Trade-offs and driving forces of land use functions in ecologically fragile areas of northern Hebei Province: Spatiotemporal analysis

Liu, Chao; Xu, Yao; Lu, Xinhai; Jing, Han

doi:10.1016/j.landusepol.2021.105387

Cited by 70 publications

(29 citation statements)

References 38 publications

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“…Geodetector can directly quantify the influence of each factor on LST and clarify the types of interactions among factors, which is conducive to grasping the spatial mechanism and understanding the causes of spatial action. Geodetector model has simple parameter settings and wide application scenarios compared with the GWR model [ 46 , 47 , 48 ]. In recent years, some scholars choose geographic detector to detect the influencing factors of UHI.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Analysis of a Spatial Distribution and Driving Factors of the Urban Heat Island Effect: A Case Study of Fuzhou Central Area, China

You

Lai

Lin

et al. 2021

IJERPH

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Land surface temperature (LST) is a joint product of physical geography and socio-economics. It is important to clarify the spatial heterogeneity and binding factors of the LST for mitigating the surface heat island effect (SUHI). In this study, the spatial pattern of UHI in Fuzhou central area, China, was elucidated by Moran’s I and hot-spot analysis. In addition, the study divided the drivers into two categories, including physical geographic factors (soil wetness, soil brightness, normalized difference vegetation index (NDVI) and modified normalized difference water index (MNDWI), water density, and vegetation density) and socio-economic factors (normalized difference built-up index (NDBI), population density, road density, nighttime light, park density). The influence analysis of single factor on LST and the factor interaction analysis were conducted via Geodetector software. The results indicated that the LST presented a gradient layer structure with high temperature in the southeast and low temperature in the northwest, which had a significant spatial association with industry zones. Especially, LST was spatially repulsive to urban green space and water body. Furthermore, the four factors with the greatest influence (q-Value) on LST were soil moisture (influence = 0.792) > NDBI (influence = 0.732) > MNDWI (influence = 0.618) > NDVI (influence = 0.604). The superposition explanation degree (influence (Xi ∩ Xj)) is stronger than the independent explanation degree (influence (Xi)). The highest and the lowest interaction existed in ”soil wetness ∩ MNDWI” (influence = 0.864) and “nighttime light ∩ population density” (influence = 0.273), respectively. The spatial distribution of SUHI and its driving mechanism were also demonstrated, providing theoretical guidance for urban planners to build thermal environment friendly cities.

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Section: Introductionmentioning

confidence: 99%

Quantitative Analysis of a Spatial Distribution and Driving Factors of the Urban Heat Island Effect: A Case Study of Fuzhou Central Area, China

You

Lai

Lin

et al. 2021

IJERPH

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“…Numerous studies have already revealed that the LUFs are correlated with physical factors and socioeconomic activities [44][45][46]. Therefore, two groups of independent variables are introduced in the econometric model.…”

Section: Model and Variables Specificationmentioning

confidence: 99%

“…The other group is related to the socioeconomic aspect, containing distance to prefecture and county center, distance to national highway, average population density, whether the township is urban (with the urban construction land area as more than 80% of total construction land), and GDP per capita (logarithm form) and public expenditure per capita of the county (logarithm form). Distances to different administrative centers and highway reflect the geographical location, which mainly affect spatial suitability and rationality of different functions and have been proven critical to economic and social functions of land uses [45]. Urbanization and regional development (represented by GDP per capita) may cause environmental degradation on the one hand, but on the other hand it can change LUFs by altering people's various needs [48,49].…”

Section: Model and Variables Specificationmentioning

confidence: 99%

Valuating Multifunctionality of Land Use for Sustainable Development: Framework, Method, and Application

Peng

Liu

Cao

2023

Land

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The concept of land use functions (LUFs) has been widely employed to study and manage sustainable development. However, its employment is barely based on actual land uses. Difficulties in the accessibility of data and comparability of results also hinder the wide application of contemporary LUF frameworks on sustainability analysis. To fill these gaps, this study improves the LUF framework in which the monetary value of economic, social, and environmental LUF is evaluated using land use data. This framework is then used to examine how different LUFs relate to each other in Shandong, China. Results show that, at the township level, monetary values of economic and social functions are positively correlated, but are both negatively correlated with environmental function. All three functions grew between 2009 and 2018 in Shandong. Results also suggest that a focus on quantitative trade-offs of these three LUFs is insufficient; rather, their spatial balance also requires attention.

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“…Based on the main function of land-use types, the land-use type merging method directly merges land-use types into different spatial types [24,29,38]. The index system calculation method is based on social, economic, natural, and other factors that affect PLE spaces, and it adopts the comprehensive evaluation method to construct the index system to identify PLE spaces [28,36,39]. Index system classification is mainly based on land-use multifunction [40,41], ecosystem service [42], landscape function [43], and other theories to carry out PLE function classification.…”

Section: Introductionmentioning

confidence: 99%

Functional Tradeoffs and Feature Recognition of Rural Production–Living–Ecological Spaces

Zhao

Cheng

Fan

et al. 2022

Land

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Recently, the spatial contradiction in rural construction has intensified. Production–living–ecological (PLE) spaces, as important load-bearing spatial patterns of rural revitalization, have become a research focus of territorial space planning. Because of the lack of studies on the scale and accuracy at the township level in rural PLE spaces, the objective of this study is to quantify the subfunctional and functional areas of PLE spaces, weigh the relationship between PLE functions, and conduct feature identification and strategy formulation of the PLE synergistic functional areas. Combined with multitype measurement methods, the study constructed a township-level PLE space evaluation system composed of 12 subfunctional indicators. Taking Guli Street in Nanjing city as an example, Spearman correlation analysis, spatial local autocorrelation analysis, and cold/hot spot identification were used to analyze the synergies and tradeoffs between PLE functions. On this basis, the evaluation model of the PLE synergies area was constructed. The results showed that the production function showed a fragmented distribution pattern. The proportion of high-intensity living function areas was very small. The ecological function area had good patch integrity. In the PLE functions, obvious synergies exist between any two functions, and the tradeoff between the third one and any of the two functions. The seven types of PLE synergistic potential areas were dominated by the dual-function high synergistic zone (DF-H-Z). The zoning scheme and governance strategy proposed in this paper have important practical value for solving the contradiction of sustainable and coordinated development of township-scale spatial resources.

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Trade-offs and driving forces of land use functions in ecologically fragile areas of northern Hebei Province: Spatiotemporal analysis

Cited by 70 publications

References 38 publications

Quantitative Analysis of a Spatial Distribution and Driving Factors of the Urban Heat Island Effect: A Case Study of Fuzhou Central Area, China

Quantitative Analysis of a Spatial Distribution and Driving Factors of the Urban Heat Island Effect: A Case Study of Fuzhou Central Area, China

Valuating Multifunctionality of Land Use for Sustainable Development: Framework, Method, and Application

Functional Tradeoffs and Feature Recognition of Rural Production–Living–Ecological Spaces

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