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Landsat-based approaches for mapping of land degradation prevalence and soil functional properties in Ethiopia
Abstract
Agriculture is the basis of the Ethiopian economy, accounting for the majority of its employment and export earnings. Land degradation is, however, widespread and improved targeting of land management interventions is needed, taking into account the variability of soil properties that affect agricultural productivity and land degradation risk across landscapes. In the current study we demonstrate the utility of Landsat ETM+imagery for landscape-level assessments of land degradation risk and soil condition through a combination of systematic field methodologies, infrared (IR) spectroscopy and ensemble modeling techniques. The approaches presented allow for the development of maps at spatial scales that are appropriate for making spatially explicit management recommendations. Field data and soil samples collected from 38 sites, each 100km2, were used to develop predictive models that were applied as part of a case study to an independent dataset from four sites in Ethiopia. The predictions based on Landsat reflectance were robust, with R-squared values of 0.86 for pH and 0.79 for soil organic carbon (SOC), and were used to create predicted surfaces (maps) for these soil properties. Further, models were developed for the mapping of the occurrence of soil erosion and root depth restrictions within 50cm of the soil surface (RDR50), with an accuracy of about 80% for both variables. The maps generated from these models were used to assess the spatial distribution of soil pH and SOC, which are important indicators of soil condition, and land degradation risk factors in order to target relevant management options.
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“Recently developed sensor-based approaches show promise to expand soil quality assessment to the landscape level (e.g. Vågen et al., 2013).”
From Soil quality – A critical review (2018) · cites this paper as Vågen et al., 2013
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Konra, N., Kalambukattu, J. G., & Kumar, S. (2026) · Journal of the Indian Society of Remote Sensing · doi:10.1007/s12524-026-02517-8 · Cited by 1
STUDY ON THE MAIN FACTORS AFFECTING SOIL FERTILITY AND IMPROVEMENT PATHWAYS IN HENAN PROVINCE, CHINA
ZHA, L. S., Wang, W., Zhong, J., & Su, Y. (2025) · Applied Ecology and Environmental Research · doi:10.15666/aeer/2306_1081910839 · Cited by 1
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Metadata
- Authors
- Vågen, T.-G., Winowiecki, L. A., Abegaz, A., & Hadgu, K. M.
- Affiliations
- World Agroforestry Centre (KE)
- International Center for Tropical Agriculture (KE)
- Addis Ababa University (ET)
- Corresponding author
- Vågen, Tor-G.
- Venue
- Remote Sensing of Environment
- Publisher
- Elsevier BV
- Published
- 2013-07
- Volume
- 134
- Pages
- 266-275
- ISSN
- 0034-4257 (ISSN-L)
- OpenAlex
- W2068967960
- Cited by
- 109
- References
- 77
- Citations by year
- 2026: 12 · 2025: 6 · 2024: 8 · 2023: 7 · 2022: 3 · 2021: 11 · 2020: 10 · 2019: 7 · 2018: 14 · 2017: 9 · 2016: 7 · 2015: 11 · 2014: 3 · 2013: 1
- FWCI
- 6.08
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Remote Sensing of Environment (publishedVersion)
- Funders
- Bill and Melinda Gates Foundation
- Topics
- Life Sciences › Agricultural and Biological Sciences › Soil Science › Soil Geostatistics and Mapping
- Physical Sciences › Environmental Science › Ecology › Remote Sensing in Agriculture
- Life Sciences › Agricultural and Biological Sciences › Soil Science › Soil erosion and sediment transport
- Keywords
- land degradation, soil pH, soil organic carbon, soil erosion, Landsat Enhanced Thematic Mapper, infrared spectroscopy, ensemble learning, Ethiopia
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