Mapping land degradation and desertification (LDD) at the global scale still is a conceptual and operational challenge. The present study has been performed in the frame of the WAD (new World Atlas of Desertification) initiative. The objective of the paper is to test a structured procedure to identify relevant indicators for an effective representation of complex global LDD issues, based on available data sets (both geo-spatial and statistical), and conform to the UNCCD (United Nations Convention to Combat Desertification) requirements. Available indicators and data sets were reviewed and the collected information was organized through a database (DB). The proposed selection procedure is semi-quantitative and based on expert ranking decisions made within the relational DB environment, which allows for transparent definition and iterative refinement of the selection rules. The procedure was operationally tested on a concrete case study ("deforestation in Sub-Saharan Africa") by using available global data sets. Questions related to global data availability and to major conceptual aspects such as the concept of "minimum indicator set", the indicator frameworks, the ranking and selection criteria are raised and discussed. © 2011 Elsevier Ltd. All rights reserved.

Towards a World Desertification Atlas. Relating and selecting indicators and data sets to represent complex issues

Salvia R.
Methodology
;
2012

Abstract

Mapping land degradation and desertification (LDD) at the global scale still is a conceptual and operational challenge. The present study has been performed in the frame of the WAD (new World Atlas of Desertification) initiative. The objective of the paper is to test a structured procedure to identify relevant indicators for an effective representation of complex global LDD issues, based on available data sets (both geo-spatial and statistical), and conform to the UNCCD (United Nations Convention to Combat Desertification) requirements. Available indicators and data sets were reviewed and the collected information was organized through a database (DB). The proposed selection procedure is semi-quantitative and based on expert ranking decisions made within the relational DB environment, which allows for transparent definition and iterative refinement of the selection rules. The procedure was operationally tested on a concrete case study ("deforestation in Sub-Saharan Africa") by using available global data sets. Questions related to global data availability and to major conceptual aspects such as the concept of "minimum indicator set", the indicator frameworks, the ranking and selection criteria are raised and discussed. © 2011 Elsevier Ltd. All rights reserved.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11563/137901
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