Evidence map›Paper›PMID 40119233›Full record

ArticleEnvironmental science and pollution research international2025

Artificial intelligence to evaluate the impact of urban green and blue spaces on chlorophyll-a concentrations.

Panchali U Fonseka, Lakindu Mampitiya, Namal Rathnayake, Hongsheng Zhang, Chaminda Samarasuriya, Ranjith Premasiri, Upaka Rathnayake

Abstract read
In one paragraph

Article in Environmental science and pollution research international, 2025. 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

7 authors.

Panchali U FonsekaDepartment of Earth Resource Engineering, Faculty of the Engineering, University of Moratuwa, Katubedda, Moratuwa, 10400, Sri Lanka.
Lakindu MampitiyaWater Resources Management and Soft Computing Research Laboratory, Athurugiriya, Millennium City, 10150, Sri Lanka.
Namal RathnayakeDepartment of Civil Engineering, Faculty of Engineering, The University of Tokyo, 1 Chome-1-1 Yayoi, Bunkyo City, Tokyo, 113-8656, Japan.
Hongsheng ZhangDepartment of Geography, Centennial Campus, The University of Hong Kong, Pokfulam Road, Hong Kong, China.
Chaminda SamarasuriyaDepartment of Earth Resource Engineering, Faculty of the Engineering, University of Moratuwa, Katubedda, Moratuwa, 10400, Sri Lanka.
Ranjith PremasiriDepartment of Earth Resource Engineering, Faculty of the Engineering, University of Moratuwa, Katubedda, Moratuwa, 10400, Sri Lanka.
Upaka RathnayakeDepartment of Civil Engineering and Construction, Faculty of Engineering and Design, Atlantic Technological University, Sligo, F91 YW50, Ireland. upaka.rathnayake@atu.ie.ORCID http://orcid.org/0000-0002-7341-9078

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Urbanization is accelerating rapidly, highlighting the critical role of aligning with sustainable development goals, urban green and blue spaces (UGS and UBS). These spaces play a crucial role in enhancing the health and well-being of city residents in terms of ecology. Acknowledging the importance of urban ecology, this study utilizes Sentinel-2A data and support vector machine classification, aimed to identify UGS and UBS. To examine the connections between UGS and UBS, specific indices, spectral bands, and textures were calculated. Additionally, the concentration of chlorophyll, a vital indicator of ecological health, was assessed using three indices. Structural equation modeling was employed to elucidate the relationship between UGS and UBS and their impact on chlorophyll concentration for the years 2017 and 2023. In the 2017 model, UGS exhibited a positive path coefficient (0.25) with chlorophyll-a, indicating that an increase in UGS is associated with an increase in chlorophyll levels. Conversely, in 2023, the path coefficient turned negative (- 0.83), presenting a stark contrast to the 2017 model. This shift suggests potential environmental or urban development changes, such as alterations in the quality or type of urban green spaces, potentially including more non-native or ornamental plants that contribute less to overall chlorophyll levels. UGS can be subjected to pollution, soil compaction, and other stressors that reduce plant health. Similarly, the UBS showed an increase in its path coefficient from - 0.99 in 2017 to - 1.8 in 2023, suggesting improvements such as cleaner water or urban planning strategies aimed at reducing water pollution. The consistent negative relationship across both years suggests that urban water bodies are not contributing to Chl levels due to complex interactions of water bodies with their urban surroundings. However, further research is essential to delve into these dynamics and comprehend the implications for urban ecological planning and sustainability.

Indexed as

Artificial IntelligenceChlorophyllChlorophyll AEnvironmental MonitoringCitiesUrbanizationChlorophyllChlorophyll AArtificial intelligenceChlorophyll-a concentrationsRandom forest classificationUrban green and blue spacesUrbanization

Identifiers

PMID40119233
PMCPMC12819471

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.