Evidence map›Paper›PMID 38765127›Full record

ArticleHeliyon2024

CA-based urban growth model considering the temporal dynamic adjustment of local spatial driving factors: An application in Wuhan City.

Jianwei Sun, Qingsong He, Haofeng Wang

Abstract read
In one paragraph

Article in Heliyon, 2024. 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

3 authors.

Jianwei SunSchool of Geographical and Environmental Sciences, Guizhou Normal University, Guizhou, Guiyang, 550025, PR China.
Qingsong HeCollege of Public Administration, Huazhong University of Science & Technology, 1037Luoyu Road, Wuhan, 430074, Hubei Province, PR China.
Haofeng WangInformation Center of Natural Resources and Planning of Wuhan City, 13Sanyang Road, Wuhan, 430074, Hubei Province, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cellular Automaton (CA) is widely used because of its ability to simulate complex spatiotemporal dynamic processes through applying simple rules. The basis of the CA model is the definition of transformation rules. During a simulation process, the rules determine the change of the cell state. However, existing processing methods calculate the driving factors based on single-point time (start time or end time), making it difficult to reflect the fact that numerous driving factors affecting the cell conversion dynamically change with time. Based on the time dynamics perspective and the data set of multiple time series, this paper designs a method of dynamic adjustment of driving factors of urban expansion on the local cell-scale. It uses linear, exponential, logarithmic, and polynomial fitting to develop a CA model of dynamic adjustment that conforms to the characteristics of local spatial evolution. The main conclusions of the paper are as follows: (1) The polynomial fitting has the highest average R

Indexed as

Cellular automataDynamic driving factorsMicro-scaleWuhan

Identifiers

PMID38765127
PMCPMC11101809

What OpenQuestion holds

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LicenceCC BY-NC
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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.