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Land use and land cover dynamics in dryland ecosystem of Northwestern Ethiopia: taking into account uncertainties and correcting bias in satellite-based maps
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  • Published: 18 February 2026

Land use and land cover dynamics in dryland ecosystem of Northwestern Ethiopia: taking into account uncertainties and correcting bias in satellite-based maps

  • Amsalu Abich1,2,
  • Mesele Negash1,4,
  • Temesgen Gashaw Tarkegn3,5 &
  • …
  • Asmamaw Alemu2 

Scientific Reports , Article number:  (2026) Cite this article

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We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Ecology
  • Environmental sciences

Abstract

Information on Land use and land cover (LULC) dynamics is crucial for environmental change studies. Remote sensing offers option for monitoring multitemporal LULC dynamics. However, remote sensing-based LULC maps include classification errors that may have effect on area estimates. A variety of area estimators have been developed to correct the errors despite they have not been fully utilized. The study investigated spatiotemporal LULC dynamics that account bias and uncertainty analysis in dry woodlands of Northwestern Ethiopia. Reference data were collected from Google Earth for classification and accuracy assessment. Then, a random forest model was used to produce LULC maps of 1986‒2019 with the overall accuracies ranged from 92.0 to 97.8%. A stratified estimator was used to estimate a bias-adjusted area with its uncertainty using reference data. The result indicated the bias-adjusted area estimates of LULC class had minor uncertainty ranged 0‒13.0%. Cropland substantially increased by 116.8%, while grassland and woodland decreased by 59.1 and 24.7%, respectively between 1986 and 2019. However, woodland and forest gained 21.4 and 24.0% between 2000 and 2010 and 2010 and 2019, respectively. There was insignificant difference between the mapped area and the corresponding bias-adjusted area estimates, with a relative error ranged from ‒6.7 to 4.3%. Despite these, errors in maps were somehow critical, accounting for significant variation in the estimations of some classes. The study highlighted the importance of reference data to produce robust estimates along with spatially explicit maps. Landscapes of the study area have experienced widespread LULC changes requiring strategy that properly manage woodland ecosystems.

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Data availability

All datasets used and/or analysed during this study are included in this published article and its supplementary information files.

Abbreviations

CI:

Confidence intervals

FAO:

Food and agricultural organization of the United Nation

IPCC:

Intergovernmental panel on climate change

LULC:

Land use and land cover

MEA:

Millennium ecosystem assessment

MEFCC:

Ministry of environment forest and climate change

MSAVI:

Modified soil adjusted vegetation index

NDVI:

Normalized difference vegetation index

REDD + :

Reducing emissions from deforestation and forest degradation

OWL:

Other woodland

RE:

Relative difference

SE:

Standard error

SM:

Supplementary materials

USGS:

United State geological survey

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Acknowledgements

We are deeply grateful to the following institutions for their many supports: College of Agriculture and Environmental Science, University of Gondar and Wondo Genet College of Forestry and Natural Resources, Hawassa University. We thank all individuals for their assistance in this study.

Funding

This study was supported by UK Research and Innovation (UKRI) through the Global Challenges Research Fund (GCRF) program, Grant Ref. ES/P011306/, under the project Social and Environmental Trade-offs in African Agriculture (SENTINEL) led by the International Institute for Environment and Development (IIED) in part implemented by the Regional Universities Forum for Capacity Building in Agriculture (RUFORUM); and Institutional Strengthening for the Forest Sector Development Program, Ministry of Environment, Forest and Climate Change.

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Authors and Affiliations

  1. Wondo Genet College of Forestry and Natural Resources, Hawassa University, P.O. Box 128, Shashemene, Ethiopia

    Amsalu Abich & Mesele Negash

  2. College of Agriculture and Environmental Sciences, University of Gondar, P.O. Box 196, Gondar, Ethiopia

    Amsalu Abich & Asmamaw Alemu

  3. College of Agriculture and Environmental Sciences, Bahir Dar University, P.O. Box 1289, Bahir Dar, Ethiopia

    Temesgen Gashaw Tarkegn

  4. European Forest Institute, Rome c/o CREA-IT, Via Manziana 30, 00189, Rome, Italy

    Mesele Negash

  5. College of Agriculture, Food and Natural Resources, Prairie View AM University, Prairie View, TX, 77446, USA

    Temesgen Gashaw Tarkegn

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Contributions

This work is part of a Ph.D. study of the first author. A.A. (Amsalu Abich): Conceptualization, methodology, software, validation, formal analysis, investigation, data curation, writing—original draft preparation, and writing—review and editing. M.N. (Mesele Negash): Conceptualization, methodology, and writing—review and editing. A.A. (Asmamaw Alemu): Conceptualization, methodology, and writing—review and editing. T.G. (Temsgen Gashaw): Conceptualization, methodology, and writing—review and editing. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Amsalu Abich.

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Abich, A., Negash, M., Tarkegn, T.G. et al. Land use and land cover dynamics in dryland ecosystem of Northwestern Ethiopia: taking into account uncertainties and correcting bias in satellite-based maps. Sci Rep (2026). https://doi.org/10.1038/s41598-026-39301-0

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  • Received: 24 November 2025

  • Accepted: 04 February 2026

  • Published: 18 February 2026

  • DOI: https://doi.org/10.1038/s41598-026-39301-0

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Keywords

  • LULC
  • Northwestern Ethiopia
  • Random forest
  • Remote sensing
  • Woodland
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