Created
January 24, 2020 18:08
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Example: Reading GEDI Level 2A data in Python
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| import h5py | |
| import pandas as pd | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| # read file | |
| file = 'GEDI02_A_2019138044926_O02428_T03843_02_001_01.h5' | |
| f = h5py.File(file, 'r') | |
| # get some variables for BEAM0000 (change to other beam/vars as needed) | |
| elev = f['BEAM0000']['elev_highestreturn'][:] | |
| lat = f['BEAM0000']['lat_highestreturn'][:] | |
| lon = f['BEAM0000']['lon_highestreturn'][:] | |
| # subset transect to specific range of lats | |
| idx = np.where((lat >= 0.0) & (lat <= 21.0)) | |
| elev = elev[idx[0][0]:idx[0][-1]] | |
| lat = lat[idx[0][0]:idx[0][-1]] | |
| lon = lon[idx[0][0]:idx[0][-1]] | |
| # create a basic plot | |
| plt.plot(lon, elev) | |
| plt.show() | |
| # create a data frame, write it to CSV for mapping in QGIS | |
| df = pd.DataFrame({ | |
| 'lat': lat, | |
| 'lon': lon, | |
| 'elev': elev | |
| }) | |
| df.to_csv('gedi_out.csv', index=False) |
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