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Can linear trend analyses of NDVI time series data truly detect land degradation? Simulations may provide the answer

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dc.contributor.author Wessels, Konrad J
dc.contributor.author Van den Bergh, F
dc.contributor.author Scholes, RJ
dc.contributor.author Miteffa, S
dc.date.accessioned 2011-09-23T09:18:04Z
dc.date.available 2011-09-23T09:18:04Z
dc.date.issued 2011-04
dc.identifier.citation Wessels, KJ, Van den Bergh, F, Scholes, RJ. 2011. Can linear trend analyses of NDVI time series data truly detect land degradation? Simulations may provide the answer. 34th International Symposium for Remote Sensing of Environment. Sydney Convention & Exhibition Centre Sydney, Australia, 10-15 April 2011 en_US
dc.identifier.uri http://hdl.handle.net/10204/5170
dc.description 34th International Symposium for Remote Sensing of Environment. Sydney Convention & Exhibition Centre Sydney, Australia, 10-15 April 2011 en_US
dc.description.abstract There has been a recent proliferation of remote sensing-based trend analysis for monitoring regional desertification. These show contradictory results. All of them claim to have been “validated” through expert interpretation, in the absence of sufficient field data. The authors suggest that such an approach is not sufficiently rigorous. Therefore, they demonstrate an approach which simulates land degradation so that the intensity, rate and timing of the reduction in NDVI can be controlled, in order to quantitatively evaluate the ability of methods to detect these known changes. The results show that linear trend analysis is rather insensitive to previously observed levels of NDVI reduction due to degradation in the well-studied communal lands in the Lowveld of South Africa. The period of investigation, has a large but rather unpredictable influence on the linear trends. This casts doubts over the ability of linear trend analysis, to detect relatively subtle, slowly-developing degradation in semiarid rangelands. en_US
dc.language.iso en en_US
dc.relation.ispartofseries Workflow request;7223
dc.subject Remote sensing en_US
dc.subject Regional desertificatio en_US
dc.subject AVHRR en_US
dc.subject NDVI en_US
dc.subject Desertification en_US
dc.subject Land degradation en_US
dc.subject Linear trends en_US
dc.subject South African Lowveld en_US
dc.title Can linear trend analyses of NDVI time series data truly detect land degradation? Simulations may provide the answer en_US
dc.type Conference Presentation en_US
dc.identifier.apacitation Wessels, K. J., Van den Bergh, F., Scholes, R., & Miteffa, S. (2011). Can linear trend analyses of NDVI time series data truly detect land degradation? Simulations may provide the answer. http://hdl.handle.net/10204/5170 en_ZA
dc.identifier.chicagocitation Wessels, Konrad J, F Van den Bergh, RJ Scholes, and S Miteffa. "Can linear trend analyses of NDVI time series data truly detect land degradation? Simulations may provide the answer." (2011): http://hdl.handle.net/10204/5170 en_ZA
dc.identifier.vancouvercitation Wessels KJ, Van den Bergh F, Scholes R, Miteffa S, Can linear trend analyses of NDVI time series data truly detect land degradation? Simulations may provide the answer; 2011. http://hdl.handle.net/10204/5170 . en_ZA
dc.identifier.ris TY - Conference Presentation AU - Wessels, Konrad J AU - Van den Bergh, F AU - Scholes, RJ AU - Miteffa, S AB - There has been a recent proliferation of remote sensing-based trend analysis for monitoring regional desertification. These show contradictory results. All of them claim to have been “validated” through expert interpretation, in the absence of sufficient field data. The authors suggest that such an approach is not sufficiently rigorous. Therefore, they demonstrate an approach which simulates land degradation so that the intensity, rate and timing of the reduction in NDVI can be controlled, in order to quantitatively evaluate the ability of methods to detect these known changes. The results show that linear trend analysis is rather insensitive to previously observed levels of NDVI reduction due to degradation in the well-studied communal lands in the Lowveld of South Africa. The period of investigation, has a large but rather unpredictable influence on the linear trends. This casts doubts over the ability of linear trend analysis, to detect relatively subtle, slowly-developing degradation in semiarid rangelands. DA - 2011-04 DB - ResearchSpace DP - CSIR KW - Remote sensing KW - Regional desertificatio KW - AVHRR KW - NDVI KW - Desertification KW - Land degradation KW - Linear trends KW - South African Lowveld LK - https://researchspace.csir.co.za PY - 2011 T1 - Can linear trend analyses of NDVI time series data truly detect land degradation? Simulations may provide the answer TI - Can linear trend analyses of NDVI time series data truly detect land degradation? Simulations may provide the answer UR - http://hdl.handle.net/10204/5170 ER - en_ZA


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