Evidence map›Paper›PMID 41826715›Full record

ArticleEnvironmental monitoring and assessment2026

Improved remote sensing ecological index for monitoring urban sustainability: 100 resilient cities vs non-resilient cities in South Asia.

Jayanta Biswas, Niloy Biswas

Abstract read
In one paragraph

Article in Environmental monitoring and assessment, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Jayanta BiswasDepartment of Earth Sciences, University of Memphis, Memphis, TN, USA, 38152. jayantakurp17@gmail.com.ORCID http://orcid.org/0000-0003-2899-2980
Niloy BiswasUrban and Rural Planning Discipline, Khulna University, Khulna, 9208, Bangladesh.ORCID http://orcid.org/0009-0000-8787-8470

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study assesses ecological change in two 100 resilient cities (100RC) (Pune, Surat) and two non-100RC cities (Chattogram, Nagpur) in South Asia using an improved remote sensing ecological index (RSEI). The enhanced model incorporates six indicators composite vegetation index (CVI), wetness, normalized difference build-up and bare soil index (NDBSI), impervious surface index (ISI), urban index (UI), and land surface temperature (LST)-with entropy-based weighting and a moving window approach to overcome traditional PCA limitations. The results reveal apparent differences between 100RC and non-100RC cities. Non-100RC cities exhibited high volatility, characterized by sharp ecological declines, partial recoveries, and subsequent collapses. In contrast, 100RC cities followed steadier but persistent downward trajectories: Surat exhibited a monotonic decline, while Pune improved until 2022 before declining in 2024. Hotspot analysis revealed that cold spots expanded dynamically in non-100RC cities, whereas they spread gradually in 100RC cities. Moran's I confirmed strong spatial clustering (0.89-0.97) across all cities. A two-way ANOVA revealed significant group, year, and interaction effects (p < 0.001). These findings suggest that resilience frameworks reduce ecological instability but are insufficient to halt structural degradation. Strengthening urban resilience requires more rigorous policy enforcement, continuous monitoring, and ecological restoration to achieve sustainable ecological outcomes.

Indexed as

Conservation of Natural ResourcesEnvironmental MonitoringRemote Sensing TechnologyAsia, SouthernCitiesEcosystem100 resilient citiesRemote sensing ecological index (RSEI)South AsiaUrban resilienceUrban sustainability

Identifiers

PMID41826715
PMCPMC12987812

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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.