DefME Software for Landsat 8 OLI data processing

Description: DefMe (Defoliation and Maximum Entropy) is a set of Python scripts that provides users and developers with tools for atmospheric and topographic correction of Landsat 8 OLI images, synthesis of indexes (products), implementing vector points of in-situ observation data, configuring and training of MaxEnt model and computing raster of target variable distribution. Scripts are organized accordingly to stages of research and purposes of each stage (Table 1). General description of the script set is given in Section 2.1. Subsequent details of software functions are presented in Section 2.2.

Description of files in the script set:

Number File name Stage of research Description 1 0_Batch_crop_geotiff_folder.py Preprocessing Parsing of files in the directory, batch processing of Landsat 8 OLI tif files, including cropping to AOI, atmospheric and topographic corrections, computing of RGB composite images. 2 1_Generate_ore_points_from_shp.py Preprocessing Creating of raster tiff layer from vector points of target variable observation. 3 2_Defoliation_and_mineral_mapping.py Defoliation Implementing of software defoliant technique, computing of directed principal components.
4 3_Model_CollectingData.py Dataset building Composing of dataset for further manipulation. 5 4_MaxEnt_model_teaching.py Model training Configuring and training of MaxEnt model, rendering target variable distribution layer, model export into file. 6 5_MaxEnt_model_predicting.py Model deployment (optional) Model loading from the saved file, its deployment to the new area. Requires previously collected dataset. 7 5_Prediction_C-A_analysis.py Classification Classification of target variable output, determining of class boundaries. 8 6_Prediction_P-A.py Assessment Assessment of model efficacy, drawing of Prediction-Area curve 9 mygdal_functions0_9.py - User defined functions for spatial data operation 10 configuration.py - Storing analysis configuration variables

Research conducted with DefMe:

Shevyrev, S, Carranza, EJM. Application of Maximum Entropy for Mineral Prospectivity Mapping in Heavily Vegetated Areas of Greater Kurile Chain with Landsat 8 Data. Ore Geology Review https://doi.org/10.1016/j.oregeorev.2022.104758