期刊：
ISPRS International Journal of Geo-Information,2022年11(5):281- ISSN：2220-9964
通讯作者：
Chang Ren
作者机构：
[Shao, Shiwei] Cent China Normal Univ, Natl Res Ctr Cultural Ind, Wuhan 430070, Peoples R China.;[Shao, Shiwei] Zhongzhi Software Technol Co Ltd, Wuhan 430010, Peoples R China.;[Yu, Mengting] Shenzhen Longgang Dist Urban Planning & Land Reso, Shenzhen 518172, Peoples R China.;[Huang, Yimin] Chinese Acad Sci, Inst Elect Engn, Beijing 100190, Peoples R China.;[Tian, Jing; Wang, Yiheng] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.
通讯机构：
[Chang Ren] C;College of Air Traffic Management, Civil Aviation Flight University of China, Guanghan 618307, China<&wdkj&>Author to whom correspondence should be addressed.
关键词：
landscape metric;urban land use;correlation analysis;factor analysis;vector data
摘要：
In this study, we investigate the urban landscape patterns in Wuhan, China based on the land use data in the vector format. Using the approach of landscape metric analysis, we calculate forty-four vector-based landscape metrics and then reduce redundant ones through a combination of Spearman correlation analysis and factor analysis, in order to extract a core set of characterizing landscape metrics. We find that the urban landscape can be depicted by six factors including the overall shape and diversity, mean proximity, overall area variation, fragmentation variation, elongation variation, and mean shape complexity. After analyzing typical patterns indicated by the core metrics and the spatial distribution of land use patterns, we compare our findings with other studies and discuss how the core metrics coincide and differ.
作者机构：
[Long, Ting] Univ Turku, Turku Sch Econ, Turku, Finland.;[Long, Ting] Cent China Normal Univ, Natl Res Ctr Cultural Ind, Wuhan, Peoples R China.
会议名称：
9th International Conference on Well-Being in the Information Society (WIS)
会议时间：
AUG 25-26, 2022
会议地点：
Turku, FINLAND
会议主办单位：
[Long, Ting] Univ Turku, Turku Sch Econ, Turku, Finland.^[Long, Ting] Cent China Normal Univ, Natl Res Ctr Cultural Ind, Wuhan, Peoples R China.
会议论文集名称：
Communications in Computer and Information Science
关键词：
Mobile applications;Theme park;User engagement;Uses and gratification
作者机构：
[Shao, Shiwei; Shao, SW] Cent China Normal Univ, Natl Res Ctr Cultural Ind, Wuhan 430056, Peoples R China.;[Shao, Shiwei; Shao, SW] Zhongzhi Software Technol Co Ltd, Wuhan 430013, Peoples R China.;[Xiao, Lixia] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China.;[Xiao, Lixia] Wuhan Nat Resources & Planning Informat Ctr, Wuhan 430014, Peoples R China.;[Tian, Jing; Lin, Liupeng] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.
通讯机构：
[Shao, SW ] C;Cent China Normal Univ, Natl Res Ctr Cultural Ind, Wuhan 430056, Peoples R China.;Zhongzhi Software Technol Co Ltd, Wuhan 430013, Peoples R China.
摘要：
Roads are closely related to people’s lives, and road network extraction has become one of the most important remote sensing tasks. This study aimed to propose a road extraction network with an embedded attention mechanism to solve the problem of automatic extraction of road networks from a large number of remote sensing images. Channel attention mechanism and spatial attention mechanism were introduced to enhance the use of spectral information and spatial information based on the U-Net framework. Moreover, residual densely connected blocks were introduced to enhance feature reuse and information flow transfer, and a residual dilated convolution module was introduced to extract road network information at different scales. The experimental results showed that the method proposed in this study outperformed the compared algorithms in overall accuracy. This method had fewer false detections, and the extracted roads were closer to ground truth. Ablation experiments showed that the proposed modules could effectively improve road extraction accuracy.
