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

Simple item page
dc.contributor.authorOkolie, Chukwuma
dc.contributor.authorSmit, Julian
dc.date.accessioned2022-04-08T09:50:28Z
dc.date.available2022-04-08T09:50:28Z
dc.date.issued2022-04-06
dc.description.abstractThe 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.en_US
dc.identifier.apacitationOkolie, C., & Smit, J. (2022). A systematic review and meta-analysis of Digital elevation model (DEM) fusion: pre-processing, methods and applications. <i>ISPRS Journal of Photogrammetry and Remote Sensing</i>, 188(June 2022), 1-29. http://hdl.handle.net/11427/36298en_ZA
dc.identifier.chicagocitationOkolie, Chukwuma, and Julian Smit "A systematic review and meta-analysis of Digital elevation model (DEM) fusion: pre-processing, methods and applications." <i>ISPRS Journal of Photogrammetry and Remote Sensing</i> 188, June 2022. (2022): 1-29. http://hdl.handle.net/11427/36298en_ZA
dc.identifier.citationOkolie, C. & Smit, J. 2022. A systematic review and meta-analysis of Digital elevation model (DEM) fusion: pre-processing, methods and applications. <i>ISPRS Journal of Photogrammetry and Remote Sensing.</i> 188(June 2022):1-29. http://hdl.handle.net/11427/36298en_ZA
dc.identifier.ris TY - Journal Article AU - Okolie, Chukwuma AU - Smit, Julian AB - 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. DA - 2022-04-06 DB - OpenUCT DP - University of Cape Town IS - June 2022 J1 - ISPRS Journal of Photogrammetry and Remote Sensing KW - Digital elevation model fusion KW - Remote sensing image fusion KW - Data fusion KW - Multi-sensor fusion KW - InSAR KW - LiDAR KW - Weight maps LK - https://open.uct.ac.za PY - 2022 T1 - A systematic review and meta-analysis of Digital elevation model (DEM) fusion: pre-processing, methods and applications TI - A systematic review and meta-analysis of Digital elevation model (DEM) fusion: pre-processing, methods and applications UR - http://hdl.handle.net/11427/36298 ER - en_ZA
dc.identifier.urihttps://doi.org/10.1016/j.isprsjprs.2022.03.016
dc.identifier.urihttp://hdl.handle.net/11427/36298
dc.identifier.vancouvercitationOkolie C, Smit J. A systematic review and meta-analysis of Digital elevation model (DEM) fusion: pre-processing, methods and applications. ISPRS Journal of Photogrammetry and Remote Sensing. 2022;188(June 2022):1-29. http://hdl.handle.net/11427/36298.en_ZA
dc.language.isoenen_US
dc.publisher.departmentDivision of Geomaticsen_US
dc.publisher.facultyFaculty of Engineering and the Built Environmenten_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.sourceISPRS Journal of Photogrammetry and Remote Sensingen_US
dc.sourceISPRS Journal of Photogrammetry and Remote Sensing
dc.source.journalissueJune 2022en_US
dc.source.journalvolume188en_US
dc.source.pagination1-29en_US
dc.source.urihttps://www.sciencedirect.com/journal/isprs-journal-of-photogrammetry-and-remote-sensing
dc.subjectDigital elevation model fusionen_US
dc.subjectRemote sensing image fusionen_US
dc.subjectData fusionen_US
dc.subjectMulti-sensor fusionen_US
dc.subjectInSARen_US
dc.subjectLiDARen_US
dc.subjectWeight mapsen_US
dc.titleA systematic review and meta-analysis of Digital elevation model (DEM) fusion: pre-processing, methods and applicationsen_US
dc.typeJournal Articleen_US
Files
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.72 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
Journal Articles