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Proxy global assessment of land degradation
Open accessAbstract
Abstract Land degradation is always with us but its causes, extent and severity are contested. We define land degradation as a long‐term decline in ecosystem function and productivity, which may be assessed using long‐term, remotely sensed normalized difference vegetation index (NDVI) data. Deviation from the norm may serve as a proxy assessment of land degradation and improvement – if other factors that may be responsible are taken into account. These other factors include rainfall effects which may be assessed by rain‐use efficiency, calculated from NDVI and rainfall. Results from the analysis of the 23‐year Global Inventory Modeling and Mapping Studies (GIMMS) NDVI data indicate declining rain‐use efficiency‐adjusted NDVI on ca. 24% of the global land area with degrading areas mainly in Africa south of the equator, South‐East Asia and south China, north‐central Australia, the Pampas and swaths of the Siberian and north American taiga; 1.5 billion people live in these areas. The results are very different from previous assessments which compounded what is happening now with historical land degradation. Economic appraisal can be undertaken when land degradation is expressed in terms of net primary productivity and the resultant data allow statistical comparison with other variables to reveal possible drivers.
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In the citing paper
“Therefore, applying CM without vegetation covers may not fully prevent land degradation”
From Almond farm profitability under agroecological management in south-eastern Spain: Accounting for externalities and opportunity costs (2020) · cites this paper as Bai et al., 2008
Experimental — accuracy not yet measuredIn the citing paper
“Bai et al. (2008) also found that nearly one-fifth of this degraded land is cropland, an area equivalent to more than 20 percent of all cultivated areas.”
From Mapping the world's degraded lands (2015) · cites this paper as Bai et al. (2008)
In the citing paper
“Indeed, Wessels, Van Den Bergh, and Scholes (2012) commented on the Bai et al. (2008) publication of GLADA results, and was highly critical of their methods, especially in the humid tropics where results were described as fatally flawed and misleading.”
From Mapping the world's degraded lands (2015) · cites this paper as Bai et al. (2008)
In the citing paper
“But at the same time, they also found that 16 percent of global land area is increasing in NPP, with 20 percent of total cropland area on an upward swing.”
From Mapping the world's degraded lands (2015) · cites this paper as Bai et al. (2008)
In the citing paper
“Early GLADA results reveal a declining trend in NPP across 21 percent of the global land area, 2.7 billion ha, mainly in tropical Africa, Southeast Asia, China, north central Australia, the Pampas, and swaths of the boreal forest in Siberia and North America.”
From Mapping the world's degraded lands (2015) · cites this paper as Bai et al., 2008
In the citing paper
“Roughly 23 percent of forests are also improving along with more than 43 percent of rangelands.”
From Mapping the world's degraded lands (2015) · cites this paper as Bai et al., 2008
In the citing paper
“The vast majority (78 percent) of degrading lands are found in humid regions, which is contrary to the popular belief that most degradation occurs in drylands.”
From Mapping the world's degraded lands (2015) · cites this paper as Bai et al., 2008
In the citing paper
“Roughly 40 percent of the degraded lands were found to be in forests, with another quarter in rangelands.”
From Mapping the world's degraded lands (2015) · cites this paper as Bai et al., 2008
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Bindraban, P. S., Batjes, N. H., Leenaars, J. G. B., & Bai, Z. (2010) · Socio-Environmental Systems Modeling · Cited by 2
Self-citationLand degradation assessment by applying relative rue in Inner Mongolia, China, 2001–2010
Gao, Z., Sun, B., del Barrio, G., Li, X., Wang, H., Bai, L., Wang, B., & Zhang, W. (2014) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss.2014.6946709 · Cited by 2
Soil carbon and agricultural productivity: perspectives from sub-Saharan Africa.
Bationo, A., Waswa, B., & Kihara, J. (2014) · CABI eBooks · doi:10.1079/9781780645322.0132 · Cited by 2
Liniger, H., van Lynden, G., Biancalani, R., Lindeque, L., Ndiaye, D., & Schwilch, G. (2013) · Bern Open Repository and Information System (University of Bern) · doi:10.7892/boris.46535 · Cited by 2
NPP Estimation Using Time-Series GF-1 Data in Sparse Vegetation Area
Sun, B., Li, Z., Gao, Z., WenTao, G., Zhang, Y., Ding, X., & Li, C. (2018) · IEEE International Geoscience and Remote Sensing Symposium (IGARSS) · doi:10.1109/igarss.2018.8518912 · Cited by 2
Metadata
- Authors
- Bai, Z. G., Dent, D. L., Olsson, L., & Schaepman, M. E.
- Affiliations
- ISRIC - World Soil Information (NL)
- Lund University (SE)
- Wageningen University & Research (NL)
- Corresponding author
- Dent, D. L.
- Venue
- Soil Use and Management
- Publisher
- Wiley
- Published
- 2008-08-22
- Volume
- 24
- Issue
- 3
- Pages
- 223-234
- ISSN
- 0266-0032 (ISSN-L)
- 1475-2743
- OpenAlex
- W2162414982
- Cited by
- 987
- References
- 28
- Citations by year
- 2026: 34 · 2025: 42 · 2024: 56 · 2023: 68 · 2022: 72 · 2021: 81 · 2020: 87 · 2019: 88 · 2018: 63 · 2017: 55 · 2016: 63 · 2015: 63 · 2014: 64 · 2013: 51 · 2012: 36
- FWCI
- 17.60
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Soil Use and Management (publishedVersion)
- Zurich Open Repository and Archive (University of Zurich) (acceptedVersion)
- Socio-Environmental Systems Modeling (acceptedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Zurich Open Repository and Archive (University of Zurich)
- Topics
- Physical Sciences › Environmental Science › Ecology › Remote Sensing in Agriculture
- Life Sciences › Agricultural and Biological Sciences › Soil Science › Soil erosion and sediment transport
- Physical Sciences › Environmental Science › Global and Planetary Change › Land Use and Ecosystem Services
- Keywords
- land degradation, NDVI, precipitation use efficiency, net primary productivity, GIMMS, remote sensing, rainfall effects on vegetation
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