Using music and music‐based analysis to model and to classify terrain in geomorphology

Author:

Lin Siwei1ORCID,Yu Yang1,Chen Nan23,Shen Rui4,Wang Xianyan1

Affiliation:

1. School of Geography and Ocean Science Nanjing University Nanjing China

2. Key Laboratory of Spatial Data Mining and Information Sharing, Ministry of Education Fuzhou University Fuzhou China

3. The Academy of Digital China (Fujian) Fuzhou University Fuzhou China

4. Portland Institute Nanjing University of Posts and Telecommunications Nanjing China

Abstract

AbstractMusic has long served as a bridge between science and nature, allowing for the artistic expression of natural and human‐made phenomena. While music has been used in geomorphology as an engaging teaching strategy, its application in specific scientific inquiries within geomorphology remains relatively unexplored. Drawing on the morphological similarities between music and terrain relief, this work introduced a novel music‐based method for modelling and expressing terrain relief based on the drainage basin profile (DBP). It converts terrain relief into pitches and time values according to mapping rules and then describes terrain relief in an audible form. Based on 5 sample areas and 360 drainage basins on the Loess Plateau, we developed the application of the proposed method on four core geomorphic tasks, including landform interpretation, analysis, recognition and classification. Experimental results show that (1) terrain music can interpret the terrain relief and landform evolution processes through its musical structure and rhythmic variations; (2) music derivatives are related to different terrain features, such as terrain relief, terrain variation intensity, landform evolution degree and terrain complexity, and have a well‐functioning relationship with a series of conventional terrain derivatives; (3) leveraging machine learning techniques, the terrain music method is effective for landform recognition, achieving an overall accuracy of 88.85% and a mean accuracy of 88.85%; and (4) via a case study in Northern Shaanxi, music modelling successfully divided it into 12 distinct landform regions and 8 landform types. Different landform regions exhibit clear regional boundaries and gradual transition zones, while specific landform regions share prominent terrain, spatial clustering and landform processes. Our delineation provides reasonable and effective landform differentiation but captures additional bed‐rock mountain features compared with a traditional method. This study highlights that music is not only an artistic expression but also a valuable research paradigm for a wide range of geomorphic tasks, offering fresh perspectives and enhancing our understanding of loess landforms. The results show a promising effort to integrate music theory into practical geomorphic tasks, demonstrating the potential of using music as a medium for conveying and analysing spatial information in geomorphology.

Funder

Natural Science Foundation of Fujian Province

Publisher

Wiley

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