Ranking desertification indicators using TOPSIS algorithm

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.