Optical satellite-derived waterline time series at 8 beaches using various indexes and thresholding methods

Satellite-derived waterlines, each file is associated to a site and a thresholding method and contains the waterline time series derived from 5 different indexes (refer to the associated paper) Example of code : import pickle import matplotlib.pyplot as plt index = 'NDWI' #NDWI can be switched to SCoWI, MNDWI, AWEIsh, AWEIns indexes. data = pickle.load(open('path/to/file.p','rb')) key = 'TRANSECT NAME' #data.keys() to see transects names waterline_dict = data[key][index]['raw'] #raw refers to raw waterline, IQR refers to raw data without outliers, and tcorr the tide corrected data. t,X = waterline_dict['sat_dates'], waterline_dict['SDW_'+index] plt.plot(t,X) plt.ylabel('Cross-shore waterline position [m]') plt.xlabel('Time')