https://muse.jhu.edu/journal/66 Project MUSE®: Latest articles in Geographical Analysis. daily 1 2026-05-12T00:00:00-05:00 text/html en-US Vol. 34 (2002) - vol. 36 (2004) Latest Articles: Geographical Analysis TWO Project MUSE® Geographical Analysis 1538-4632 0016-7363 Latest articles in Geographical Analysis. Feed provided by Project MUSE® https://muse.jhu.edu/article/173522 <p></p> For various sorts of analytical models in geography, there is often a question of how much detail to build into the models. The question is particularly acute for location models, since the underlying problem may involve determining the location of one or more new facilities to serve a large population. For example, if demand is generated by all private residences in a major metropolitan area, there can be hundreds of thousands of demand points. Instead of modeling such a problem with all of its detail, an alternative is to first do demand point aggregation, a process that reduces the level of detail in the model by replacing demand points by aggregate demand points. However, it is well known that this aggregation ... <a href="https://muse.jhu.edu/article/173527">Read More</a> Project MUSE® https://muse.jhu.edu/ 2026-05-12T00:00:00-05:00 https://muse.jhu.edu/journal/66/image/coversmall Aggregation Decomposition and Aggregation Guidelines for a Class of Minimax and Covering Location Models 2004-09-29 text/html en-US Aggregation Decomposition and Aggregation Guidelines for a Class of Minimax and Covering Location Models 2004-09-29 2004 TWO Project MUSE® 143137 2026-05-12T00:00:00-05:00 2004-09-29 https://muse.jhu.edu/article/173523 <p></p> January ............................................................ 1-86April.............................................................. 87-196July.............................................................. 197-298October ...................................................... 299-385Aggregation Decomposition and Aggregation Guidelines for a Class of Minimax and Covering Location Models (36:4, pp. 332-349)Akella, Mohan (36:2, pp. 177-194)Aldstadt, Jared (36:2, pp. 90-104)Analysis of Qualitative Similarity between Surfaces (36:3, pp. 217-233)Anisotropic Variance Functions in Geographically Weighted Regression Models (36:4, pp. 299-314)Arentze, Theo (36:1, pp. 85-86)A Bayesian Approach to Modeling Binary Data: ... <a href="https://muse.jhu.edu/article/173527">Read More</a> Project MUSE® https://muse.jhu.edu/ 2026-05-12T00:00:00-05:00 https://muse.jhu.edu/journal/66/image/coversmall Annual Index: Volume 36, (2004) 2004-09-29 text/html en-US Annual Index: Volume 36, (2004) 2004-09-29 2004 TWO Project MUSE® 8341 2026-05-12T00:00:00-05:00 2004-09-29 https://muse.jhu.edu/article/173524 <p></p> Although they have long since ceased to attract attention as research topics in and of themselves, factorial ecologies continue to provide indicators of neighborhood characteristics that can be employed in studies of relationships between individual behavior and local milieux. In particular, the utility of factor scores as indicators of neighborhood composition for ecological analyses has been realized on many occasions in recent decades. Morenoff and Sampson (1997), for example, used a factorial ecology research design to identify four separate dimensions of neighborhood differences in Chicago in their study of the changing geography of crime there&#x2014;one example of the output of their large program of research in ... <a href="https://muse.jhu.edu/article/173527">Read More</a> Project MUSE® https://muse.jhu.edu/ 2026-05-12T00:00:00-05:00 https://muse.jhu.edu/journal/66/image/coversmall Scale, Factor Analyses, and Neighborhood Effects 2004-09-29 text/html en-US Scale, Factor Analyses, and Neighborhood Effects 2004-09-29 2004 TWO Project MUSE® 130551 2026-05-12T00:00:00-05:00 2004-09-29 https://muse.jhu.edu/article/173525 <p></p> Most standard methods of statistical analysis used in the social and environmental sciences are built upon the basic assumptions of serial independence, homogeneity, and isotropy. A majority of these methods were originally developed within fields for which said assumptions were reasonable, or at a time when they were needed to make the problems tractable (Hepple 1998). A consequence of this historic development is that over time these basic assumptions were transmitted to, and in some cases unconsciously adopted by, different fields for which statistical methods became important tools of analysis. The assumption of independence, however, has long been recognized to be at odds with certain fundamental premises in a ... <a href="https://muse.jhu.edu/article/173527">Read More</a> Project MUSE® https://muse.jhu.edu/ 2026-05-12T00:00:00-05:00 https://muse.jhu.edu/journal/66/image/coversmall Anisotropic Variance Functions in Geographically Weighted Regression Models 2004-09-29 text/html en-US Anisotropic Variance Functions in Geographically Weighted Regression Models 2004-09-29 2004 TWO Project MUSE® 96888 2026-05-12T00:00:00-05:00 2004-09-29 https://muse.jhu.edu/article/173526 <p></p> A fundamental debate in biogeography and ecology is whether, or the extent to which, communities and ecosystems follow a developmental pathway leading toward a stable, steady-state equilibrium condition. The absence of, deviation from, or variation in such monotonic developmental pathways is likewise a focus of debate, particularly on the roles and relative importance of external disturbances, intrinsic complex dynamics, and historical or path dependencies. The purpose of this paper is not to provide a comprehensive review or critique of these debates. Rather, the goal is to attempt to redirect the focus to observable manifestations of (non)equilbrium, (in)stability, and other phenomena in ecosystems. Rather than ... <a href="https://muse.jhu.edu/article/173527">Read More</a> Project MUSE® https://muse.jhu.edu/ 2026-05-12T00:00:00-05:00 https://muse.jhu.edu/journal/66/image/coversmall Divergence, Sensitivity, and Nonequilibrium in Ecosystems 2004-09-29 text/html en-US Divergence, Sensitivity, and Nonequilibrium in Ecosystems 2004-09-29 2004 TWO Project MUSE® 150208 2026-05-12T00:00:00-05:00 2004-09-29 https://muse.jhu.edu/article/173527 <p></p> There currently exist a variety of tests for the presence of attraction and repulsion effects between spatial point populations, most notably those involving either nearest-neighbor or cell-count statistics (as reviewed for example in Cressie 1993, section 8.6). The advantage of nearest-neighbor approaches is that it is often possible to obtain exact (or at least asymptotic) distributions for certain test statistics under the null hypothesis of statistically independent populations. Most notable here is the approach of Diggle and Cox (1981), who showed that a powerful nearest-neighbor test of independence between two spatial point patterns could be constructed using Kendall&#39;s rank correlation coefficient. But by ... <a href="https://muse.jhu.edu/article/173527">Read More</a> Project MUSE® https://muse.jhu.edu/ 2026-05-12T00:00:00-05:00 https://muse.jhu.edu/journal/66/image/coversmall A Scale-Sensitive Test of Attraction and Repulsion Between Spatial Point Patterns 2004-09-29 text/html en-US A Scale-Sensitive Test of Attraction and Repulsion Between Spatial Point Patterns 2004-09-29 2004 TWO Project MUSE® 91407 2026-05-12T00:00:00-05:00 2004-09-29