E3S Web Conf.
Volume 206, 20202020 2nd International Conference on Geoscience and Environmental Chemistry (ICGEC 2020)
|Number of page(s)||5|
|Section||Earth Geological Energy Mining And Landform Protection|
|Published online||11 November 2020|
Study of energy-efficient architecture address utilizing topography and geomorphology based on Google Earth and its remote sensing data
Northeast Yucai school, Shenyang, China, 214191
* Corresponding author: firstname.lastname@example.org
In this paper, we describe the formatting guidelines for ACM SIG Proceedings. With the development of social economy, smart cities, especially green energy-saving buildings, are foremost trend in the future. The location of green buildings has a very important impact on the design and plan of future smart cities. The influence of the natural environment, especially that of the topography and landform on the location of architectural design is very significant. Google Earth (GE) platform can provide sufficient remote sensing data, which greatly interpret and promote surface information. However, just few people have done related research. This article takes Beijing as an example and uses Google Earth platform and the remote sensing data to obtain the 3D digital elevation model (DEM) data; and then Google earth’s geomorphology data are used to analyze the landform features. Finally, by analyzing their characteristics and distribution features, five energy-saving building locations were selected in Beijing. It can be concluded that GE, is an effective and potential platform for providing remote sensing data, and analyzing the DEM and landform. The rational analysis of the building addresses in this paper could help the buildings to avoid potential geological disasters and make full use of natural resources. Moreover, this research on energyefficient building addresses make a suggestion for future smart city planning.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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