Multiple TIFs to NetCDF conversion

Dataset References: Minsley, B.J., James, S.R., Bedrosian, P.A., Pace, M.D., Hoogenboom, B.E., and Burton, B.L., 2021, Airborne electromagnetic, magnetic, and radiometric survey of the Mississippi Alluvial Plain, November 2019 - March 2020: U.S. Geological Survey data release, https://doi.org/10.5066/P9E44CTQ. James, S.R., and Minsley, B.J., 2021, Combined results and derivative products of hydrogeologic structure and properties from airborne electromagnetic surveys in the Mississippi Alluvial Plain: U.S. Geological Survey data release, https://doi.org/10.5066/P9382RCI.

import matplotlib.pyplot as plt
from os.path import join
from gspy import Survey

Convert the TIFs data to netcdf

# Path to example files
data_path = '..//..//supplemental//'

# Define ..//supplemental information file
..//supplemental = data_path + "region//MAP//data//Tempest_survey_information.json"

# Add ..//supplemental information to the survey
survey = Survey(..//supplemental)

# Define input ASEG-format data file and associated variable mapping file
d_data = data_path + 'region//MAP//data//Tempest.dat'
d_supp = data_path + 'region//MAP//data//Tempest_data_information.json'

# Read data and format as tabular class object
# survey.add_tabular(type='aseg', data_filename=d_data, metadata_file=d_supp)

# Define input TIF-format data file and associated variable mapping file
d_grid_path = data_path + 'region//MAP//data//'
d_grid_supp = data_path + 'region//MAP//data//Tempest_rasters_Attributes.json'

# Read data and format as Griddata class object
survey.add_raster(metadata_file=d_grid_supp)

# Write NetCDF
d_out = data_path + 'region//MAP//data//tifs.nc'
survey.write_netcdf(d_out)

Read in the netcdf files

new_survey = Survey.read_netcdf(d_out)

Plotting

plt.figure()
new_survey.raster.pcolor('resistivity', stack=0, vmin=0, vmax=3, cmap='jet')
plt.show()