Cited by 762Land Use and Ecosystem ServicesAgriculture, Land Use, Rural DevelopmentSoil erosion and sediment transport

The DOI matches its Crossref record; 71 of the 71 references it cites were found in a registry or an index; none of the 110 sources its claims cite is checked for support yet.

Mapping the world's degraded lands

Open access
Gibbs, H.K., Salmon, J.M.·2015·Applied Geography

Abstract

Degraded lands have often been suggested as a solution to issues of land scarcity and as an ideal way to meet mounting global demands for agricultural goods, but their locations and conditions are not well known. Four approaches have been used to assess degraded lands at the global scale: expert opinion, satellite observation, biophysical models, and taking inventory of abandoned agricultural lands. We review prominent databases and methodologies used to estimate the area of degraded land, translate these data into a common framework for comparison, and highlight reasons for discrepancies between the numbers. Global estimates of total degraded area vary from less than 1 billion ha to over 6 billion ha, with equally wide disagreement in their spatial distribution. The risk of overestimating the availability and productive potential of these areas is severe, as it may divert attention from efforts to reduce food and agricultural waste or the demand for land-intensive commodities.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

Global estimates of degraded land vary from less than 1 billion ha to over 6 billion ha and disagree widely in spatial distribution. The paper reviews four major mapping approaches and compares prominent datasets on a common grid, warning that overestimating degraded-land availability could distract from reducing waste and demand for land-intensive commodities.

Key findings

  • Global degraded-area estimates range from <1 billion ha to >6 billion ha: GLASOD estimated nearly 2 billion ha (22.5%) degraded since the mid-20th century; FAO TerraSTAT found over 6 billion ha (66% of world land) affected; Dregne and Chou estimated roughly 3.6 billion ha (70%) of drylands degraded; GLADA found declining NPP across 21% of global land, 2.7 billion ha; Cai et al. estimated nearly 1 billion ha; Campbell et al. estimated 385–472 million ha of abandoned agricultural land.
  • Spatial disagreement is severe: the greatest disagreement is in Asia, where only two datasets agree and standard deviation exceeds 30% of cell area across large parts of China and Southeast Asia; Central Africa shows >40% standard deviations.
  • Agreement is mostly about non-degradation: of cells where all four datasets agree, 89% have average degradation less than 5% of cell area.
  • Pairwise comparison shows little relationship between some methods: GLADA and GLASOD had R² = 0.00 for percent area degraded in 20 km cells, partly because GLASOD considered soil degradation over centuries while GLADA considered vegetation degradation over decades.

Methods

  • The paper reviews four approaches to global degraded-land assessment: expert opinion, satellite-derived net primary productivity, biophysical models, and abandoned agricultural land mapping.
  • For comparison, the authors selected one map per method (GLASOD, GLADA, Cai et al. 2011, and Campbell et al. 2008), converted them to percent area degraded on a common equal-area Eckert IV grid at 1 km, aggregated to 20 km cells, and excluded degradation labeled light in severity.
  • They assessed similarities and differences using visual comparison, number of datasets in agreement, linear regression among pairs of datasets, and standard deviation among all four datasets in each 20 km cell.

Limitations

  • Stated: none of the assessments provided direct measurement of degradation; all relied on proxies, and quantifying error or uncertainty is difficult or impossible because there are no accepted values for comparison.
  • Stated: definitions, methodologies, time periods, and geographic domains differ across datasets; satellite approaches only capture degradation after the 1980s and mainly ongoing processes, biophysical models are limited to current croplands, and abandonment estimates exclude non-agricultural degradation and rely on uncertain historical land-use inputs.
  • Evident from the paper’s methods: the comparison uses only one map per approach and excludes light-severity degradation, so the synthesis may not represent the full range or detail of each method’s estimates.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1016/j.apgeog.2014.11.024

Cites

71 of 71 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

0 of 110 cited sources checked · 0 supported · 0 flagged

Show all 58 claims

  • It may state two separate claims as one. 60
  • Probably not a substantial claim. 47
88 of 88
  • The authors state this as an assumption.

    Any pixel with a negative trend in RUE-adjusted NDVI is degraded over its full area.

    “Following the method used by Bai et al. (2008), we assumed that any pixel with a negative trend in RUE-adjusted NDVI is degraded over its full area.”
  • The authors state this as an assumption.

    Marginal productivity is an indicator of land fragility or sensitivity to over-utilization.

    “Marginal productivity is assumed to be an indicator of land fragility or sensitivity to over-utilization.”
  • The paper relies on this without support.

    There are no accepted values against which to compare estimates of degraded land.

    “there are no accepted values against which to make comparisons”
  • The paper relies on this without support.

    During periods of widespread degradation covering upward of 75 percent of the world's land surface, agricultural production continued to increase.

    “during these periods of widespread degradation covering upward of 75 percent of the world's land surface, we have continued to increase our agricultural production”
  • The paper relies on this without support.

    Degradation is a dynamic and subjective condition.

    “capturing a dynamic and subjective condition”
  • The paper relies on this without support.

    Site-specific context, such as soil type, topography, farming practices and land use history, influences degradation.

    “Site-specific context, such as soil type, topography, farming practices and land use history, all influence degradation.”
  • The paper relies on this without support.

    The recoverability of degraded lands is not in linear relationship with its degradation pressure.

    “the recoverability of degraded lands is not in linear relationship with its degradation pressure”
  • The paper relies on this without support.

    There is a tipping point beyond which the resources needed to recover degraded land may no longer justify its improvement.

    “Beyond this threshold, the resources needed to recover the land may no longer justify its improvement.”
  • The paper relies on this without support.

    Irrigation will be needed in many degraded regions and will stress worldwide water supply.

    “Irrigation will undoubtedly be needed in many degraded regions and this will stress our already tenuous worldwide water supply.”
9 of 9

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Citations

Cites

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Show all 71 references

Research works printed but not linked: 2

  1. Dregne, 1992, Global desertification dimensions and costs, Degradation & Restoration of Arid Lands, 73
  2. Wiegmann, K., Hennenberg, K. J., Fritsche, U. R. (2008). Degraded land and sustainable bioenergy feedstock production. Paper presented at the joint international workshop on high natural value criteria and potential for sustainable use of degraded Lands, Paris.

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Metadata

Authors
Gibbs, H. K., & Salmon, J. M.
Affiliations
University of Wisconsin–Madison (US)
Corresponding author
Gibbs, H.K.
Venue
Applied Geography
Publisher
Elsevier BV
Published
2015-02
Volume
57
Pages
12-21
ISSN
0143-6228 (ISSN-L)
OpenAlex
W2046206266
Cited by
753
References
71
Citations by year
2026: 63 · 2025: 88 · 2024: 82 · 2023: 89 · 2022: 98 · 2021: 79 · 2020: 83 · 2019: 69 · 2018: 39 · 2017: 39 · 2016: 22 · 2015: 2
FWCI
17.36
Type
journal article
Language
en
Open access
Locations
Applied Geography (publishedVersion, cc-by-nc-nd)
Topics
  • Physical Sciences › Environmental Science › Global and Planetary Change › Land Use and Ecosystem Services
  • Social Sciences › Development › Agriculture, Land Use, Rural Development
  • Life Sciences › Agricultural and Biological Sciences › Soil Science › Soil erosion and sediment transport
Keywords
degraded land, land scarcity, agricultural land demand, satellite remote sensing, biophysical model, abandoned farmland

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