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• W3216486485 abstract "Compared with other ecosystems, urban ecosystem is more vulnerable to the interference of external environmental factors, thus changing the original structure of urban ecosystem, so it is more vulnerable. In a city, how to reasonably layout the landscape of green space, to a certain extent, will affect the development of the city and people's daily life. The emergence of remote sensing technology provides convenience for the extraction of urban green space information. On this basis, scholars at home and abroad constantly put forward new theories and methods to improve the remote sensing technology. The accuracy of green space information extracted by high-resolution image is high, but the workload and cost of this method are large. The most important point is that some confidential information may be involved in the process of green space information extraction with high resolution, so this method is not applicable in the process of large-scale green space information extraction. At present, relevant data show that the medium resolution data can be used to extract urban green space information. In the planning of green space landscape in coastal cities, the city is divided into three areas: coastal water area, intermediate transition area, and land landscape area. According to the theory of landscape ecology, the city is divided into three parts: patch, matrix, and corridor. The process of urban ecological landscape planning is the process of communication between human and nature. In the city, people can feel the beauty of nature. According to the current relevant theory, there are many ways of plant configuration and configuration principles. This paper analyzes the methods and principles of plant configuration in the city by taking the road greening landscape design along a certain place as an example." @default.
• W3216486485 created "2021-12-06" @default.
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• W3216486485 date "2021-11-23" @default.
• W3216486485 modified "2023-09-27" @default.
• W3216486485 title "Retraction Note to: Marine climate prediction based on satellite remote sensing and landscape design of green space in coastal areas" @default.
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• W3216486485 doi "https://doi.org/10.1007/s12517-021-09025-8" @default.
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