dc.contributor.author |
Kgaphola, Motsoko J
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dc.contributor.author |
Ramoelo, Abel
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|
dc.contributor.author |
Odindi, J
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dc.contributor.author |
Mwenge Kahinda, Jean-Marc
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dc.contributor.author |
Seetal, Ashwin R
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dc.date.accessioned |
2023-05-08T05:59:00Z |
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dc.date.available |
2023-05-08T05:59:00Z |
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dc.date.issued |
2023-03 |
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dc.identifier.citation |
Kgaphola, M.J., Ramoelo, A., Odindi, J., Mwenge Kahinda, J. & Seetal, R.A. 2023. Apportioning human-induced and climate-induced land degradation: A Case of the Greater Sekhukhune District Municipality. <i>Applied Sciences, 13(6).</i> http://hdl.handle.net/10204/12761 |
en_ZA |
dc.identifier.issn |
2076-3417 |
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dc.identifier.uri |
https://doi.org/10.3390/app13063644
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|
dc.identifier.uri |
http://hdl.handle.net/10204/12761
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|
dc.description.abstract |
Land degradation (LD) is a global issue that affects sustainability and livelihoods of approximately 1.5 billion people, especially in arid/semi-arid regions. Hence, identifying and assessing LD and its driving forces (natural and anthropogenic) is important in order to design and adopt appropriate sustainable land management interventions. Therefore, using vegetation as a proxy for LD, this study aimed to distinguish anthropogenic from rainfall-driven LD in the Greater Sekhukhune District Municipality from 1990 to 2019. It is widely established that rainfall highly correlates with vegetation productivity. A linear regression was performed between the Normalized Difference Vegetation Index (NDVI) and rainfall. The human-induced LD was then distinguished from that of rainfall using the spatial residual trend (RESTREND) method and the Mann–Kendall (MK) trend. RESTREND results showed that 11.59% of the district was degraded due to human activities such as overgrazing and injudicious rangeland management. While about 41.41% was degraded due to seasonal rainfall variability and an increasing frequency of droughts. Climate variability affected vegetation cover and contributed to different forms of soil erosion and gully formation. These findings provide relevant spatial information on rainfall or human-induced LD, which is useful for policy formulation and the design of LD mitigation measures in semi-arid regions. |
en_US |
dc.format |
Fulltext |
en_US |
dc.language.iso |
en |
en_US |
dc.relation.uri |
https://www.mdpi.com/2076-3417/13/6/3644 |
en_US |
dc.source |
Applied Sciences, 13(6) |
en_US |
dc.subject |
Land degradation |
en_US |
dc.subject |
Land Use and Land Cover Change |
en_US |
dc.subject |
Mann-Kendall trend |
en_US |
dc.subject |
Normalized Difference Vegetation Index |
en_US |
dc.subject |
NDVI |
en_US |
dc.subject |
Rainfall |
en_US |
dc.subject |
Residual trend |
en_US |
dc.subject |
RESTREND |
en_US |
dc.title |
Apportioning human-induced and climate-induced land degradation: A Case of the Greater Sekhukhune District Municipality |
en_US |
dc.type |
Article |
en_US |
dc.description.pages |
18 |
en_US |
dc.description.note |
Copyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
en_US |
dc.description.cluster |
Defence and Security |
en_US |
dc.description.cluster |
Smart Places |
en_US |
dc.description.impactarea |
Technology for Special Ops |
en_US |
dc.description.impactarea |
Smart water use |
en_US |
dc.identifier.apacitation |
Kgaphola, M. J., Ramoelo, A., Odindi, J., Mwenge Kahinda, J., & Seetal, R. A. (2023). Apportioning human-induced and climate-induced land degradation: A Case of the Greater Sekhukhune District Municipality. <i>Applied Sciences, 13(6)</i>, http://hdl.handle.net/10204/12761 |
en_ZA |
dc.identifier.chicagocitation |
Kgaphola, Motsoko J, A Ramoelo, J Odindi, Jean-Marc Mwenge Kahinda, and R Ashwin Seetal "Apportioning human-induced and climate-induced land degradation: A Case of the Greater Sekhukhune District Municipality." <i>Applied Sciences, 13(6)</i> (2023) http://hdl.handle.net/10204/12761 |
en_ZA |
dc.identifier.vancouvercitation |
Kgaphola MJ, Ramoelo A, Odindi J, Mwenge Kahinda J, Seetal RA. Apportioning human-induced and climate-induced land degradation: A Case of the Greater Sekhukhune District Municipality. Applied Sciences, 13(6). 2023; http://hdl.handle.net/10204/12761. |
en_ZA |
dc.identifier.ris |
TY - Article
AU - Kgaphola, Motsoko J
AU - Ramoelo, A
AU - Odindi, J
AU - Mwenge Kahinda, Jean-Marc
AU - Seetal, R Ashwin
AB - Land degradation (LD) is a global issue that affects sustainability and livelihoods of approximately 1.5 billion people, especially in arid/semi-arid regions. Hence, identifying and assessing LD and its driving forces (natural and anthropogenic) is important in order to design and adopt appropriate sustainable land management interventions. Therefore, using vegetation as a proxy for LD, this study aimed to distinguish anthropogenic from rainfall-driven LD in the Greater Sekhukhune District Municipality from 1990 to 2019. It is widely established that rainfall highly correlates with vegetation productivity. A linear regression was performed between the Normalized Difference Vegetation Index (NDVI) and rainfall. The human-induced LD was then distinguished from that of rainfall using the spatial residual trend (RESTREND) method and the Mann–Kendall (MK) trend. RESTREND results showed that 11.59% of the district was degraded due to human activities such as overgrazing and injudicious rangeland management. While about 41.41% was degraded due to seasonal rainfall variability and an increasing frequency of droughts. Climate variability affected vegetation cover and contributed to different forms of soil erosion and gully formation. These findings provide relevant spatial information on rainfall or human-induced LD, which is useful for policy formulation and the design of LD mitigation measures in semi-arid regions.
DA - 2023-03
DB - ResearchSpace
DP - CSIR
J1 - Applied Sciences, 13(6)
KW - Land degradation
KW - Land Use and Land Cover Change
KW - Mann-Kendall trend
KW - Normalized Difference Vegetation Index
KW - NDVI
KW - Rainfall
KW - Residual trend
KW - RESTREND
LK - https://researchspace.csir.co.za
PY - 2023
SM - 2076-3417
T1 - Apportioning human-induced and climate-induced land degradation: A Case of the Greater Sekhukhune District Municipality
TI - Apportioning human-induced and climate-induced land degradation: A Case of the Greater Sekhukhune District Municipality
UR - http://hdl.handle.net/10204/12761
ER - |
en_ZA |
dc.identifier.worklist |
26374 |
en_US |
dc.identifier.worklist |
26672 |
en_US |