The Use of the Getis-Ord Index in a Spatio-Temporal Principal Component Analysis of Interdependent Spatial Systems

The Use of the Getis-Ord Index in a Spatio-Temporal Principal Component Analysis of Interdependent Spatial Systems | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Use of the Getis-Ord Index in a Spatio-Temporal Principal Component Analysis of Interdependent Spatial Systems Mirosław Krzyśko, Andrzej Wojtyła, Peter Nijkamp, Waldemar Ratajczak, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6458216/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Apr, 2026 Read the published version in Networks and Spatial Economics → Version 1 posted 11 You are reading this latest preprint version Abstract This paper addresses the multifunctional nature of interconnected spatial systems shaped by a network of adjacent regions. The space-time dynamics of the socio-economic patterns of regions is usually co-determined by spatial and temporal dependences, so that also the resilience trajectories of regions is influenced by spatio-temporal autocorrelations. This study employs a new form of spatio-temporal principal component analysis of the multi-faceted socio-economic profile of spatially dependent regions. It seeks to integrate the global Getis-Ord spatial association index in a multifunctional and multivariate approach for the analysis of space-time dependence patterns of a multiregional system, in which both temporal and spatial variability of socio-economic indicators are incorporated. A novel element of the study is also that both positive and negative spatial autocorrelation phenomena are taken into account. Negative spatial autocorrelation suggests essentially a case of spatial vulnerability. This approach is empirically tested by means of an evidence-based examination of the temporal evolution – and resilience patterns – of distinct socio-economic indicators for 16 interconnected regions in Poland. The socio-economic and geographic mosaic of our spatially dependent network analysis is described by means of choropleth maps which confirm the presence of both positive and negative spatio-temporal autocorrelation among several core socio-economic variables in the Polish space-economy. The analytical approach based on the global Getis-Ord index G enriches the quantitative research tradition on the study of mutually interacting socio-economic characteristics of complex spatial systems. spatio-temporal principal components spatio-temporal data functional data Getis–Ord index resilience vulnerability spatial association Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 14 Apr, 2026 Read the published version in Networks and Spatial Economics → Version 1 posted Editorial decision: Revision requested 04 Sep, 2025 Reviews received at journal 28 Aug, 2025 Reviewers agreed at journal 10 Aug, 2025 Reviews received at journal 22 Jun, 2025 Reviews received at journal 27 May, 2025 Reviewers agreed at journal 14 May, 2025 Reviewers agreed at journal 10 May, 2025 Reviewers invited by journal 24 Apr, 2025 Editor assigned by journal 17 Apr, 2025 Submission checks completed at journal 16 Apr, 2025 First submitted to journal 15 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6458216","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":447599472,"identity":"fcb59dfa-7e73-4292-a41e-b30bbc31383c","order_by":0,"name":"Mirosław Krzyśko","email":"","orcid":"","institution":"University of Kalisz","correspondingAuthor":false,"prefix":"","firstName":"Mirosław","middleName":"","lastName":"Krzyśko","suffix":""},{"id":447599473,"identity":"07abed0d-19f9-4d01-9f3b-12a1eff6f086","order_by":1,"name":"Andrzej Wojtyła","email":"","orcid":"","institution":"University of 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