Evidence map›Paper›PMID 42143120›Full record

ArticleScientific reports2026

Decoding peri-urban transformation through multi-scale mapping of bidirectional urbanisation.

B Linda Theres, R Selvakumar, Vasu Sathyakumar, S Anandha Kumar, Shankar Karuppannan, Keerat Kumar Gupta

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

B Linda TheresCentre of Data for Public Good, Indian Institute of Science, Bangalore, India.
R SelvakumarSchool of Civil Engineering, SASTRA Deemed to be University, Thanjavur, Tamil Nadu, India. selvakumar@civil.sastra.edu.
Vasu SathyakumarSchool of Civil Engineering, SASTRA Deemed to be University, Thanjavur, Tamil Nadu, India.
S Anandha KumarDepartment of Civil Engineering, Aditya University, Surampalem, 533437, Andhra Pradesh, India.
Shankar KaruppannanDepartment of Applied Geology, College of Applied Natural Science, Adama Science and Technology University, P.O. Box 1888, Adama, Ethiopia. shankar.karuppannan@astu.edu.et.
Keerat Kumar GuptaDepartment of Civil Engineering, Graphic Era (Deemed to be University, Clement Town, Dehradun, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapid urbanisation in emerging economies is reshaping the geography of human settlement at an unprecedented pace, placing acute pressure on the principles of sustainable development. In India, these transformations are particularly pronounced in non-metropolitan regions, where expansion routinely surpasses statutory (de jure) administrative boundaries. Yet conventional analyses of urban sprawl fail to capture these processes' complex, bidirectional nature, providing an incomplete account of the functional and spatial extent of contemporary urban growth. Here, we present a novel, data-driven geospatial framework for delineating dynamic urban expansion boundaries and quantifying bidirectional growth patterns. We apply this methodology to Salem and its surrounding towns in Tamil Nadu, India, spanning the period 2001-2020. Our three-tiered approach combines: (i) buffer analysis to identify the spatial threshold of built-up expansion; (ii) centroid shift analysis to track macro-scale directional change; and (iii) landscape metrics to measure micro-scale fragmentation and aggregation. Over two decades, Salem's built-up area increased by ~ 170%, generating a compact urban core encircled by a fragmented, outwardly expanding periphery. Neighbouring towns, including Omalur, Sankari, Rasipuram, and Vazhapadi, exhibited marked bidirectional expansion towards Salem, underscoring the emergence of strongly interconnected regional growth corridors. By redefining urban boundaries through quantitative spatial metrics, our framework enables early detection of emergent urban linkages and sprawl intensities. These findings not only advance the methodological frontier of urban spatial analysis, but also provide actionable intelligence for planners and policymakers seeking to manage expansion sustainably and equitably in rapidly transforming city-regions.

Indexed as

Centroid shiftDirectional studyFragmentationLandscape metricsSpatial arrangementUrbanisation

Identifiers

PMID42143120
PMCPMC13377198

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.