies which provide a dense source of resources for many bird species. However, pikas are regarded as a pest by local pastoralists, and they are the target of a population reduction campaign which could have a significant impact on the bird communities. We surveyed bird communities at Gansu Yanchiwan National Nature Reserve to investigate the differences in community structure between sites with pika colonies (on colony) and sites without them (off colony), and between pika colonies which had been poisoned and those which had not. Using non-metric multidimensional scaling (NMDS) combined with permutational multivariate analysis of variance (PERMANOVA) and Wilcoxon rank-sum tests, we found that there was no significant difference in bird community composition or abundance between the poisoned and untreated colonies. However, there was a very large and statistically significant difference in bird community structures between on- and off-colony sites. Only horned lark Eremophila alpestris was consistently observed at sites without pika colonies, while ten bird species were observed on colonies. Six species were significantly more abundant on colony than off. While we could not claim that the poisoning campaign at Yanchiwan is altering bird communities, the presence of pika colonies seems to be an indispensable resource for the resident birds. 相似文献
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塔里木河中游天然植被的数量分类与排序研究 总被引：13，自引：4，他引：13
通过塔里木河中下游天然植被带的调查研究，应用数量分类(TWINSPAN)和排序(CCA)方法，对塔里木河中下游地区天然植被类型进行了划分，并探讨了决定该地区天然植物群落类型的主要环境因子。该地区天然植被可分为4个植被型组，4个植被型，6种植被亚型，9个群系，15个群丛。通过对8个环境因子的CCA排序分析，结果表明制约塔里木河中下游天然植被组成和结构的主导环境因子为地下水位、地下水矿化度、地下水酸碱度。通过CCA二维排序图将16种植物对干旱、盐碱的适应性划分5类型。21个样地在CCA二维排序图上可聚集成9个植物群落类群，即胡杨(Populus euphratica)群落、铃铛刺(Halimodendron halodendron)群落、库尔勒沙拐枣(Calligonum Kuerlese)群落、多枝柽柳(Tamarix ramosissima)群落、黑果枸杞(Lycium ruthenicum)群落、盐穗木(Halostashys caspica)群落、花花柴(Karelinia caspica)群落、疏叶骆驼剂(Alhagi sparsifolia)群落、罗布麻(Apocynum venetum)群落，与TWINSPAN结果中的群系分类单位一致。CCA连续排序与TWINSPAN分类结果吻合较好。9种植物群落类型中，能耐受最大盐胁迫的为盐穗木群落，能耐受最大干旱胁迫的为铃铛刺群落，能耐受最大地下水碱胁迫的为黑果枸杞群落。 相似文献
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Given species' vulnerability to climate change, land use change, and habitat loss, it is pertinent to examine how the distribution of a particular species is related to those factors. We assessed the use of climate, habitat, and topography data for modeling the distributions of 14 central European wetland birds, and compared the relative importance of these factors among bird groups with differing latitudinal distributions in Europe. We used the Third Atlas of Breeding Birds in the Czech Republic as a source of species distribution data. Variables were derived from Corine Land Cover, WorldClim, and Shuttle Radar Topography Mission (SRTM) data. Hierarchical partitioning and multiple logistic models identified climatic, topographical, and habitat predictors as important determinants of distribution for each of the species under study. However, the relative contributions of particular variables differed among the species. Climatic, topographical, and habitat factor groups also differed in their importance to latitudinal species groups. Our results indicated that wetland birds with range margins close to the Czech Republic were potentially limited by two different factors: climate conditions impact the southerly distributed species and the availability of suitable habitat affects the northerly distributed species. The accuracy of the study models varied from fair to high (the area under curve values was 0.60–0.89) and revealed negative correlations with the relative occurrence area. In this study, we propose that any difference in model performance is more attributable to data characteristics than to a species' geographical characteristics. 相似文献
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《Urban geography》2013,34(3):246-257
This study identifies generational divisions among urban areas, investigates traditional regional divisions of Frostbelt/Sunbelt, and formally tests whether these divisions can be identified using contemporary socioeconomic variables. Contemporary urban areas are influenced by initial technological and cultural patterns. Cities formed in the 19th century are different than those formed in the 20th century. Urban generations, therefore, are defined as periods in history when particular urban areas first experienced substantial growth. Technological and cultural patterns also vary from region to region. The urban areas, therefore, also are classified regionally based on Gober's (1984) definition of Frostbelt and Sunbelt. The various classifications are all examined using analysis of covariance and discriminant analysis. The analysis of covariance demonstrates that generation and region significantly affected the study variables individually. In turn, the results of the discriminant analysis demonstrate that it is possible to discriminate generationally and regionally based on the study variables as a group. 相似文献
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Niche theory predicts that coexisting species with similar trophic requirements should demonstrate resource partitioning, particularly where resources are scarce. Conversely, this is not expected between species that do not share primary resources. This study analyses the patterns of spatial coexistence and habitat selection, on two spatial scales, of three species of semidesert regions in Morocco: the Black-bellied Sandgrouse (Pterocles orientalis), the Stone Curlew (Burhinus oedicnemus) and the Cream-coloured Courser (Cursorius cursor). Co-occurrence analysis results point to between-species segregation on a macrohabitat scale. Hotelling's T test of the species-presence data showed a pattern of macrohabitat selection that diverged from habitat availability for the three species with differences among them. Both the classification tree and the pattern of microhabitat selection obtained by model averaging showed scant overlap between the Sandgrouse and the Courser, suggesting habitat partitioning between them on a fine scale. Our results confirm spatial segregation of the three species, especially between species with different trophic strategies: the Sandgrouse versus the Stone Curlew and the Courser. The latter two species were best segregated on a microhabitat scale, supporting the conclusions that macro- and microhabitat selection are major factors in bird community configuration in arid ecosystems and contributing to reduce potential competition. 相似文献
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TIAN Li ZHANG Yangjian Claus HOLZAPFEL HUANG Ke CHEN Ning TAO Jian ZHU Juntao 《资源与生态学报(英文版)》2018,9(5):526-537
Environmental and Geo-spatial factors have long been considered as crucial determinants of species composition and distributions. However, quantifying the relative contributions of these factors for the alpine ecosystems is lacking. The Tibetan Plateau has a unique ecological environment and vegetation types. Our objectives are to quantify the spatial distributions of plant communities on the Northern Tibetan Alpine grasslands and to explore the relationships between vegetation composition, Geo-spatial factors and environmental factors. We established 63 field plots along a 1200-km gradient on the Northern Tibetan Plateau Alpine Grassland and employed the two-way indicator species analysis (TWINSPAN) and the detrended canonical correspondence analysis (DCCA). Fourteen communities of alpine grassland were identifiable along the transect and consisted of three vegetation types: Alpine meadow, Alpine steppe, and desert steppe. Vegetation composition and spatial distribution appeared to be largely determined by mean annual precipitation and less influenced by temperature. A large fraction (73.5%) of the variation in vegetation distribution was explained by environmental variables along this transect, somewhat less by Geo-spatial factors (56.3%). The environmental and Geo-spatial factors explained 29.6% and 12.3% of the total variation, respectively, while their interaction explained 43.9%. Our findings provide strong empirical evidence for explaining biological and environmental synergetic relationships in Northern Tibet. 相似文献