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dc.contributor.authorMoomen, A.W.
dc.contributor.authorYevugah, L.L
dc.contributor.authorBoakye, L.
dc.contributor.authorOsei, J.D.
dc.contributor.authorMuthoni, F.
dc.date.accessioned2024-04-08T09:13:50Z
dc.date.available2024-04-08T09:13:50Z
dc.date.issued2024-03-29
dc.identifier.citationMoomen, A.W., Yevugah, L.L., Boakye, L., Osei, J.D. & Muthoni, F. (2024). Review of Applications of Remote Sensing towards Sustainable Agriculture in the Northern Savannah Regions of Ghana. Agriculture, 14:(4), 546, 2-22.
dc.identifier.issn2077-0472
dc.identifier.urihttps://hdl.handle.net/20.500.12478/8459
dc.description.abstractThis paper assesses evidence-based applications of Remote Sensing for Sustainable and Precision Agriculture in the Northern Savanna Regions of Ghana for three decades (1990–2023). During this period, there have been several government policy intervention schemes and pragmatic support actions from development agencies towards improving agriculture in this area with differing level of success. Over the same period, there have been dramatic advances in remote sensing (RS) technologies with tailored applications to sustainable agriculture globally. However, the extent to which intervention schemes have harnessed the incipient potential of RS for achieving sustainable agriculture in the study area is unknown. To the best of our knowledge, no previous study has investigated the synergy between agriculture policy interventions and applications of RS towards optimizing results. Thus, this study used systematic literature review and desk analysis to identify previous and current projects and studies that have applied RS tools and techniques to all aspects of agriculture in the study area. Databases searched include Web of Science, Google Scholar, Scopus, AoJ, and PubMed. To consolidate the gaps identified in the literature, ground-truthing was carried out. From the 26 focused publications found on the subject, only 13 (54%) were found employing RS in various aspects of agriculture observations in the study area. Out of the 13, 5 studies focused on mapping the extents of irrigation areas; 2 mapped the size of crop and pasturelands; 1 focused on soil water and nutrient retention; 1 study focused on crop health monitoring; and another focused on weeds/pest infestations and yield estimation in the study area. On the type of data, only 1 (7%) study used MODIS, 2 (15%) used ASTER image, 1 used Sentinel-2 data, 1 used Planetscope, 1 used IKONOS, 5 used Landsat images, 1 used Unmanned Aerial Vehicles (UAVs) and another 1 used RADAR for mapping and monitoring agriculture activities in the study area. There is no evidence of the use of LiDAR data in the area. These results validate the hypothesis that failing agriculture in the study area is due to a paucity of high-quality spatial data and monitoring to support informed farm decision-making.
dc.description.sponsorshipDonors
dc.format.extent2-22
dc.language.isoen
dc.subjectagriculture
dc.subjectsustainable agriculture
dc.subjectfarming
dc.titleReview of Applications of Remote Sensing towards Sustainable Agriculture in the Northern Savannah Regions of Ghana
dc.typeArticle
cg.contributor.crpMaize
cg.contributor.affiliationInternational Institute of Tropical Agriculture
cg.coverage.regionAfrica
cg.coverage.countryGhana
cg.coverage.countryKenya
cg.coverage.countryNigeria
cg.coverage.hubEastern Africa Hub
cg.researchthemeBiometrics
cg.isijournalISI Journal
cg.authorship.typesCGIAR and developing country institute
cg.iitasubjectAgronomy
cg.iitasubjectBiometrics
cg.iitasubjectFood Security
cg.iitasubjectMaize
cg.journalAgriculture
cg.notesOpen Access Journal
cg.accessibilitystatusOpen Access
cg.reviewstatusPeer Review
cg.usagerightslicenseCreative Commons Attribution 4.0 (CC BY 0.0)
cg.targetaudienceScientists
cg.identifier.doihttps://doi.org/10.3390/agriculture14040546
cg.iitaauthor.identifierAbdul-Wadood Moomen: 0000-0002-6842-5078
cg.iitaauthor.identifierLily Lisa Yevugah: 0000-0002-0242-6158
cg.iitaauthor.identifierLouvis Boakye: 0000-0002-1426-9081
cg.iitaauthor.identifierFrancis: 0000-0001-6785-0550
cg.futureupdate.requiredNo
cg.identifier.issue4
cg.identifier.volume14


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