太阳成8722(中国)有限公司-GREEN NO.1

标题:  A New Algorithm for Calculating the Flow Path Curvature (C) from the Square-Grid Digital Elevation Model (DEM)

作者: Qianjiao Wu, Yumin Chen *, Hongyan Zhou, Shujie Chen , Han Wang

来源出版物: ISPRS International Journal of Geo-Information   卷: 9  期:9 文献号:510   DOI: 10.3390/ijgi9090510    出版时间: 24 August 2020

摘要: This paper proposes a flow-path-network-based (FPN-based) algorithm, constructed from a square-grid digital elevation model (DEM) to improve the simulation of the flow path curvature (C). First, the flow-path network model was utilized to obtain an FPN. Then, a flow-path-network-flow-path-curvature (FPN-C) algorithm was proposed to estimate C from the FPN. The experiments consisted of two sections: (1) quantitatively evaluating the accuracy using 5 m DEMs generated from the mathematical ellipsoid and Gauss models, and (2) qualitatively assessing the accuracy using a 30 m DEM of a real-world complex region. The three algorithms proposed by Evans (1980), Zevenbergen and Throne (1987), and Shary (1995) were used to validate the accuracy of the new algorithm. The results demonstrate that the C value of the proposed algorithm was generally closer to the theoretical C value derived from two mathematical surfaces. The root mean standard error (RMSE) and mean absolute error (MAE) of the new method are 0.0014 and 0.0002 m, reduced by 42% and 82% of that of the third algorithm on the ellipsoid surface, respectively. The RMSE and MAE of the presented method are 0.0043 and 0.0025 m at best, reduced by up to 35% and 14% of that of the former two algorithms on the Gauss surface, respectively. The proposed algorithm generally produces better spatial distributions of C on different terrain surfaces.

作者关键词: digital elevation model (DEM); flow path curvature (C); flow-path-network-based (FPN-based); flow-path-network-flow-path-curvature (FPN-C); flow line

通讯作者: Yumin Chen, School of Resource and Environment Science, Wuhan University, 129 Luoyu Road, Wuhan 430079, China

电子邮件地址: ymchen@whu.edu.cn

影响因子：2.239