Urban development trend analysis and spatial simulation based on time series remote sensing data: A case study of Jinan, China

Zhang, Yanghua; Zhao, Liang; Zhao, Hu; Gao, Xiaoyang

doi:10.1371/journal.pone.0257776

Cited by 8 publications

(6 citation statements)

References 58 publications

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“…Gong et al 30 devised three distinct scenarios to forecast the evolution of various civil building areas in China from 2020 to 2060, namely the benchmark scenario, the moderate control scenario, and the stringent control scenario. Similarly, Zhang et al 31 formulated three urban growth simulation scenarios spanning from 2015 to 2030, namely the historical scenario, a moderate growth scenario, and the strict restriction scenario. The velocity of urban growth under the historical growth scenario was significantly greater than the other two scenarios.…”

Section: Resultsmentioning

confidence: 99%

Forecasting the carbon footprint of civil buildings under different floor area growth trends and varying energy supply methods

Teng,

Yin

2023

Sci Rep

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The energy consumption and carbon footprint of buildings are significantly impacted by variations in building area and the number of households. Therefore, it is crucial to forecast the growth trend of building area and number of households. A validated time series model is used to predict the new building area in Jilin Province from 2023 to 2030. The new building area in Jilin Province is expected to exhibit two trends of growth in the future: rapid growth (S1) and slow growth (S2). By 2030, under the S1 growth trend, the residential construction area and public building construction area in Jilin Province are expected to be 30.26 Mm2 (million square meters) and 7.23 Mm2, respectively. If the future floor area grows slowly under the S2 trend, the new floor area of different types will be 8.26 Mm2 and 1.33 Mm2 by 2030, respectively. The population growth shows a downward trend. Therefore, the energy consumption and carbon footprint of new buildings with different growth trends of floor areas and the number of households can be predicted. The energy consumption of new buildings shows an increasing trend from 0.32 Mtce in 2023 to 0.55 Mtce in 2030 under the S1 trend and a slight downward trend under the S2 trend. The carbon footprint is expected to be reduced by 0.017–0.311 million tons of CO2 when using heat pumps to supply 10–50% of the heat and wind and solar to supply 10–50% of the electricity. For every 10% increase in the use of ultra-low energy buildings, the energy consumption of civil buildings decreases in the range of 0.0063–0.028 Mtce. If the use of heat pumps and renewable energy increases by 10%, the energy consumption of civil buildings decreases in the range of 0.0054–0.0249 Mtce.

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Section: Resultsmentioning

confidence: 99%

Forecasting the carbon footprint of civil buildings under different floor area growth trends and varying energy supply methods

Teng,

Yin

2023

Sci Rep

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“…The results of our study demonstrate the use of city administrative taxes, a socioeconomic survey of living standards, household income, and satellite data to assess the primary drivers of urban growth in different built-up areas in Uyo (Figure 2). We performed an analysis on the socio-economic variables using an approach adapted from [31,32,40,41] in the study area. According to the NBS 2020 statistical data for Uyo, low-density built-up areas are situated near the designated urban area.…”

Section: Discussionmentioning

confidence: 99%

“…The linear statistics model for this research has been described in detail by [31,32,40,41] with regard to its application, standardization, and validation. The model combines statistical data with numerical analysis, is suitable for predicting urban built-up changes, and can also be used to explore different statistical approaches [31,40].…”

Section: Statistical Analysesmentioning

confidence: 99%

Evaluation of Economic Linkage between Urban Built-Up Areas in a Mid-Sized City of Uyo (Nigeria)

Samimi

2021

Land

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Urban growth has transformed many mid-sized cities into metropolitan areas. One of the effects of this growth is a change in urban growth patterns, which are directly linked with household income. Hence, this paper aims to assess the effect of different economic variables that trigger urban built-up patterns, using economic indicators such as city administrative taxes, a socio-economic survey of living standards, household income and satellite data. The regression model was used and adapted, and a case study is presented for the mid-sized city of Uyo in southeastern Nigeria. The result shows sparse built-up growth patterns with numerous adverse effects. Although, there is awareness of the impact of unregulated sparse built-up growth patterns in the literature, little attention has been given to this growth pattern in Africa. The results also show that increases in federal allocation (27%), investment tax (22%), direct tax (52%) and indirect tax (26%) have led to urban expansion into vegetative land and have a causal correlation with different built-up areas. Hence, medium and high-income earners migrate to suburban areas for bigger living space and a lack of basic social amenities affects the land value in suburban areas. They also assist in the provision of social amenities in the neighborhood.

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“…It is consistent with Li (2014), who applied a Geographic Information System (GIS) based buffer analysis to determine a 0-250 m buffer zone around a built-up area to monitor an urban growth process, and Wang et al (2022b), who used a 20-100 m buffer zone to measure the UBG of 15 districts for a road network and urban population density analysis. Urban development trend analyses from urban simulation scenarios are often on selected years within the range of the starting and ending years (Aljoufie et al, 2011;Molugaram and Rao, 2017;Shi et al, 2018;Tennoy et al, 2019;Zhang et al, 2021;Zhao et al, 2017). Supplementary Table S1 shows that the ranges of years chosen in spatial data analysis were not necessarily equally spaced and could be as discrete as continuous.…”

Section: Methodsmentioning

confidence: 99%

Urban expansion and transportation interaction: Evidence from Akure, southwestern Nigeria

Faiyetole

Adewumi

2023

Environment and Planning B: Urban Analytics and City Science

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The unprecedented increase in population and urbanization dynamics, particularly without the requisite road infrastructure on the African continent, necessitates a more contextual understanding of the interaction between urban expansion and transportation in its cities. The study used Landsat and Google Earth, two readily available data in a resource-constrained context, and population data from 1999 to 2018 to estimate the interactions between roads stock, urban size and corresponding population changes in Akure, a mid-sized capital city in Nigeria, with substantial federal road connectivity. The results suggest strong positive relationships among all the variables of interest. At α = 10%, an increase in road stock causes a significant ( p = 0.064) increase in population. The study reveals a heavier road density as the city expanded, slightly reduced from the core, with an increased stock of roads toward the periphery. These findings could significantly inform how cities evolve and can guide urban and transportation planners on complementary road infrastructure for growing cities. The study recommends that, irrespective of the political dispensation, the government could increase connective and motorable road stock toward the periphery each fiscal year, with promises of sustainability and resilience in the urban system despite the ever-increasing population.

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Urban development trend analysis and spatial simulation based on time series remote sensing data: A case study of Jinan, China

Cited by 8 publications

References 58 publications

Forecasting the carbon footprint of civil buildings under different floor area growth trends and varying energy supply methods

Forecasting the carbon footprint of civil buildings under different floor area growth trends and varying energy supply methods

Evaluation of Economic Linkage between Urban Built-Up Areas in a Mid-Sized City of Uyo (Nigeria)

Urban expansion and transportation interaction: Evidence from Akure, southwestern Nigeria

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