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RETRACTED ARTICLE: Environmental planning and economic efficiency of green cities based on improved neural network and satellite remote sensing

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This article was retracted on 06 December 2021

An Editorial Expression of Concern to this article was published on 28 September 2021

This article has been updated

Abstract

The society is constantly progressing, the population is increasing, and the pace of urbanization is getting faster and faster. However, while the city is developing rapidly, there are also problems of thermal environment. The most important part of solving the current environmental problems in the city is to strengthen the greening in the city. The solution of economic problems in the environment can promote the coordinated development of the city, thereby improving economic efficiency. The strength of the urban heat island has a certain relationship with the greening of the city. When the green area of the city is large, the heat island effect in the city is low, and the two are in a negative correlation. In the center of the city, the degree of economic development is relatively high, and people in areas with little land and little money are unwilling to use land where they cannot generate economic benefits. Therefore, vegetation coverage should be increased in urban centers, especially by planting some trees on both sides of the road to reduce the heat island effect. Planning for the urban environment should pay attention to the following two aspects: Firstly, for other types of land use, scientific planning should be done and the land should be used rationally. Secondly, in order to make the urban green space construction more systematic and the layout more reasonable, in the construction process, the various areas should be united to form a whole, so as to make the layout more reasonable and scientific. In this article, the author judges the surface temperature of the city by improving the neural network based on the data in the satellite remote sensing image. In the planning of the future environment of the green city, the author compared different evaluation systems in order to obtain more accurate results, mainly the two evaluation systems of statistical data and remote sensing data. After considering the advantages and disadvantages of different models, the parameters of the model were further improved, and the feasibility of the model was tested.

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Acknowledgement

Yeung Lapfu is the PHD candidate in China University of Political Science and Law.

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Authors and Affiliations

  1. Civil, Commercial and Economic Law School, China University of Political Science and Law, Beijing, 100088, China

    Yeung Lap-fu

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  1. Yeung Lap-fu
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Correspondence to Yeung Lap-fu.

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The authors declare that they have no competing interests.

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Responsible Editor: Sheldon Williamson

This article is part of the Topical Collection on Environment and Low Carbon Transportation

This article has been retracted. Please see the retraction notice for more detail: https://doi.org/10.1007/s12517-021-09175-9

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Lap-fu, Y. RETRACTED ARTICLE: Environmental planning and economic efficiency of green cities based on improved neural network and satellite remote sensing. Arab J Geosci 14, 1399 (2021). https://doi.org/10.1007/s12517-021-07657-4

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  • DOI: https://doi.org/10.1007/s12517-021-07657-4

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