Spatio-temporal scale identification of LUCC based on remote sensing images in Shenyang Economic Zone.

Yue Wang, Xingrong Lu, Guohong Chen

Abstract read

In one paragraph

Article in Scientific reports, 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

3 authors.

Yue WangSchool of Management, Shenyang Normal University, No. 253 North Street of the Yellow River, Shenyang, 110034, Liaoning Province, China. ywmath@synu.edu.cn.

Xingrong LuSchool of Management, Shenyang Normal University, No. 253 North Street of the Yellow River, Shenyang, 110034, Liaoning Province, China.

Guohong ChenSchool of Management, Shenyang Normal University, No. 253 North Street of the Yellow River, Shenyang, 110034, Liaoning Province, China. chenguohonggl@synu.edu.cn.

Funding

Key projects of social science fund of Liaoning province of China L22AGL018Key research and development program of Liaoning province of China 2024JH2/102500056National Natural Science Foundation of China 42301296

6 · The paper itself

Abstract

Determining the appropriate analysis of spatio-temporal scale characteristics of land use and land cover change (LUCC) can effectively reveal and grasp complex geographical phenomena and patterns. However, current methodologies often suffer from subjectivity, experimental errors, and limitations in spatial representation, as they typically rely on statistical data. There is an urgent need for innovative methods to identify spatial (grid-based) and temporal (time series) scales. This study focuses on the Shenyang Economic Zone, employing an enhanced fractal box-counting dimension model and wavelet analysis to objectively determine the spatial and temporal scales of LUCC. The findings indicate that: (1) Fractal characteristics effectively measure spatial-scale, and (2) Wavelet variance serves as a novel parameter for describing LUCC's temporal development. These results demonstrate that fractal characteristics and wavelet variance are robust descriptors of LUCC, with the proposed spatio-temporal scale identification methods showing strong applicability.

Indexed as

Land use and land cover change (LUCC)Remote sensing imagesSpatial-scaleTemporal-scaleWavelet analysis

Identifiers

PMID40595020

DOI10.1038/s41598-025-94770-z

PMCPMC12214697

What OpenQuestion holds

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LicenceCC BY-NC-ND

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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.