Bayesian methods to estimate urban growth potential

Smith, Jordan W.; Smart, Lindsey S.; Dorning, Monica A.; Dupéy, Lauren Nicole; Méley, Andréanne; Meentemeyer, Ross K.

doi:10.1016/j.landurbplan.2017.03.004

Cited by 10 publications

(3 citation statements)

References 64 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Smart growth is an urban development method that offers an outline for decision making regarding community growth (Durand et al., 2011; Smith et al., 2017). Smart growth is a progress in finance, ecology, and society (Wei et al., 2018).…”

Section: Model and Methodologymentioning

confidence: 99%

A new model to investigate the impact of innovative IT services on smart urban growth: The mediating role of urban planners’ knowledge

Liu

Zhao

et al. 2021

Growth and Change

View full text Add to dashboard Cite

Cities have turned into intelligent urban zones via new data services like the semantic Web, cloud computing, mobile gadgets, and the Internet of Things (IoT). We can organize smart city policies by numerous technological and policy interferences to improve the efficacy, efficiency, and flexibility of urban infrastructures. Scholars have greatly focused on the development of smart cities. In this study, the influence of Information Technology (IT) services on smart urban growth to make a model for urban decision makers was examined. Data were collected from 201 managers and urban planners. The questionnaires using SPSS 25 and SMART‐PLS 3.2 were statistically analyzed. The outcomes show that cloud services had positive effects on urban planners’ knowledge. In addition, the influence of Near Field Communication (NFC) services on urban planners’ knowledge is positive and significant. The findings have also shown that IoT services are important factors in urban planners’ knowledge. Another point was that urban planners’ knowledge has significantly affected reliability, sustainability, social improvement, energy efficiency, and environmental improvement. At the managerial level, the findings provided recommendations to urban managers and planners.

show abstract

Section: Model and Methodologymentioning

confidence: 99%

A new model to investigate the impact of innovative IT services on smart urban growth: The mediating role of urban planners’ knowledge

Liu

Zhao

et al. 2021

Growth and Change

View full text Add to dashboard Cite

show abstract

“…The results show that as an important grain-producing area in China, the HHH Plain is rich in agriculture land, but more than half of it should be used to improve crop yields and reduce environmental impacts through improved land management and agriculture practices [57][58][59][60]. In terms of urban expansion, outside of Beijing, Tianjin, southern Jiangsu, and several provincial capitals, the urban land use efficiency of most small-and medium-sized cities does not exceed 0.5, which indicates that, to a large extent, economic development and urbanization level improvement do not depend on the expansion of urban areas [61]. Knowing how to make good use of the existing construction land and how to develop industries represent the top priorities for these cities.…”

Section: Land Use Potential and Land Use Efficiencymentioning

confidence: 99%

Study on the Trade-Offs of Land Functions in the Central Plain of China for Sustainable Development

Shi,

Liang,

et al. 2023

Land

View full text Add to dashboard Cite

Properly managing the relationship between food security, ecological protection, and urbanization, and coordinating the trade-offs among these three factors for land demand are extremely important for environmental management and sustainable development. In this study, we attempt to analyze the state of land use trade-offs from a dynamic perspective in terms of both potential and efficiency. We have innovatively proposed a new land use trade-off analysis framework integrating the Estimation System for Land Productivity (ESLP) model, machine learning algorithms, ecosystem service value assessment, and spatial analysis method. By applying the framework, the potential and efficiency of the three land use functions of urban development, ecological protection, and agricultural production on the Huang-Huai-Hai (HHH) Plain were comprehensively estimated, and the trade-off relationship between the three land use functions was identified. The results showed a prominent conflict between urban development and agricultural production (around 8%) on the HHH Plain, especially in the Beijing–Tianjin–Hebei urban agglomeration and the southern Jiangsu urban agglomeration. In the mountainous areas, such as northern Hebei and central Shandong, there was an obvious trade-off between ecological land and agriculture land. Most cities had a trade-off between ecological land and urban land (approximately 6% of the study area), but it was relatively more relaxed in comparison. Finally, we found that on the HHH Plain, where land resources are fiercely competitive, spatial planning and land resource control depend not only on the suitability or potential of the land unit, but also on whether the efficiency of land use has reached an appropriate range. The smart way to use land resources is to scientifically trade-off different land use functions and improve the efficiency of land use to achieve maximum benefit.

show abstract

“…Bayesian modeling is applicable for prediction, risk analysis, diagnosis, monitoring, reliability, and dependency [44] and it can act as a decision support system in government [45][46][47][48]. A Bayesian Network (BN) was developed to analyze the probabilistic causal relationship between the DPS components and actualize the study models.…”

Section: Modeling Toolmentioning

confidence: 99%

Model Prediction of Secondary Soil Salinization in the Keriya Oasis, Northwest China

Seydehmet

Nurmemet

et al. 2018

Sustainability

View full text Add to dashboard Cite

Significant anthropogenic and biophysical changes have caused fluctuations in the soil salinization area of the Keriya Oasis in China. The Driver-Pressure-State-Impact-Response (DPSIR) sustainability framework and Bayesian networks (BNs) were used to integrate information from anthropogenic and natural systems to model the trend of secondary soil salinization. The developed model predicted that light salinization (vegetation coverage of around 15-20%, soil salt 5-10 g/kg) of the ecotone will increase in the near term but decelerate slightly in the future, and that farmland salinization will decrease in the near term. This trend is expected to accelerate in the future. Both trends are attributed to decreased water logging, increased groundwater exploitation, and decreased ratio of evaporation/precipitation. In contrast, severe salinization (vegetation coverage of around 2%, soil salt ≥20 g/kg) of the ecotone will increase in the near term. This trend will accelerate in the future because decreased river flow will reduce the flushing of severely salinized soil crust. Anthropogenic factors have negative impacts and natural causes have positive impacts on light salinization of ecotones. In situations involving severe farmland salinization, anthropogenic factors have persistent negative impacts.

show abstract

Bayesian methods to estimate urban growth potential

Cited by 10 publications

References 64 publications

A new model to investigate the impact of innovative IT services on smart urban growth: The mediating role of urban planners’ knowledge

A new model to investigate the impact of innovative IT services on smart urban growth: The mediating role of urban planners’ knowledge

Study on the Trade-Offs of Land Functions in the Central Plain of China for Sustainable Development

Model Prediction of Secondary Soil Salinization in the Keriya Oasis, Northwest China

Contact Info

Product

Resources

About