Territorial typologies and environmental pressures: Evidence from Moldova’s districts using Principal Component Analysis and Fuzzy C-Means

Authors

  • Daniela Luminița Constantin Research Centre for Macroeconomic and Regional Forecasting, Faculty of Administration and Public Management, Bucharest University of Economic Studies https://orcid.org/0000-0002-6839-7396
  • Ionuț Nica Department of Economic Informatics and Cybernetics, Faculty of Economic Cybernetics, Statistics and Informatics, Bucharest University of Economic Studies https://orcid.org/0000-0003-2118-3654
  • Camelia Delcea Department of Economic Informatics and Cybernetics, Faculty of Economic Cybernetics, Statistics and Informatics, Bucharest University of Economic Studies https://orcid.org/0000-0003-3589-1969
  • Bianca Cibu Department of Economic Informatics and Cybernetics, Faculty of Economic Cybernetics, Statistics and Informatics, Bucharest University of Economic Studies https://orcid.org/0009-0003-8597-7514
  • Ștefan Ionescu Department of Economic Informatics and Cybernetics, Faculty of Economic Cybernetics, Statistics and Informatics, Bucharest University of Economic Studies https://orcid.org/0000-0002-0469-3022

DOI:

https://doi.org/10.17649/TET.40.3.3735

Keywords:

territorial development, environmental pressures, principal component analysis, fuzzy c-means, place-based policy, GIS, Republic of Moldova

Abstract

Territorial development in the Republic of Moldova is spatially uneven, but district typologies based on absolute volumes risk reproducing differences in population size rather than identifying substantive territorial profiles. This study constructs a size-adjusted district-level typology linking socio-economic development intensity, infrastructure provision, environmental and service-related pressure, and environmental expenditure intensity. The analysis uses the latest available mixed-year cross-section data covering 34 territorial units, while Chișinău is examined separately because of its structurally exceptional profile. Population is used as a denominator and contextual variable rather than as an active clustering indicator. Absolute measures are converted into per-capita or rate-based indicators, positively skewed variables are logarithmically transformed, and all active indicators are standardized. Principal Component Analysis (PCA) is used to summarize the correlation structure, while Fuzzy C-Means (FCM) is applied to the first three descriptive component scores. A two-cluster resolution is reported as a binary benchmark, whereas three clusters are retained as the preferred substantive typology after jointly considering fuzzy validity, membership clarity, interpretability and robustness. The results distinguish between (i) development pressure intensive districts with higher environmental expenditure intensity; (ii) intermediate development districts with lower observed pressure; and (iii) peripheral lower-intensity districts with lower environmental expenditure. GIS mapping and fuzzy membership diagnostics show that several districts occupy transitional positions rather than belonging unambiguously to a single territorial type. The findings provide a size-adjusted account of Moldova’sinternal core–periphery structure and support differentiated, place-based territorial and environmental interventions. The mixed reference years and the proxy character of waste collection and environmental expenditure as indicators are explicitly acknowledged as limitations.

Author Biographies

Daniela Luminița Constantin, Research Centre for Macroeconomic and Regional Forecasting, Faculty of Administration and Public Management, Bucharest University of Economic Studies

professor emeritus

Ionuț Nica, Department of Economic Informatics and Cybernetics, Faculty of Economic Cybernetics, Statistics and Informatics, Bucharest University of Economic Studies

assistant professor

Camelia Delcea, Department of Economic Informatics and Cybernetics, Faculty of Economic Cybernetics, Statistics and Informatics, Bucharest University of Economic Studies

professor

Bianca Cibu, Department of Economic Informatics and Cybernetics, Faculty of Economic Cybernetics, Statistics and Informatics, Bucharest University of Economic Studies

candidate

Ștefan Ionescu, Department of Economic Informatics and Cybernetics, Faculty of Economic Cybernetics, Statistics and Informatics, Bucharest University of Economic Studies

candidate

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Published

2026-11-04

How to Cite

Constantin, D. L., Nica, I., Delcea, C., Cibu, B., & Ionescu, Ștefan. (2026). Territorial typologies and environmental pressures: Evidence from Moldova’s districts using Principal Component Analysis and Fuzzy C-Means: . Tér és Társadalom, 40(3), 254–292. https://doi.org/10.17649/TET.40.3.3735