Smart city oriented Ecological Sensitivity Assessment and Service Value Computing based on Intelligent sensing data processing

Duan, Yaqiong; Zhang, Lingda; Fan, Xiaoyang; Hou, Quanhua; Hou, Xinmeng

doi:10.1016/j.comcom.2020.06.009

Cited by 21 publications

(5 citation statements)

References 5 publications

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“…A cloud platform supported by city panoramic data and unified data/business services forms comprehensive management and emergency command center of resource convergence and sharing, intelligent decision-making, and cross-departmental coordination and linkage in cities [12]. e collaborative application of multiple approaches and technologies in the ecological strategy-oriented UGS planning reveals that ecological environment improvement planning is gradually developing and improving at the level of urban spatial planning [13,14]. Based on the intelligent urban system, the intelligent implantation of the UGS system planning can significantly improve the intellectual level of regional management, support the scientific, efficient, intelligent, and refined green space management, enhance the intellectual ability of regional services, and provide convenient, practical, intelligent, and accurate green space services.…”

Section: Urban Green Space System Planning In Smart Citiesmentioning

confidence: 99%

[Retracted] Green Space Planning and Landscape Sustainable Design in Smart Cities considering Public Green Space Demands of Different Formats

Shan

Huang²,

Chen

et al. 2021

Complexity

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The fast urban development leads to many complex problems. A smart city aims to solve these problems using scientific approaches. Urban Green Space (UGS) is a fundamental component of urban infrastructure. It needs to be upgraded simultaneously with the concept of the smart city. Methods of smart UGS planning and sustainable landscape design help integrate ecological performance and other functions of UGS. Smart UGS planning is a technical management tool and a human-centered smart application. A novel UGS classification method based on function combinations is proposed in the present work. Five types of UGS (Scenic UGS, Residential UGS, Commercial UGS, Office UGS, and Road UGS) in Baqiao District of Xi’an, Shaanxi Province, are selected as sample sites. Interviewees’ socio-economic attributes, visiting frequencies, and differences in demands are investigated. Eventually, the UGSs researched in this work are optimized based on public preferences and the current conditions of the sites. Results demonstrate the following. (1) The public’s preference for different types of UGS is different considerably. (2) Based on the public’s preference, Scenic UGS is improved in terms of quantity, function, and management; Residential UGS is upgraded regarding quantity and accessibility; and Commercial UGS, Office UGS, and Road UGS are improved in terms of quality. The results could provide methodological references for planning different types of UGS and innovative insights for smart UGS planning and sustainable landscape design.

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Section: Urban Green Space System Planning In Smart Citiesmentioning

confidence: 99%

[Retracted] Green Space Planning and Landscape Sustainable Design in Smart Cities considering Public Green Space Demands of Different Formats

Shan

Huang²,

Chen

et al. 2021

Complexity

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show abstract

“…The ecological environment is often affected by various aspects, so when evaluating ecological sensitivity, a multi-factor comprehensive method is often used. Each factor has different effects on ecological sensitivity [3][4], so it should have different weights. Through the Analytical Hierarchy Process (AHP) method Calculate the weight of each factor and use the analytic hierarchy process to construct a pairwise judgment matrix of ecological sensitivity, sort and calculate the weight of each evaluation factor, and finally use a consistency test to determine whether the determined weight value is close to the objective reality.…”

Section: Determination Of Weight Of Evaluation Indicatorsmentioning

confidence: 99%

Comprehensive assessment of ecological environment sensitivity in Guangdong Province based on GIS

Ge,

chen,

Zhang

et al. 2024

Second International Conference on Environmental Remote Sensing and Geographic Information Technology (ERSGIT 2023)

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Taking Guangdong as the research area, using 2022 Landsat remote sensing data and based on geographic information system (GIS) technology, five evaluation factors were selected: slope, aspect, elevation, water system and vegetation index, analyze the sensitivity of Guangdong’s ecological environment. The results show: Single-factor ecological sensitivity analysis shows that among the five evaluation factors, land use category and elevation are important factors that affect the degree of ecological vulnerability in Guangdong Province. The weights are: land use type (0.32), elevation (0.104). Comprehensive ecological sensitivity analysis shows that Guangdong has obvious differences in ecological sensitivity, with low-sensitivity areas accounting for the largest proportion, followed by sensitive areas. The extremely sensitive areas are mainly distributed in Heyuan and Meizhou; the sensitive areas are mainly distributed in Zhaoqing, Qingyuan and Shaoguan; the low-sensitive areas are mainly distributed in Zhanjiang, Maoming, Yangjiang, Jiangmen and Shanwei; the insensitive areas are mainly distributed in central Guangdong (Guangzhou, Foshan, Zhongshan, Dongguan, Shenzhen) and the eastern region (Chaozhou and Jieyang). The comprehensive evaluation results of the ecological environment sensitivity in Guangdong Province can provide relevant suggestions for regional ecological environment protection and construction.

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“…Literature [17], in order to promote the development of rural revitalization, uses dynamics and landscape models to analyze the land use and landscape of the countryside in a spatio-temporal manner and derives a method for weighing environmental protection and economic development. Literature [18] promotes the development of rural revitalization by planning rural land space and controlling mobile ecological space to achieve sustainable development and ecological environmental protection. Literature [19] proposes the theory of coordination and coupling of the current state of rural tourism economy and industry to promote the development of rural revitalization by improving the competitiveness of rural tourism.…”

Section: Literature Reviewmentioning

confidence: 99%

Rural tourism incorporating artificial intelligence technology to help modernize rural revitalization

Gan

2023

Applied Mathematics and Nonlinear Sciences

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In the process of modernization and development, intelligent technology empowers rural tourism, which in turn enables the effective implementation of the rural revitalization strategy. In this paper, a rural tourism recommendation model combined with artificial intelligence technology is constructed, which effectively improves the accuracy and personalization level of tourist attraction recommendation by mining and analyzing tourism data and extracting tourism characteristic factors. Secondly, the random forest classification algorithm is used to establish a random forest preference attraction prediction model, and several recommendation algorithms are combined to design a personalized rural tourism recommendation model to improve the accuracy of tourists’ tourism recommendations. Finally, the countryside around a city is being investigated to explore the modern development of rural tourism and help revitalize rural areas. The results show that the number of people received by rural tourism in City A and the number of tourists received by the province in 2022 is 972 million and 1,424 million more than that of 2014, and the total income from rural tourism in City A and the total income from tourism in the province in 2022 is 724.8 billion and 1,202.02 billion yuan more than that of 2014, and it can be seen that the high level of tourism income maintains a positive correlation with the number of tourists received. It shows that rural tourism improves the overall economic level of the countryside, accelerates the process of social progress in rural areas, and strongly contributes to the modernization and development of rural revitalization.

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Smart city oriented Ecological Sensitivity Assessment and Service Value Computing based on Intelligent sensing data processing

Cited by 21 publications

References 5 publications

[Retracted] Green Space Planning and Landscape Sustainable Design in Smart Cities considering Public Green Space Demands of Different Formats

[Retracted] Green Space Planning and Landscape Sustainable Design in Smart Cities considering Public Green Space Demands of Different Formats

Comprehensive assessment of ecological environment sensitivity in Guangdong Province based on GIS

Rural tourism incorporating artificial intelligence technology to help modernize rural revitalization

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