%% This BibTeX bibliography file was created using BibDesk.
%% https://bibdesk.sourceforge.io/

%% Created for weikang at 2019-03-28 22:46:35 -0700


%% Saved with string encoding Unicode (UTF-8)

@Article{Lee2001,
author="Lee, Sang-Il",
title="Developing a bivariate spatial association measure:  An integration of {Pearson}'s r and {Moran's I}",
journal="Journal of Geographical Systems",
year="2001",
month="Dec",
day="01",
volume="3",
number="4",
pages="369--385",
abstract="{\enspace}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.",
issn="1435-5930",
doi="10.1007/s101090100064",
url="https://doi.org/10.1007/s101090100064"
}


@article{Benjamini:2001,
	Abstract = {Benjamini and Hochberg suggest that the false discovery rate may be the appropriate error rate to control in many applied multiple testing problems. A simple procedure was given there as an FDR controlling procedure for independent test statistics and was shown to be much more powerful than comparable procedures which control the traditional familywise error rate. We prove that this same procedure also controls the false discovery rate when the test statistics have positive regression dependency on each of the test statistics corresponding to the true null hypotheses. This condition for positive dependency is general enough to cover many problems of practical interest, including the comparisons of many treatments with a single control, multivariate normal test statistics with positive correlation matrix and multivariate t. Furthermore, the test statistics may be discrete, and the tested hypotheses composite without posing special difficulties. For all other forms of dependency, a simple conservative modification of the procedure controls the false discovery rate. Thus the range of problems for which a procedure with proven FDR control can be offered is greatly increased.},
	Author = {Yoav Benjamini and Daniel Yekutieli},
	Date-Added = {2019-03-28 22:46:12 -0700},
	Date-Modified = {2019-03-28 22:46:28 -0700},
	Issn = {00905364},
	Journal = {The Annals of Statistics},
	Number = {4},
	Pages = {1165--1188},
	Publisher = {Institute of Mathematical Statistics},
	Title = {The Control of the False Discovery Rate in Multiple Testing under Dependency},
	Url = {http://www.jstor.org/stable/2674075},
	Volume = {29},
	Year = {2001},
	Bdsk-File-1 = { },
	Bdsk-Url-1 = {http://www.jstor.org/stable/2674075}}

@article{Castro:2006tz,
	Author = {de Castro, Marcia Caldas and Singer, Burton H.},
	Citeulike-Article-Id = {647229},
	Date-Added = {2019-03-28 22:46:02 -0700},
	Date-Modified = {2019-03-28 22:46:02 -0700},
	Doi = {10.1111/j.0016-7363.2006.00682.x},
	Issn = {0016-7363},
	Journal = {Geographical Analysis},
	Keywords = {local statistics, multiple comparisons, false discovery rate},
	Month = {April},
	Number = {2},
	Pages = {180-208},
	Publisher = {Blackwell Publishing},
	Title = {Controlling the False Discovery Rate: A New Application to Account for Multiple and Dependent Tests in Local Statistics of Spatial Association},
	Url = {http://dx.doi.org/10.1111/j.0016-7363.2006.00682.x},
	Volume = {38},
	Year = {2006},
	Bdsk-File-1 = { },
	Bdsk-Url-1 = {http://dx.doi.org/10.1111/j.0016-7363.2006.00682.x}}

@article{Anselin95,
	Author = {Anselin, Luc},
	Doi = {10.1111/j.1538-4632.1995.tb00338.x},
	Issn = {0016-7363},
	Journal = {Geographical Analysis},
	Month = {Sep},
	Number = 2,
	Pages = {93--115},
	Publisher = {Wiley},
	Title = {Local Indicators of Spatial Association-{LISA}},
	Url = {http://dx.doi.org/10.1111/j.1538-4632.1995.tb00338.x},
	Volume = 27,
	Year = 1995,
	Bdsk-Url-1 = {http://dx.doi.org/10.1111/j.1538-4632.1995.tb00338.x}}

@article{Assuncao1999,
	Author = {Assuncao, Renato M. and Reis, Edna A.},
	Doi = {10.1002/(sici)1097-0258(19990830)18:16<2147::aid-sim179>3.0.co;2-i},
	Issn = {1097-0258},
	Journal = {Statistics in Medicine},
	Month = {Aug},
	Number = 16,
	Pages = {2147--2162},
	Publisher = {Wiley},
	Title = {A new proposal to adjust {Moran's I} for population density},
	Url = {http://dx.doi.org/10.1002/(sici)1097-0258(19990830)18:16<2147::aid-sim179>3.0.co;2-i},
	Volume = 18,
	Year = 1999,
	Bdsk-Url-1 = {http://dx.doi.org/10.1002/(sici)1097-0258(19990830)18:16%3C2147::aid-sim179%3E3.0.co;2-i}}

@book{cliff81,
	Address = {London},
	Author = {Cliff, A.D. and Ord, J.K.},
	Publisher = {Pion},
	Title = {Spatial Processes: Models and Applications},
	Year = {1981}}



@article{duque18,
    author = {Duque, Juan C. AND Laniado, H. AND Polo, A.},
    journal = {PLOS ONE},
    publisher = {Public Library of Science},
    title = {S-maup: Statistical Test to Measure the Sensitivity to the Modifiable Areal Unit Problem},
    year = {2018},
    month = {11},
    volume = {13},
    url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0207377},
    pages = {1-25},
    abstract = {This work presents a nonparametric statistical test,  S-maup, to measure the sensitivity of a spatially intensive variable to the effects of the Modifiable Areal Unit Problem (MAUP). To the best of our knowledge,  S-maup is the first statistic of its type and focuses on determining how much the distribution of the variable, at its highest level of spatial disaggregation, will change when it is spatially aggregated. Through a computational experiment, we obtain the basis for the design of the statistical test under the null hypothesis of non-sensitivity to MAUP. We performed an exhaustive simulation study for approaching the empirical distribution of the statistical test, obtaining its critical values, and computing its power and size. The results indicate that, in general, both the statistical size and power improve with increasing sample size. Finally, for illustrative purposes, an empirical application is made using the Mincer equation in South Africa, where starting from 206 municipalities, the  S-maup statistic is used to find the maximum level of spatial aggregation that avoids the negative consequences of the MAUP.},
    number = {11},
    doi = {https://doi.org/10.1371/journal.pone.0207377}
}

@Article{Getis_2010,
  author       = {Getis, Arthur and Ord, J. K.},
  title        = {The Analysis of Spatial Association by Use of Distance
                  Statistics},
  year         = 2010,
  volume       = 24,
  number       = 3,
  month        = {Sep},
  pages        = {189–206},
  issn         = {0016-7363},
  doi          = {10.1111/j.1538-4632.1992.tb00261.x},
  url          = {http://dx.doi.org/10.1111/j.1538-4632.1992.tb00261.x},
  journal      = {Geographical Analysis},
  publisher    = {Wiley}
}


@article{Ord_2010,
	Author = {Ord, J. K. and Getis, Arthur},
	Doi = {10.1111/j.1538-4632.1995.tb00912.x},
	Issn = {0016-7363},
	Journal = {Geographical Analysis},
	Month = {Sep},
	Number = 4,
	Pages = {286--306},
	Publisher = {Wiley},
	Title = {Local Spatial Autocorrelation Statistics: Distributional Issues and an Application},
	Url = {http://dx.doi.org/10.1111/j.1538-4632.1995.tb00912.x},
	Volume = 27,
	Year = 2010,
	Bdsk-Url-1 = {http://dx.doi.org/10.1111/j.1538-4632.1995.tb00912.x}}

@article{Hubert_1981,
	Author = {Hubert, L. J. and Golledge, R. G. and Costanzo, C. M.},
	Doi = {10.1111/j.1538-4632.1981.tb00731.x},
	Issn = {0016-7363},
	Journal = {Geographical Analysis},
	Month = {Sep},
	Number = 3,
	Pages = {224--233},
	Publisher = {Wiley},
	Title = {Generalized Procedures for Evaluating Spatial Autocorrelation},
	Url = {http://dx.doi.org/10.1111/j.1538-4632.1981.tb00731.x},
	Volume = 13,
	Year = 1981,
	Bdsk-Url-1 = {http://dx.doi.org/10.1111/j.1538-4632.1981.tb00731.x}}

@article{Rousseeuw1987,
  title = {Silhouettes: A Graphical Aid to the Interpretation and Validation of Cluster Analysis},
  volume = {20},
  journal = {Journal of computational and applied mathematics},
  author = {Rousseeuw, Peter J},
  year = {1987},
  pages = {53--65}
}

@Article{lunnwinbugs,
author="Lunn, David J.
and Thomas, Andrew
and Best, Nicky
and Spiegelhalter, David",
title="WinBUGS - A {Bayesian} modelling framework: Concepts, structure, and extensibility",
journal="Statistics and Computing",
year="2000",
month="Oct",
day="01",
volume="10",
number="4",
pages="325--337",
abstract="WinBUGS is a fully extensible modular framework for constructing and analysing Bayesian full probability models. Models may be specified either textually via the BUGS language or pictorially using a graphical interface called DoodleBUGS. WinBUGS processes the model specification and constructs an object-oriented representation of the model. The software offers a user-interface, based on dialogue boxes and menu commands, through which the model may then be analysed using Markov chain Monte Carlo techniques. In this paper we discuss how and why various modern computing concepts, such as object-orientation and run-time linking, feature in the software's design. We also discuss how the framework may be extended. It is possible to write specific applications that form an apparently seamless interface with WinBUGS for users with specialized requirements. It is also possible to interface with WinBUGS at a lower level by incorporating new object types that may be used by WinBUGS without knowledge of the modules in which they are implemented. Neither of these types of extension require access to, or even recompilation of, the WinBUGS source-code.",
issn="1573-1375",
doi="10.1023/A:1008929526011",
url="https://doi.org/10.1023/A:1008929526011"
}

@article{wolf2019geosilhouettes,
  title={Geosilhouettes: Geographical measures of cluster fit},
  author={Wolf, Levi J and Knaap, Elijah and Rey, Sergio},
  journal={Environment and Planning B: Urban Analytics and City Science},
  url="https://doi.org/10.1177%2F2399808319875752",
  year={2019},
  publisher={SAGE Publications Sage UK: London, England}
}

@article{sokal1998local,
	title={Local spatial autocorrelation in a biological model},
	author={Sokal, Robert R and Oden, Neal L, and Thomson, Barbara A},
	journal={Geographical Analysis},
	year={1998},
	volume=30,
	issue=4
}

@article{nowosad2018v,
    title={Spatial association between regionalizations using the information-theoretical {V}-measure},
    journal={International Journal of Geographic Information Science},
    volume={32},
    issue={12},
    year={2018},
    pages={2386--2401},
    doi={10.1080/13658816.2018.1511794}
    }

@article{basaraner2017,
  title = {Performance of Shape Indices and Classification Schemes for Characterising Perceptual Shape Complexity of Building Footprints in {{GIS}}},
  author = {Basaraner, Melih and Cetinkaya, Sinan},
  year = {2017},
  month = jul,
  volume = {31},
  pages = {1952--1977},
  doi = {10.1080/13658816.2017.1346257},
  journal = {International Journal of Geographical Information Science},
  number = {10}
}

@article{maceachren1985compactness,
  title={Compactness of geographic shape: Comparison and evaluation of measures},
  author={MacEachren, Alan M},
  journal={Geografiska Annaler: Series B, Human Geography},
  volume={67},
  number={1},
  pages={53--67},
  year={1985},
  publisher={Taylor \& Francis}
}

@article{gil2012,
  title = {On the {{Discovery}} of {{Urban Typologies}}: {{Data Mining}} the {{Multi}}-Dimensional {{Character}} of {{Neighbourhoods}}},
  author = {Gil, Jorge and Montenegro, Nuno and Beir{\~a}o, J N and Duarte, J P},
  year = {2012},
  month = jan,
  volume = {16},
  pages = {27--40},
  journal = {Urban Morphology},
  number = {1}
}

@article{bourdic2012,
  title = {Assessing Cities: A New System of Cross-Scale Spatial Indicators},
  author = {Bourdic, Loeiz and Salat, Serge and Nowacki, Caroline},
  year = {2012},
  month = jan,
  volume = {40},
  pages = {592--605},
  doi = {10.1080/09613218.2012.703488},
  journal = {Building Research \& Information},
  number = {5}
}

@article{schirmer2015,
  title = {A Multiscale Classification of Urban Morphology},
  author = {Schirmer, Patrick Michael and Axhausen, Kay W},
  year = {2015},
  month = may,
  volume = {9},
  pages = {101--130},
  doi = {10.5198/jtlu.2015.667},
  journal = {Journal of Transport and Land Use},
  number = {1}
}

@phdthesis{altman1998Districting,
  title = {Districting {{Principles}} and {{Democratic Representation}}},
  author = {Altman, Micah},
  year = {1998},
  school = {California Institute of Technology},
  doi = {10.7907/7ZE9-TH19}
}

@article{ab_gl_vm2020joue,
	title = {Building(s and) cities: Delineating urban areas with a machine learning algorithm},
	journal = {Journal of Urban Economics},
	volume = {125},
	pages = {103217},
	year = {2021},
	note = {Delineation of Urban Areas},
	issn = {0094-1190},
	doi = {10.1016/j.jue.2019.103217},
	author={Arribas-Bel, Daniel and Garcia-L{\'o}pez, M-{\`A} and Viladecans-Marsal, Elisabet},
}

@article{wolf2024confounded,
    title={{Confounded Local Inference:} Extending Local Moran Statistics to Handle Confounding},
    author={Wolf, Levi John},
    year={2024},
    number={in press},
    volume={in press},
    pages={0-0},
    journal={Annals of the American Association of Geographers}
}

@article{AnselinLi2019,
  title={{Operational Local Join Count Statistics for Cluster Detection}},
  author={Anselin, Luc and Li, Xun},
  journal={Journal of Geographical Systems},
  volume={21},
  number={2},
  pages={189--210},
  year={2019},
  publisher={Springer}
}

@article{LiEtAl2013,
  title = {An Efficient Measure of Compactness for Two-Dimensional Shapes and Its Application in Regionalization Problems},
  author = {Li, Wenwen and Goodchild, Michael F. and Church, Richard},
  year = {2013},
  month = jun,
  journal = {International Journal of Geographical Information Science},
  volume = {27},
  number = {6},
  pages = {1227--1250},
  issn = {1365-8816},
  doi = {10.1080/13658816.2012.752093},
  abstract = {A measure of shape compactness is a numerical quantity representing the degree to which a shape is compact. Ways to provide an accurate measure have been given great attention due to its application in a broad range of GIS problems, such as detecting clustering patterns from remote-sensing images, understanding urban sprawl, and redrawing electoral districts to avoid gerrymandering. In this article, we propose an effective and efficient approach to computing shape compactness based on the moment of inertia (MI), a well-known concept in physics. The mathematical framework and the computer implementation for both raster and vector models are discussed in detail. In addition to computing compactness for a single shape, we propose a computational method that is capable of calculating the variations in compactness as a shape grows or shrinks, which is a typical application found in regionalization problems. We conducted a number of experiments that demonstrate the superiority of the MI over the popular isoperimetric quotient approach in terms of (1) computational efficiency; (2) tolerance of positional uncertainty and irregular boundaries; (3) ability to handle shapes with holes and multiple parts; and (4) applicability and efficacy in districting/zonation/regionalization problems.},
  keywords = {automated zoning procedure,compactness,districting,geographic Information Science,moment of inertia,pattern recognition,raster data modelling,regionalization,shape analysis,shape index,vector data modelling},
}
