A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> A. Disaster Management <s> This paper analyses earthquake data in the perspective of dynamical systems and fractional calculus (FC). This new standpoint uses Multidimensional Scaling (MDS) as a powerful clustering and visualization tool. FC extends the concepts of integrals and derivatives to non-integer and complex orders. MDS is a technique that produces spatial or geometric representations of complex objects, such that those objects that are perceived to be similar in some sense are placed on the MDS maps forming clusters. In this study, over three million seismic occurrences, covering the period from January 1, 1904 up to March 14, 2012 are analysed. The events are characterized by their magnitude and spatiotemporal distributions and are divided into fifty groups, according to the Flinn-Engdahl (F-E) seismic regions of Earth. Several correlation indices are proposed to quantify the similarities among regions. MDS maps are proven as an intuitive and useful visual representation of the complex relationships that are present among seismic events, which may not be perceived on traditional geographic maps. Therefore, MDS constitutes a valid alternative to classic visualization tools for understanding the global behaviour of earthquakes. <s> BIB001 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> A. Disaster Management <s> Earthquakes are associated with negative events, such as large number of casualties, destruction of buildings and infrastructures, or emergence of tsunamis. In this paper, we apply the Multidimensional Scaling (MDS) analysis to earthquake data. MDS is a set of techniques that produce spatial or geometric representations of complex objects, such that, objects perceived to be similar/distinct in some sense are placed nearby/distant on the MDS maps. The interpretation of the charts is based on the resulting clusters since MDS produces a different locus for each similarity measure. In this study, over three million seismic occurrences, covering the period from January 1, 1904 up to March 14, 2012 are analyzed. The events, characterized by their magnitude and spatiotemporal distributions, are divided into groups, either according to the Flinn–Engdahl seismic regions of Earth or using a rectangular grid based in latitude and longitude coordinates. Space-time and Space-frequency correlation indices are proposed to quantify the similarities among events. MDS has the advantage of avoiding sensitivity to the non-uniform spatial distribution of seismic data, resulting from poorly instrumented areas, and is well suited for accessing dynamics of complex systems. MDS maps are proven as an intuitive and useful visual representation of the complex relationships that are present among seismic events, which may not be perceived on traditional geographic maps. Therefore, MDS constitutes a valid alternative to classic visualization tools, for understanding the global behavior of earthquakes. <s> BIB002 </s> A State-of-the-Art Survey on Multidimensional Scaling-Based Localization Techniques <s> A. Disaster Management <s> Forest fires dynamics is often characterized by the absence of a characteristic length-scale, long range correlations in space and time, and long memory, which are features also associated with fractional order systems. In this paper a public domain forest fires catalogue, containing information of events for Portugal, covering the period from 1980 up to 2012, is tackled. The events are modelled as time series of Dirac impulses with amplitude proportional to the burnt area. The time series are viewed as the system output and are interpreted as a manifestation of the system dynamics. In the first phase we use the pseudo phase plane (PPP) technique to describe forest fires dynamics. In the second phase we use multidimensional scaling (MDS) visualization tools. The PPP allows the representation of forest fires dynamics in two-dimensional space, by taking time series representative of the phenomena. The MDS approach generates maps where objects that are perceived to be similar to each other are placed on the map forming clusters. The results are analysed in order to extract relationships among the data and to better understand forest fires behaviour. <s> BIB003
The seismic data is difficult to analyze and classical mathematical tools impose strong limitations in unveiling the hidden relationships between earthquakes  . MDS based localization is one of the approaches which are useful to get information regarding earthquakes. The maps generated by MDS are intuitive to visualize the complex relationships between seismic events BIB001 , BIB002 . A cluster is formed by similar objects which represent spatially distinguished objects. Earthquake analysis is studied in BIB001 and BIB002 by using the data of more than two million seismic occurrences in the period of 1904-2012. The relationship of space-time and space-frequency is used to find the similarity among the events. The fires caused by different natural factors in forests every year consume vast vegetation areas BIB003 . These forest fires increase the carbon dioxide emission, which contributes to soil erosion and disturbs the water cycle, thus it has a direct impact on the economy of a country. The forest fires in Portugal have been investigated in BIB003 from 1980-2012 by using MDS based methods.