Seasonal effect on the accuracy of land use/land cover classification in the Bilate Sub-basin, Abaya-Chamo Basin, Rift Valley Lakes Basin of Ethiopia

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cg.coverage.countryEthiopia
cg.coverage.iso3166-alpha2ET
cg.coverage.regionEastern Africa
cg.coverage.subregionRift Valley Lakes Basin
cg.coverage.subregionAbaya-Chamo Basin
cg.coverage.subregionBilate Sub-Basin
cg.creator.identifierAlemseged Tamiru Haile: 0000-0001-8647-2188en
cg.identifier.iwmilibraryH050723en
cg.identifier.urlhttps://survey.amu.edu.et/ojs/index.php/EJWST/issue/view/87/Seasonal%20effect%20on%20the%20accuracy%20of%20Land%20use%20Land%20cover%20classification%20in%20the%20Bilate%20Sub-basin%2C%20Abaya-Chamo%20Basin%2C%20Rift%20valley%20Lakes%20Basin%20of%20Ethiopiaen
cg.issn2220-7643en
cg.journalEthiopian Journal of Water Science and Technologyen
cg.reviewStatusPeer Reviewen
dc.contributor.authorYimer, A. K.en
dc.contributor.authorHaile, Alemseged Tamiruen
dc.contributor.authorHatiye, S. D.en
dc.contributor.authorAzeref, A. G.en
dc.date.accessioned2021-10-31T13:15:01Zen
dc.date.available2021-10-31T13:15:01Zen
dc.identifier.urihttps://hdl.handle.net/10568/115750
dc.titleSeasonal effect on the accuracy of land use/land cover classification in the Bilate Sub-basin, Abaya-Chamo Basin, Rift Valley Lakes Basin of Ethiopiaen
dcterms.abstractA correct and timely land use/land cover (LULC) classification provides indispensable information for the effective management of environmental and natural resources. However, earlier studies mapped the LULC map of Bilate Sub-basin using remote sensing images that were acquired for a single season. Hence, these studies did not consider the seasonal effects on the accuracy of LULC classification. Therefore, the objective of this study was to evaluate changes in classification accuracy for images acquired during wet and dry seasons in the Bilate Sub-basin. LULC of the study area was classified using the Landsat 8 satellite imageries. Based on field observations, we classified the LULC of the study area into 9 dominant classes. The classification for the two seasons resulted in a noticeable difference between the LULC composition of the study area because of seasonal differences in the classification accuracy. The overall accuracy of the LULC maps was 80%for the wet season and 90% for the dry season with Kappa coefficient values of 0.8 and 0.9 respectively. Therefore, the two seasons showed a significant difference in the overall accuracy of the classification. However, we discovered that when the classification accuracy was tested locally, that is for individual pixels, the results were not the same. In Bilate Sub-basin, several pixels (14.71%) were assigned to different LULC classes on the two seasons maps while 85.29% of the LULC classes remained unaltered in the two maps. According to the classification results, the season had a noticeable effect on the accuracy of LULC classification. This suggests that for LULC classification, multitemporal images should be used rather than a single remote sensing image.en
dcterms.accessRightsOpen Access
dcterms.bibliographicCitationYimer, A. K.; Haile, Alemseged Tamiru; Hatiye, S. D.; Azeref, A. G. 2020. Seasonal effect on the accuracy of land use/land cover classification in the Bilate Sub-basin, Abaya-Chamo Basin, Rift Valley Lakes Basin of Ethiopia. Ethiopian Journal of Water Science and Technology, 3:23-50.en
dcterms.extent3:23-50en
dcterms.issued2021-07-22en
dcterms.languageen
dcterms.licenseOther
dcterms.subjectland useen
dcterms.subjectland coveren
dcterms.subjectclassification systemsen
dcterms.subjectseasonal variationen
dcterms.subjectwet seasonen
dcterms.subjectdry seasonen
dcterms.subjectcultivated landen
dcterms.subjectagricultureen
dcterms.subjectwater resourcesen
dcterms.subjectforestsen
dcterms.subjectshrubsen
dcterms.subjectsettlementen
dcterms.subjectremote sensingen
dcterms.subjectlandsaten
dcterms.subjectsatellite imageryen
dcterms.typeJournal Article

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