A systematic review and meta-analysis of Digital elevation model (DEM) fusion: pre-processing, methods and applications

Okolie, Chukwuma; Smit, Julian

A systematic review and meta-analysis of Digital elevation model (DEM) fusion: pre-processing, methods and applications

Journal Article

2022-04-06

Permanent link to this Item

https://doi.org/10.1016/j.isprsjprs.2022.03.016
http://hdl.handle.net/11427/36298

Authors

Okolie, Chukwuma

Smit, Julian

Journal Title

ISPRS Journal of Photogrammetry and Remote Sensing

Abstract

The remote sensing community has identified data fusion as one of the key challenging topics of the 21st century. The subject of image fusion in two-dimensional (2D) space has been covered in several published reviews. However, the special case of 2.5D/3D Digital Elevation Model (DEM) fusion has not been addressed till date. DEM fusion is a key application of data fusion in remote sensing. It takes advantage of the complementary characteristics of multi-source DEMs to deliver a more complete, accurate, and reliable elevation dataset. Although several methods for fusing DEMs have been developed, the absence of a well-rounded review has limited their proliferation among researchers and end-users. Combining knowledge from multiple studies is often required to inform a holistic perspective and guide further research. In response, this paper provides a systematic review of DEM fusion: the pre-processing workflow, methods and applications, enhanced with a meta-analysis. Through the discussion and comparative analysis, unresolved challenges and open issues are identified, and future directions for research are proposed. This review is a timely solution and an invaluable source of information for researchers within the fields of remote sensing and spatial information science, and the data fusion community at large.