Fractal-Wavelet Classifier as a QGIS Plugin and Python programfor Geochemical anomalies

In the systematic exploration process for integrating the data layers, Python and Python-GIS programming are valuable environments for creating and developing automatic algorithms in calculations, analysis, preprocessing, and processing exploration layers. In this study, a fractal wavelet classifier was made as a unique program in Python and then used as a Plugin for the QGIS Plugin. The program uses geochemical Stream sediment samples in the Tarom metallogenic zone, NW Iran, as input values to target REE minerals anomalies in the Iron apatite mineralization type. Then, preprocess and process the Geochemical Data layer in the GIS environment to classify the anomal catchment basin populations from the background. Also, the program draws the fractal charts, calculates the fraction points, and stores them in a proper path in picture format and Excel. In fractal graphs, the fraction points are optional to select the best suitable values and could be modified the threshold values in final classification and layer integration.