Abstract
In recent years, many cities in the world have been hit by the high temperature heat wave and suffered heavy losses. And many coastal cities have been affected to a certain extent. Through reasonable urban form and architectural design to cope with the heat wave, improving the city’s ability to cope with high temperature has become an important planning and mitigation strategy to adapt to urban high temperature. In this paper, big data is applied to the study of coastal weather characteristics. From the perspective of urban planning and architecture, the interaction mechanism of coastal weather characteristics is discussed by using quantitative analysis methods such as correlation analysis and spatial regression model, which provides an important basis for the planning and urban design of high temperature heat wave. Then, taking urban morphology parameters, land use parameters and LST as variables, Pearson correlation coefficient was calculated by SPSS and GeoDa tools, and a spatial regression model was established to explore the quantitative relationship between coastal weather characteristics and land surface temperature. In the Pearson correlation coefficient, the correlation between vegetation coverage and LST is the largest, showing a negative correlation, with the coefficient of −0.595; 595. In addition to coastal climate types, the correlation between building density and LST is the largest, the coefficient is 0.360, positive correlation, the correlation is the smallest. With the application of big data technology, the tax collection and management mode will develop in the direction of intelligence, efficiency, fairness, and accuracy. Big data technology will provide a new direction for the research of coastal meteorological characteristics and the optimization of urban enterprise finance and taxation. In this paper, through the study of coastal meteorological characteristics of big data, it is applied in the city enterprise financial tax, to promote the enterprise financial tax more standardized.
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17 November 2021
This article has been retracted. Please see the Retraction Notice for more detail: https://doi.org/10.1007/s12517-021-08988-y
28 September 2021
An Editorial Expression of Concern to this paper has been published: https://doi.org/10.1007/s12517-021-08471-8
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Resposible 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/s12517-021-08988-y
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Li, Z., Ping, C. RETRACTED ARTICLE: Coastal meteorological characteristics based on big data and financial tax optimization of urban enterprises. Arab J Geosci 14, 1499 (2021). https://doi.org/10.1007/s12517-021-07892-9
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DOI: https://doi.org/10.1007/s12517-021-07892-9