Quantitative analysis of the relationship between land use and urbanization development in typical arid areas

Hou, Kun; Wen, Jiafeng

doi:10.1007/s11356-020-08577-8

Cited by 15 publications

(6 citation statements)

References 31 publications

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“…Since natural factors are relatively stable with cumulative effects over short time scales, human activities have played a dominant role in regional environmental change at the scale of decades to centuries [ 2 ]. With the rapid development of social economy, the role of human socioeconomic activities in driving the evolution of land use systems has become more obvious [ 3 , 4 ]. Since the reform and opening up, China has experienced rapid urbanization [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Scenario-Based Analysis of Land Use Competition and Sustainable Land Development in Zhangye of the Heihe River Basin, China

Bai

Zhao

Weng

et al. 2021

IJERPH

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Rapid economic growth has a significant impact on land use change, which would threaten the natural ecology. Zhangye city of the Heihe River Basin, China is an ecologically vulnerable region where land use changes significantly due to socioeconomic development and population increases. The study employed a computable general equilibrium of land use change (CGELUC) model to simulate land use change and then used a dynamic land system (DLS) model to spatialize land use change during 2015–2030 under three development scenarios in Zhangye city. The three development scenarios are the baseline scenario (BAU), the resource consumption scenario (RCS) and the green development scenario (GDS). We found that economic growth would lead to land demand increases in high value-added industries and decreases in low value-added industries. The cultivated land would decrease while the built-up area would increase. By 2030, the cultivated land will decrease by 8.16%, 10.89% and 4.16%, respectively, under BAU, RCS and GDS, while the built-up area will increase by 8.61%, 10.39% and 4.75%, respectively. The expansion of built-up area under RCS presents spatial characteristics of centralized distribution, while spatial characteristics of uniform discrete distributions are presented under GDS. The expansion of ecological land under GDS would be considerable, especially in the north of Sunan County and Gaotai County, and around the natural reserve of Ganzhou County. This paper provides a scientific reference for coordinating economic development and ecological protection in the rapidly developing urbanized areas in western China.

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Section: Introductionmentioning

confidence: 99%

Scenario-Based Analysis of Land Use Competition and Sustainable Land Development in Zhangye of the Heihe River Basin, China

Bai

Zhao

Weng

et al. 2021

IJERPH

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“…Related studies in recent years showed that the urbanization rate of Jiayuguan was extremely high, exceeding 90% [ 22 ]. Therefore, this study focused on road dust in the urban area of Jiayuguan.…”

Section: Methodsmentioning

confidence: 99%

Pollution Characteristics, Source Apportionment, and Health Risk Assessment of Potentially Toxic Elements (PTEs) in Road Dust Samples in Jiayuguan, Hexi Corridor, China

Xiao

Yao

Zhang

et al. 2022

Toxics

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The sources of potentially toxic elements (PTEs) in road dust are complex and potentially harmful to humans, especially in industrial cities. Jiayuguan is the largest steel-producing city in Northwest China, and this study was the first to conduct a related study on PTEs in road dust in this city, including the pollution characteristics, source apportionment, and health risk assessment of PTEs in road dust. The results showed that the highest concentration of PTEs in the local road dust samples were Mn, Ba, Zn, and Cr. The enrichment factor (EF) of Se was the highest, and it was “Very high enrichment” in areas other than the background area, indicating that the local Se was more affected by human activities. The geoaccumulation index (Igeo) of Se was also the highest, and the pollution level was 5 in all areas except the background area, indicating that the local Se was more polluted and related to coal combustion. The sources of PTEs in local road dust samples mainly included geogenic-industrial sources, coal combustion, traffic sources, and oil combustion. For the non-carcinogenic risk, the hazard index (HI) of each element of children was higher than that of adults, and the sum of the HI of each element was greater than 1, indicating that there was a non-carcinogenic risk under the combined influence of multiple elements, which was especially obvious in industrial areas. For the carcinogenic risk, the cancer risk (CR) of Cr at a certain point in the industrial area exceeded 10−4, which was a carcinogenic risk, and the Cr in this area may be related to the topsoil of the local abandoned chromate plant.

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“…Land use/cover changes deeply depend on urbanization. A study on the quantitative relationships between land use/cover type and the UHI effects is an important step for understanding the mechanism of UHI (Hou and Wen, 2020). Traditional UHI studies using the observed temperature data from fixed or mobile monitoring stations may lead to a potential bias that cannot represent the holistic urban thermal environment.…”

Section: Introductionmentioning

confidence: 99%

Long Time-Series Urban Heat Island Monitoring and Driving Factors Analysis Using Remote Sensing and Geodetector

Xiong

Zou

et al. 2022

Front. Environ. Sci.

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Urban heat island (UHI) effect decribes significant change due to rapid urbanization development. This study focused on the long time series analysis of UHI during the period 2000-2018, and analyzed the impact of land cover type and landscape metric factors on surface temperature. The results revealed that the UHI had a continuously decreasing trend in 2005–2010, and an increasing trend in 2000–2005 and 2010–2018. Cropland, built-up land, patch density (PD), Shannon Diversity Index (SHDI), and Landscape Shape Index (LSI) had a positive relationship with UHI, whereas forestland, open water, and CONTAG had a negative correlation with the UHI effect. The Geodetector analysis further revealed that PD, SHDI, and LSI had the greatest influences on LST as the three factors had the largest q values (0.287, 0.286, and 0.278). Forestland, cropland, and built-up land had greater impacts on the UHI than other land cover type factors. The explanatory power reached a maximum value of 0.408 when built-up land and cropland variables interacted. The findings of this study provide new understandings of the relationship between urban landscape and UHI, as well as important insights for urban planners to mitigate the UHI effect for the sustainable development of future urban agglomeration.

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Quantitative analysis of the relationship between land use and urbanization development in typical arid areas

Cited by 15 publications

References 31 publications

Scenario-Based Analysis of Land Use Competition and Sustainable Land Development in Zhangye of the Heihe River Basin, China

Scenario-Based Analysis of Land Use Competition and Sustainable Land Development in Zhangye of the Heihe River Basin, China

Pollution Characteristics, Source Apportionment, and Health Risk Assessment of Potentially Toxic Elements (PTEs) in Road Dust Samples in Jiayuguan, Hexi Corridor, China

Long Time-Series Urban Heat Island Monitoring and Driving Factors Analysis Using Remote Sensing and Geodetector

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