A review of fusion framework using optical sensors and Synthetic Aperture Radar imagery to detect and map land degradation and sustainable land management in the semi-arid regions

dc.contributor.authorSengani, David
dc.contributor.authorRamoelo, Abel
dc.contributor.authorArcher, Emma Rosa Mary
dc.date.accessioned2023-11-27T11:02:37Z
dc.date.available2023-11-27T11:02:37Z
dc.date.issued2023
dc.description.abstractThis paper examines a feature-level fusion framework for detecting and mapping land degradation (LD) and enabling sustainable land management (SLM) in semi-arid areas using optical sensors and Synthetic Aperture Radar (SAR) satellite data. The objectives of this review were to (i) determine the trends and geographical location of land degradation mapping publications, (ii) to identify and report current challenges pertaining to mapping LD using multiscale remote sensing data, (iii) to recommend a way forward for monitoring LD using multiscale remote sensing data. The study reviewed 78 peer-reviewed research articles published over the past 24 years (1998–2022). Image fusion has the potential to be more useful in various remote sensing applications than individual sensor image data, making it more informative and valuable in the interpretation process. In addition, this review discusses the importance of SAR and optical image fusion, pixel-level techniques, applications, and major classes of quality metrics for objectively assessing fusion performance. The literature review alluded that the SAR and optical image fusion in the detection and mapping of land degradation and enabling sustainable land management has not been fully explored. Advanced techniques such as the fusion of SAR and optical satellite imageries need to be incorporated for the detection and mapping of LD, as well as the promotion of SLM in halting LD in South African drylands and around the world. We conclude that there is scope for further research on the fusion of SAR and optical images, as new micro-wave and optical sensors with higher resolution are introduced on a regular basis. The results of this review contribute to a better understanding of the applications of SAR and optical image fusion in future research in the severely degraded drylands of southern Africa.en_US
dc.description.departmentGeography, Geoinformatics and Meteorologyen_US
dc.description.librarianhj2023en_US
dc.description.sdgSDG-02:Zero Hungeren_US
dc.description.sdgSDG-15:Life on landen_US
dc.description.urihttps://www.tandfonline.com/loi/tgei20en_US
dc.identifier.citationDavid Sengani, Abel Ramoelo & Emma Archer (2023) A review of fusion framework using optical sensors and Synthetic Aperture Radar imagery to detect and map land degradation and sustainable land management in the semi-arid regions, Geocarto International, 38:1, 2278325, DOI: 10.1080/10106049.2023.2278325.en_US
dc.identifier.issn1010-6049 (print)
dc.identifier.issn1752-0762 (online)
dc.identifier.other10.1080/10106049.2023.2278325
dc.identifier.urihttp://hdl.handle.net/2263/93467
dc.language.isoenen_US
dc.publisherTaylor and Francisen_US
dc.rights© 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/ licenses/by/4.0).en_US
dc.subjectRemote sensingen_US
dc.subjectSynthetic aperture radar (SAR)en_US
dc.subjectSentinel-1en_US
dc.subjectLandsat 8. Land degradationen_US
dc.subjectSDG-02: Zero hungeren_US
dc.subjectSDG-15: Life on landen_US
dc.subjectSustainable land management (SLM)en_US
dc.titleA review of fusion framework using optical sensors and Synthetic Aperture Radar imagery to detect and map land degradation and sustainable land management in the semi-arid regionsen_US
dc.typeArticleen_US

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