Abstract
Desertification is the result of natural and anthropogenic processes, leading to degradation or loss of the land’s productivity and complexity. To assess the desertification status, integrated set of indicators must be identified. Indicators must provide synthetic information on threshold levels, status and evolution of relevant physical, chemical, biological and anthropogenic processes. Multi-criteria decision-making (MCDM) is a collection of methodologies to compare, select, or rank multiple alternatives that involve incommensurate attributes. Technique for order preference by similarity to ideal solution (TOPSIS) method is a multiple criteria method to identify solutions from a finite set. TOPSIS is an algorithm for determining the most preferable choices among the possible indicators that can be developed. The aim of this paper is to introduce TOPSIS as a decision-making method for the selection and integration of desertification indicators. The simulation case study presented here is related to the selection of the best set of indicators to monitor land degradation by remote sensing in three different countries (Brazil, Mozambique and Portugal), within the framework defined by the DesertWatch Extension project.
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Notes
Environmental Sensitive Areas (in this method, different types of ESAs to desertification can be analyzed in terms of various parameters such as landforms, soil, geology, vegetation, climate and human actions. Each of these parameters is grouped into various uniform classes and a weighting factor is assigned to each class. Then four layers are evaluated: soil quality, climate quality, vegetation quality and management quality. For more information, see Kosmas et al. 1999).
Technique for Order Preference by Similarity to Ideal Solution (Hwang and Yoon, 1981).
NADIR point is a geometric allegory for distance of preferred indicators from desirable and undesirable solutions which has shortest distance from positive solution and farthest distance from negative solution.
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Acknowledgments
The data used were kindly provided by the DesertWatch Extension project, a project funded by the European Space Agency (ESA) and coordinated by Advanced Computer System (ACS Spa). Data have been collected by the implementing Consortium lead by Critical Software SA.
Authors would like to thank Prof. S. Madrau of the Sassari University for his assistance in the preparation of this paper.
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Sepehr, A., Zucca, C. Ranking desertification indicators using TOPSIS algorithm. Nat Hazards 62, 1137–1153 (2012). https://doi.org/10.1007/s11069-012-0139-z
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DOI: https://doi.org/10.1007/s11069-012-0139-z