GIS multi-criteria decision analysis for assessment and mapping of neotectonic landscape deformation: A case study from Crete

Abstract

This study of drainage systems in a tectonically active region is based on the Geographical Information Systems (GIS) integration of data from an analytic hierarchy process (AHP) and a weighted linear combination (WLC) procedure with multiple criteria 2 data. A set of thematic maps were produced, based on existing geological maps and freelyavailable ASTER Global DEM elevation data, using various geological information (i.e. lineaments and lithologies), geomorphometric indices (i.e. slope gradient, drainage density, stream frequency, and the topographic wetness index) and morphotectonic indices (i.e. amplitude of relief and stream length gradient) that highlight areas of neotectonic landscape deformation. The weights of the factors were determined using AHP and WLC. A neotectonic landscape deformation index (NLDI) is computed as the sum of the various weighted factors to provide a map of NLDI distribution across the study region (western Crete). The main objective of this study was to analyse and map the intra-basin spatial variations in neotectonic landscape deformation: five classes, very low to very high, were determined. High to very high deformation zones are linked with known and newly detected active fault zones. The methodology could be developed into a low-cost technique for assessing seismic hazard, guiding disaster risk reduction activities. It can provide an alternative to the Interferometric Synthetic Aperture Radar (InSAR) approach for highlighting zones of neotectonic deformation, particularly in regions where dense vegetation or snow cover renders InSAR ineffective.

Integrated Assessment of Natural Hazards, Including Climate Change’s Influences, for Cultural Heritage Sites: The Case of the Historic Centre of Rethymno in Greece

“…Moreover, the fact that the seismic intensity decreases (attenuates) with distance to faults, a cost distance parameter from the pilot site to the recorded faults was acknowledged (Cooke 1997). The geological formations were also considered as another parameter in this hazard map development process, since deep, weak soils tend to amplify and prolong the seismic waves shaking more than the stronger rock bed (Argyriou et al 2016). All the datasets were implemented into a GIS environment following appropriate standardization, rating, and ranking of the datasets (Argyriou et al 2016).…”

“…The geological formations were also considered as another parameter in this hazard map development process, since deep, weak soils tend to amplify and prolong the seismic waves shaking more than the stronger rock bed (Argyriou et al 2016). All the datasets were implemented into a GIS environment following appropriate standardization, rating, and ranking of the datasets (Argyriou et al 2016). The reason is that in order to combine them in a single analysis, each cell for each factor needed to be reclassified into a common hazard assessment scale such as 1 to 10, with 10 being a location with the highest likelihood or severity of the hazard occurrence.…”

Automatic selection of weights for GIS-based multicriteria decision analysis: site selection of transmission towers as a case study

“…aggregation, is occupied by AHP (Analytic Hierarchy Process; Saaty, 1990), which is again based on the additive weighting model (Argyriou, Teeuw, Rust, & Sarris, 2016). The main difference here is in the weights calculation, which is achieved using a preference matrix where each criterion is compared to all others in a pairwise comparison.…”

“…This technique is more reliable than SAW, since it allows for checking the weights (again derived by expert judgment) assigned to the criteria in terms of consistency using the pairwise comparison, and calculating the consistency index (Dedemen, 2013). This technique is widely used in the literature to solve many different problems: for example, Argyriou et al (2016) used AHP to map neotectonic landscape deformations in Crete. In Ş ener, Süzen, and Doyuran (2006) AHP was used to identify suitable location for landfills, Zhu and Dale (2001) developed a web AHP tool to solve complex multicriteria environmental problems, and Akash, Mamlook, and Mohsen (1999) used it to identify suitable locations for power plants.…”

Equilibrium Strategy Based Recycling Facility Site Selection towards Mitigating Coal Gangue Contamination

“…Depending on the different features, the buffer zone characteristics are as follows; 0.25 km from electricity networks and vehicular roads, 1 km from farm pumps, water wells, residential areas, railways and paved roads and 5 km from pipelines and airports. The above assigned buffer zone dimensions are determined based on Argyriou et al [49], and suitable and unsuitable areas are screened. Then, the suitable area is divided into 5 km × 7 km units using ArcGIS in ESRI.…”