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Cited by 109Soil Geostatistics and MappingRemote Sensing in AgricultureSoil erosion and sediment transport

The DOI matches its Crossref record; 72 of the 77 references it cites were found in a registry or an index.

Landsat-based approaches for mapping of land degradation prevalence and soil functional properties in Ethiopia

Vågen, Tor-G., Winowiecki, Leigh A., Abegaz, Assefa, Hadgu, Kiros M.·2013·Remote Sensing of Environment
DOI 10.1016/j.rse.2013.03.006
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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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Crossref · 10.1016/j.rse.2013.03.006

Cites

72 of 72 references verified0 citation errors · 0 not checkable

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  • Recently developed sensor-based approaches show promise to expand soil quality assessment to the landscape level.

    “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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5 of the 77 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

  1. Wischmeier, 1962, Soil-loss estimation as a tool in soil and water management planning, International Association of Scientific Hydrology Publication, 59, 148

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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.
ORCID
Venue
Remote Sensing of Environment
Publisher
Elsevier BV
Published
2013-07
Volume
134
Pages
266-275
ISSN
0034-4257 (ISSN-L)
DOI
10.1016/j.rse.2013.03.006
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
Licence
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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