Towards the next generation of digital terrain modelling and analysis: New value-added perspective for geoscience
Year: 2025
Type: article
Abstract: Digital terrain modelling and analysis play critical roles in geoscientific research, which underpins the understanding of Earth's surface dynamics and processes. Traditional digital elevation models (DEMs) capture the geometric characteristics of the Earth's surface at a specific time, providing limited insights into the underlying geomorphological processes. To address these limitations, this study proposes the concept of value-added digital terrain, which extends elevation-only DEMs by integrating multidimensional information such as temporal dynamics, spatial relationships, and geomorphological attributes. The proposed framework encompasses quality enhancement methods, multidimensional information integration, and process-based dynamic modelling. Quality enhancement is achieved through a comprehensive framework involving positional accuracy improvement, terrain feature enhancement, spatial relationship optimization, and regional morphology reconstruction. Enrichment with multidimensional information, including temporal and spatial dimension extensions, object and morphological feature integrations, and attribute augmentation, allows for a deeper exploration of terrain processes and mechanisms. Finally, the paper highlights the significance of transitioning from morphological representation to process-oriented analysis, emphasizing the necessity for future digital terrain analysis to evolve towards dynamic, multidimensional, and globally applicable frameworks. • A novel value-added framework for digital terrain modelling and analysis. • Incorporates innovative quality enhancement techniques to improve DEMs. • Providing process-oriented digital terrain analysis to support geomorphological studies.
Source: Information Geography
Language: English
Subfield: Ocean Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $2,200
Awards: G1078678516, G1324817374, G7776299137
OpenAlex ID: W4409708507
