E3S Web Conf.
Volume 131, 20192nd International Conference on Biofilms (ChinaBiofilms 2019)
|Number of page(s)
|19 November 2019
Impervious surface extraction of multi-source high-resolution images in 2018 in Anhui Province
Anhui Xinhua University, Hefei, 230088, China
2 School of Surveying and Mapping Science and Engineering, Shandong University of Science and Technology, Qingdao 266510, China
3 School of Civil Engineering and Architecture, Shandong University of Technology, Zibo, Shandong 255000, China
* Corresponding author: firstname.lastname@example.org
With the development of the economy and the continuous improvement of social demand, the impervious area is more and more representative of the urbanization process and economic development level of the society. Anhui Province is a big province, and the impervious information is an essential element for an accurate understanding of economic development. To accurately understand the impervious surface and economic development level of Anhui Province, this study selects the training samples of Anhui province, trains the classifier, uses the classification algorithm of support vector machine, combines 2018 Sentinel-2 and Landsat8 in Matlab, and uses the LUOJIA-1 nighttime light data as auxiliary. The data was used to make land use planning maps for forests, farmland, impervious surfaces and water bodies in Anhui Province, and then the impervious information of the province in Anhui Province was extracted with high precision in 2018. Compared with the results of Sentinel-2&LUOJIA-1 and Landsat8&LUOJIA-1, it is proved that the combination of Sentinel-2, Landsat8 and LUOJIA-1 data can extract impervious information with high accuracy and high precision.
© The Authors, published by EDP Sciences, 2019
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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