科研成果
沈意浪、艾廷华的论文在IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 刊出
发布时间:2022-01-05 10:08:13 发布者:易真 浏览次数:

标题: Multilevel Mapping From Remote Sensing Images: A Case Study of Urban Buildings

作者: Shen, YL (Shen, Yilang); Ai, TH (Ai, Tinghua); Chen, H (Chen, Hao); Li, JZ (Li, Jingzhong)

来源出版物: IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING: 60文献号: 5503016 DOI: 10.1109/TGRS.2021.3062751出版年: 2022

摘要: Remote sensing mapping plays an important role in understanding regional development and geographical environment characteristics. Traditional remote sensing mapping at different levels usually fails to consider the shape, quantity, distribution, and position features of map objects. Therefore, a multilevel representation of urban buildings is realized based on the proposed framework for multilevel mapping from remote sensing images. In this process, the Mask R-CNN method is first applied to extract buildings from remote sensing images. Then, the orthogonal shape features of the extracted buildings are reconstructed based on corner detection, and urban roads are generated by extracting the internal structural characteristics of urban buildings for further multilevel representation. Finally, three innovative raster-based generalization algorithms, including simplification, aggregation, and typification based on Hough line detection technology, are developed for a multilevel representation of urban buildings. The experimental results reveal that the proposed methods can effectively realize multilevel mapping of urban buildings from remote sensing images while meeting basic cartographic requirements.

入藏号: WOS:000728266600082

语言: English

文献类型: Article

作者关键词: Buildings; Remote sensing; Feature extraction; Image reconstruction; Shape; Sensors; Roads; Hough line detection; Mask R-CNN; multilevel mapping; remote sensing images; urban buildings

KeyWords Plus: MAP GENERALIZATION; SIMPLIFICATION; AGGREGATION; LINES

地址: [Shen, Yilang; Ai, Tinghua; Chen, Hao; Li, Jingzhong] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Peoples R China.

通讯作者地址: Ai, TH (通讯作者)Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430072, Peoples R China.

电子邮件地址:tinghuaai@whu.edu.cn

影响因子:5.6

信息服务
学院网站教师登录 学院办公电话 学校信息门户登录

版权所有 © 开云电竞官方网
地址:湖北省武汉市珞喻路129号 邮编:430079 
电话:027-68778381,68778284,68778296 传真:027-68778893 邮箱:easylangar.com

Baidu
map