Reference soil groups map of Ethiopia based on legacy data and machine learning-technique: EthioSoilGrids 1.0

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dc.creatorAli, Ashenafi
dc.creatorTadesse, Solomon
dc.creatorWolde, Yitbarek
dc.creatorGudeta, Kiflu
dc.creatorAbera, Wuletawu
dc.creatorMesfin, Ephrem
dc.creatorMekete, Terefe
dc.creatorHaile, Mitiku
dc.creatorHaile, Wondwosen
dc.creatorAbegaz, Assefa
dc.creatorTafesse, Demeke
dc.creatorBelay, Gebeyhu
dc.creatorGetahun, Mekonen
dc.creatorBeyene, Sheleme
dc.creatorAssen, Mohamed
dc.creatorRegassa, Alemayehu
dc.creatorSelassie, Yihenew G.
dc.creatorAbebe, Dawit
dc.creatorSchulz, Steffen
dc.creatorErkossa, Teklu
dc.creatorHussien, Nesru
dc.creatorYirdaw, Abebe
dc.creatorMera, Addisu
dc.creatorAdmas, Tesema
dc.creatorWakoya, Feyera
dc.creatorLegesse, Awgachew
dc.creatorTessema, Nigat
dc.creatorAbebe, Ayele
dc.creatorGebremariam, Simret
dc.creatorAregaw, Yismaw
dc.creatorAbebaw, Bizuayehu
dc.creatorBekele, Damtew
dc.creatorZewdie, Eylachew
dc.creatorTamene, Lulseged D.
dc.creatorElias, Eyasu
dc.date2024-03-05
dc.date2024-05-17T07:38:21Z
dc.date2024-05-17T07:38:21Z
dc.date.accessioned2026-06-27T13:24:23Z
dc.descriptionUp-to-date digital soil resource information and its comprehensive understanding are crucial to supporting crop production and sustainable agricultural development. Generating such information through conventional approaches consumes time and resources, and is difficult for developing countries. In Ethiopia, the soil resource map that was in use is qualitative, dated (since 1984), and small scaled (1 : 2 M), which limit its practical applicability. Yet, a large legacy soil profile dataset accumulated over time and the emerging machine-learning modeling approaches can help in generating a high-quality quantitative digital soil map that can provide better soil information. Thus, a group of researchers formed a Coalition of the Willing for soil and agronomy data-sharing and collated about 20 000 soil profile data and stored them in a central database. The data were cleaned and harmonized using the latest soil profile data template and 14 681 profile data were prepared for modeling. Random forest was used to develop a continuous quantitative digital map of 18 World Reference Base (WRB) soil groups at 250 m resolution by integrating environmental covariates representing major soil-forming factors. The map was validated by experts through a rigorous process involving senior soil specialists or pedologists checking the map based on purposely selected district-level geographic windows across Ethiopia. The map is expected to be of tremendous value for soil management and other land-based development planning, given its improved spatial resolution and quantitative digital representation.
dc.formatapplication/pdf
dc.identifierhttps://hdl.handle.net/10568/141878
dc.identifier.urihttp://hdl.handle.net/123456789/58396
dc.languageen
dc.publisherCopernicus Publications
dc.rightsOpen Access
dc.sourceAli, A.; Tadesse, S.; Wolde, Y.; Gudeta, K.; Abera, W.; Mesfin, E.; Mekete, T.; Haile, M.; Haile, W.; Abegaz, A.; Tafesse, D.; Belay, G.; Getahun, M.; Beyene, S.; Assen, M.; Regassa, A.; Selassie, Y.G.; Abebe, D.; Schulz, S.; Erkossa, T.; Hussien, N.; Yirdaw, A.; Mera, A.; Admas, T.; Wakoya, F.; Legesse, A.; Tessema, N.; Abebe, A.; Gebremariam, S.; Aregaw, Y.; Abebaw, B.; Bekele, D.; Zewdie, E.; Tamene, L.; Elias, E. (2024) Reference soil groups map of Ethiopia based on legacy data and machine learning-technique: EthioSoilGrids 1.0. Soil 10(1): p. 189-209. ISSN: 2199-398X
dc.subjectsoil types
dc.subjectsoil
dc.subjectmaps
dc.titleReference soil groups map of Ethiopia based on legacy data and machine learning-technique: EthioSoilGrids 1.0
dc.typeJournal Article

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