Evidence map›Paper›PMID 41776229›Full record

ArticleScientific reports2026

Assessment of coastal land use structure and efficiency based on multi-source data: From the perspective of sea-land gradient.

Yifei Pei, Jianfeng Zhu, Jiake Zhou, Guangshun Sun, Shiru Tang

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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.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Yifei PeiSchool of Geography, Liaoning Normal University, Dalian, Liaoning, China.
Jianfeng ZhuSchool of Geography, Liaoning Normal University, Dalian, Liaoning, China. zjf014@lnnu.edu.cn.
Jiake ZhouSchool of Geography, Liaoning Normal University, Dalian, Liaoning, China.
Guangshun SunSchool of Geography, Liaoning Normal University, Dalian, Liaoning, China.
Shiru TangSchool of Geography, Liaoning Normal University, Dalian, Liaoning, China.

Funding

the National Natural Science Foundation of China 42101257
6 · The paper itself

Abstract

The economic evaluation of urban land depends critically on two aspects: land use structure and land use efficiency(LUE). Understanding how land use structure and efficiency change in response to urban development is critical. Geographically, coastal regions have higher population densities. However, it is unclear from the current study how changes in land use efficiency and structure relate to distance from the coast. Thus, the land use structure of Jinpu New Area from 2015 to 2020 is evaluated in this paper using the location entropy, Lorenz curve, and Gini coefficient methods. The land use efficiency is assessed using the comprehensive index method of multi-source data fusion, and the coupling analysis is carried out in conjunction with the sea-land gradient to thoroughly examine the space–time variation law of the land use structure and efficiency. The results demonstrate that: (1) The land use structure in Jinpu New Area exhibits distinct gradient differentiation. Within the [0,2] km range, land use types are evenly distributed, with an average Gini coefficient of 0.088. The [14,max] km range shows significant disparities in land use distribution, most notably in railway land (locational entropy > 11) and urban land (Gini coefficient > 0.7); (2) Based on land use intensity and land use efficiency, it is concluded that the coupling efficiency of land use in 2015 and 2020 both showed an obvious land-sea gradient: coastal regions had a higher share of inefficient land use with an average coupling efficiency of 0.170 (CI > 0); inland areas had a larger proportion of overloaded land use with an average coupling efficiency of -1.04 (CI < 0); and the land-sea transition zones demonstrated favorable coupling efficiency, with the coupling index being approximately zero. (3) Land use structure correlates with land use efficiency. Land use efficiency exhibits a significant positive correlation with urban land use(p < 0.05) and a significant negative correlation with railway land use(p < 0.1). In contrast, inland regions are often underdeveloped in terms of land use intensity, and railway land use may serve as a useful indicator of potential for future development.

Indexed as

Gini coefficientJinpu new areaLand use efficiencyLand use structureLorenz curveMulti-source data fusionSea-land gradient

Identifiers

PMID41776229
PMCPMC13065806

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