New high-fidelity terrain modeling method constrained by terrain semanteme

Area of Science:

• Geoinformatics
• Remote Sensing
• Geomorphometry

Background:

• Digital elevation models (DEMs) are crucial for space data infrastructure.
• Grid-based DEMs suffer from loss of terrain features, limiting their utility.
• Existing DEM definitions restrict their use in terrain modeling.

Purpose of the Study:

• To propose a novel concept, the terrain semanteme, for defining local terrain features.
• To design a new process for generating grid DEMs using terrain semantemes.
• To evaluate the effectiveness of the terrain semanteme approach in improving DEM fidelity and enabling distortion recovery.

Main Methods:

• Concept development of terrain semantemes for local feature definition.
• Design of a new DEM generation process incorporating terrain semantemes.
• Prototyping and experimental testing of the proposed approach.

Main Results:

• Terrain semantemes can be successfully integrated into DEM generation.
• The proposed concept significantly improves DEM fidelity.
• The terrain semanteme technique demonstrates good efficiency in recovering distorted DEM regions.

Conclusions:

• The terrain semanteme concept offers a valuable advancement for DEM production.
• This novel approach enhances the accuracy and reliability of digital elevation models.
• The technique shows promise for correcting and improving existing DEM datasets.