标题: Construction of a neural network model for small-scale shaded relief maps constrained by topographic feature lines

作者: Wang, Y (Wang, Yue); Jiang, WP (Jiang, Wenping); Jiang, H (Jiang, Han); Dai, DF (Dai, Danfeng); Ma, PY (Ma, Peiyang); Wang, Y (Wang, Yuan); Wang, ZZ (Wang, Zhizhi)

来源出版物: GEOCARTO INTERNATIONAL 卷: 40 期: 1 文献号: 2459099 DOI: 10.1080/10106049.2025.2459099 Published Date: 2025 DEC 31

摘要: Traditional manual methods for generating shaded relief maps can effectively highlight major topographic structures but are time-consuming and require professional skills. Analytical shading methods are faster but often lead to maps overloaded with terrain details, obscuring key topographic features, especially in Small-Scale Shaded Relief Maps (SSSR-Maps). This study focuses on the relief shading of alpine canyon terrain, introduces topographic feature lines (TFLs) as constraints, and constructs a neural network model based on Pix2pixHD, namely, TFLC-CGAN. Two generation methods, TFLC-CGAN-E and TFLC-CGAN-M, are proposed and compared. Experimental results show that TFLC-CGAN can generate SSSR-Maps with manual shading styles, simplifying terrain while preserving key features. TFLC-CGAN-E adapts better to sharply reduced TFL density, while TFLC-CGAN-M excels in feature preservation. Additionally, the relationships among digital elevation model resolution, TFL density, and the generated shaded relief map scales are explored. The proposed TFLC-CGAN offers an efficient solution for large-scale production of SSSR-Maps.

作者关键词: Small-scale shaded relief map (SSSR-map); topographic feature lines (TFLs); neural network; terrain simplification

KeyWords Plus: TERRAIN REPRESENTATION; VISUALIZATION

地址: [Wang, Yue; Jiang, Wenping; Dai, Danfeng] Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Peoples R China.

[Jiang, Han] Case Western Reserve Univ, Sch Med, Cleveland, OH USA.

[Ma, Peiyang] China Univ Geosci, Sch Geog & Informat Engn, Wuhan, Peoples R China.

[Wang, Yuan] Big Data Ctr Geospatial & Nat Resources Qinghai Pr, Xining, Peoples R China.

[Wang, Zhizhi] Hubei Univ Technol, Sch Comp Sci, Wuhan, Peoples R China.

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

电子邮件地址: AndyJiang@whu.edu.cn

影响因子：3.3