A Review of Digital Elevation Model Super Resolution

• Author(s): Musa Muhammad Chindo
• Paper ID: 1712040
• Page: 861-879
• Published Date: 14-11-2025
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 5 November-2025

Abstract

High-resolution (HR) digital elevation models (DEMs) have been found to be critical for many applications, as they provide accurate basic geodata, as well as more information and accurate results. However, despite the importance of HR DEM, many areas across the world, particularly in developing countries, lack access to them. Thus, researchers inspired by the success of super resolution (SR) on image enhancement, especially the use of deep learning (DL) approaches, instead of using high-precision equipment to obtain HR DEMs, have recently presented and are discussing the concept of DEM SR. This paper provides a review of such a DEM SR technique. It first explains the basic idea of SR, then describes DEM SR, and finally, a review of DEM SR algorithms proposed in the literature is presented, describing the main approaches and some of the shortcomings. This review shall provide the geoscientific community with information on an emerging alternative technique for acquiring HR DEM that is more cost-effective and can contribute to open data, which is widely recognised as the key engine for achieving the Sustainable Development Goals (SDGs).

Keywords

DEM, High Resolution, Low Resolution, Super Resolution, Machine Learning, Deep Learning.

Citations

IRE Journals:
Musa Muhammad Chindo "A Review of Digital Elevation Model Super Resolution" Iconic Research And Engineering Journals Volume 9 Issue 5 2025 Page 861-879 https://doi.org/10.64388/IREV9I5-1712040

IEEE:
Musa Muhammad Chindo "A Review of Digital Elevation Model Super Resolution" Iconic Research And Engineering Journals, 9(5) https://doi.org/10.64388/IREV9I5-1712040