Zoning and prioritizing the context of the 6th area of ​​Kerman city against earthquakes using remote sensing techniques

Today, the vulnerability of cities and especially old and worn-out structures against earthquakes is an important issue for environmental risk experts. The city of Kerman, due to its location in the tectonic zone of central Iran and having large and deep faults and fractures from a geological point of view, can be the source of huge crises, severe losses and casualties; Therefore, in this research, first, by using ASTER satellite images of 2007, the worn-out tissues of Kerman city were identified using SVM. In this study, the kappa coefficient of 76% was determined for all classes, and the kappa coefficient of 59% of the worn-out tissue was determined. The city of Kerman was identified. The results showed that the support vector machine classification method has the ability to detect nearly 75% of the worn-out fabric of the area, and the SVM method has worked very well in identifying the six areas of worn-out urban fabric.