Analysis of urban street microclimate data based on ENVI-met
Advances in Intelligent Systems and Computing, ISSN: 2194-5365, Vol: 1117 AISC, Page: 759-767
2020
- 1Citations
- 11Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Conference Paper Description
Microclimate is an important factor affecting the behavior and activities of people in cities. How to analyze the influencing factors of urban microclimate through data analysis and put forward the improvement strategy is an urgent problem to be solved under the background of intelligent city construction. In this paper, the microclimate data of four streets in Majialong Industrial area of Shenzhen are analyzed by using ENVI-met data simulation software, and based on several elements of street orientation, sky view faktor and plant, the improvement strategy of microclimate in urban streets is put forward. To achieve the purpose of guiding urban design, so as to promote the construction of smart city.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85079518473&origin=inward; http://dx.doi.org/10.1007/978-981-15-2568-1_104; http://link.springer.com/10.1007/978-981-15-2568-1_104; http://link.springer.com/content/pdf/10.1007/978-981-15-2568-1_104; https://dx.doi.org/10.1007/978-981-15-2568-1_104; https://link.springer.com/chapter/10.1007/978-981-15-2568-1_104
Springer Science and Business Media LLC
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know