References

[Alt98]

Micah Altman. Districting Principles and Democratic Representation. PhD thesis, California Institute of Technology, 1998. doi:10.7907/7ZE9-TH19.

[Ans95]

Luc Anselin. Local indicators of spatial association-LISA. Geographical Analysis, 27(2):93–115, Sep 1995. URL: http://dx.doi.org/10.1111/j.1538-4632.1995.tb00338.x, doi:10.1111/j.1538-4632.1995.tb00338.x.

[AR99]

Renato M. Assuncao and Edna A. Reis. A new proposal to adjust Moran's I for population density. Statistics in Medicine, 18(16):2147–2162, Aug 1999. URL: http://dx.doi.org/10.1002/(sici)1097-0258(19990830)18:16<2147::aid-sim179>3.0.co;2-i, doi:10.1002/(sici)1097-0258(19990830)18:16<2147::aid-sim179>3.0.co;2-i.

[BC17]

Melih Basaraner and Sinan Cetinkaya. Performance of shape indices and classification schemes for characterising perceptual shape complexity of building footprints in GIS. International Journal of Geographical Information Science, 31(10):1952–1977, July 2017. doi:10.1080/13658816.2017.1346257.

[BY01]

Yoav Benjamini and Daniel Yekutieli. The control of the false discovery rate in multiple testing under dependency. The Annals of Statistics, 29(4):1165–1188, 2001. URL: http://www.jstor.org/stable/2674075.

[BSN12]

Loeiz Bourdic, Serge Salat, and Caroline Nowacki. Assessing cities: a new system of cross-scale spatial indicators. Building Research & Information, 40(5):592–605, January 2012. doi:10.1080/09613218.2012.703488.

[CO81]

A.D. Cliff and J.K. Ord. Spatial Processes: Models and Applications. Pion, London, 1981.

[dCS06]

Marcia Caldas de Castro and Burton H. Singer. Controlling the false discovery rate: a new application to account for multiple and dependent tests in local statistics of spatial association. Geographical Analysis, 38(2):180–208, April 2006. URL: http://dx.doi.org/10.1111/j.0016-7363.2006.00682.x, doi:10.1111/j.0016-7363.2006.00682.x.

[DLP18]

Juan C. Duque, H. Laniado, and A. Polo. S-maup: statistical test to measure the sensitivity to the modifiable areal unit problem. PLOS ONE, 13(11):1–25, 11 2018. URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0207377, doi:https://doi.org/10.1371/journal.pone.0207377.

[GO10]

Arthur Getis and J. K. Ord. The analysis of spatial association by use of distance statistics. Geographical Analysis, 24(3):189–206, Sep 2010. URL: http://dx.doi.org/10.1111/j.1538-4632.1992.tb00261.x, doi:10.1111/j.1538-4632.1992.tb00261.x.

[HGC81]

L. J. Hubert, R. G. Golledge, and C. M. Costanzo. Generalized procedures for evaluating spatial autocorrelation. Geographical Analysis, 13(3):224–233, Sep 1981. URL: http://dx.doi.org/10.1111/j.1538-4632.1981.tb00731.x, doi:10.1111/j.1538-4632.1981.tb00731.x.

[Lee01]

Sang-Il Lee. Developing a bivariate spatial association measure: an integration of Pearson's r and Moran's I. Journal of Geographical Systems, 3(4):369–385, Dec 2001. URL: https://doi.org/10.1007/s101090100064, doi:10.1007/s101090100064.

[Mac85]

Alan M MacEachren. Compactness of geographic shape: comparison and evaluation of measures. Geografiska Annaler: Series B, Human Geography, 67(1):53–67, 1985.

[OG10]

J. K. Ord and Arthur Getis. Local spatial autocorrelation statistics: distributional issues and an application. Geographical Analysis, 27(4):286–306, Sep 2010. URL: http://dx.doi.org/10.1111/j.1538-4632.1995.tb00912.x, doi:10.1111/j.1538-4632.1995.tb00912.x.

[Rou87]

Peter J Rousseeuw. Silhouettes: a graphical aid to the interpretation and validation of cluster analysis. Journal of computational and applied mathematics, 20:53–65, 1987.

[SOT98]

Robert R Sokal, Oden, Neal L, and Barbara A Thomson. Local spatial autocorrelation in a biological model. Geographical Analysis, 1998.

[WKR19]

Levi J Wolf, Elijah Knaap, and Sergio Rey. Geosilhouettes: geographical measures of cluster fit. Environment and Planning B: Urban Analytics and City Science, 2019. URL: https://doi.org/10.1177%2F2399808319875752.