Online-only Table 2 Overview of the structure and content of the figshare data record28 (including directory, subdirectory and file listing, and content).
From: Multiyear in-situ L-band microwave radiometry of land surface processes on the Tibetan Plateau
Directory / Filename | Subdirectory / Filename | Subdirectory / Filename | Content |
|---|---|---|---|
ELBARA-III dataset_Update | |||
Code | |||
Plot_TB_SM_Pre | |||
AWS_TB_SMST_Display.py | Code for plotting AWS, TB and SMST (Fig. 6) | ||
Time_F.py | Code for rounding datetime to any time interval in seconds | ||
Time_F.pyc | Python interpreter generated file when Time_F.py is imported. | ||
MODIS_LAI | |||
HANTS.py | Code for HANTS algorithm | ||
LAI_Hants_Process.py | Code for smoothing MODIS LAI with HANTS algorithm | ||
MODIS_LAI_Extract.py | Code for extracting MODIS LAI | ||
Time_F.py | Code for rounding datetime to any time interval in seconds | ||
Time_F.pyc | Python interpreter generated file when Time_F.py is imported. | ||
SMAP_TB SMAP L1C TB reading.m | Code for extracting SMAP L1C data | ||
AWS_Time_Check | |||
AWS_TB_30min_timeCheck.py | Code for checking time information of AWS data. | ||
Time_F.py | Code for rounding datetime to any time interval in seconds | ||
Time_F.pyc | Python interpreter generated file when Time_F.py is imported. | ||
Data | ELBARA-III dataset-2016–2017ELBARA-III TB.csv | ELBARA TB data, 2016–2017 | |
ELBARA-III dataset-2016–2017Field_Unit.csv | Definition of field (and unit) involved in each.csv file in 2016–2017 period | ||
ELBARA-III dataset-2016–2017MeteoData_15min_20160325_201701.csv | Meteorological data, 2016–2017, 15 min interval | ||
ELBARA-III dataset-2016–2017MeteoData_30min_20160101_0315.csv | Meteorological data, 2016–2017, 30 min interval | ||
ELBARA-III dataset-2016–2017MODIS LAI_HANTS.csv | LAI at hourly scale interpolated from MODIS LAI after smoothing by HANTS algorithm, 2016–2017 | ||
ELBARA-III dataset-2016–2017SMAP TB.csv | SMAP TB data, 2016–2017 | ||
ELBARA-III dataset-2016–2017SMST_LC.csv | SMST_LC data, 2016–2017 | ||
ELBARA-III dataset-2016–2017SMST_Z.csv | SMST_Z data, 2016–2017 | ||
ELBARA-III dataset-2016–2019MODIS_LAI_8daily.csv | MODIS LAI 8-day data, 2016–2019 | ||
ELBARA-III dataset-2017–2018ELBARA-III TB.csv | ELBARA TB, 2017–2018 | ||
ELBARA-III dataset-2017–2018Field_Unit.csv | Definition of field (and unit) involved in each.csv file in 2017–2018 period | ||
ELBARA-III dataset-2017–2018LAI_IN SITU.csv | In Situ LAI data, 2018 | ||
ELBARA-III dataset-2017–2018MeteoData_30min.csv | Meteorological data, 2017–2018, 30 min interval | ||
ELBARA-III dataset-2017–2018MODIS LAI_HANTS.csv | LAI at hourly scale interpolated from MODIS LAI after smoothing by HANTS algorithm, 2017–2018 | ||
ELBARA-III dataset-2017–2018SMAP TB.csv | SMAP TB data, 2017–2018 | ||
ELBARA-III dataset-2017–2018SMST_LC.csv | SMST_LC data, 2017–2018 | ||
ELBARA-III dataset-2018–2019ELBARA-III TB.csv | ELBARA TB, 2018–2019 | ||
ELBARA-III dataset-2018–2019Field_Unit.csv | Definition of field (and unit) involved in each.csv file in 2018–2019 period | ||
ELBARA-III dataset-2018–2019MeteoData_30min.csv | Meteorological data, 2018–2019, 30 min interval | ||
ELBARA-III dataset-2018–2019MODIS LAI_HANTS.csv | LAI at hourly scale interpolated from MODIS LAI after smoothing by HANTS algorithm, 2018–2019 | ||
ELBARA-III dataset-2018–2019SMAP TB.csv | SMAP TB data, 2018–2019 | ||
ELBARA-III dataset-2018–2019SMST_LC.csv | SMST_LC data, 2018–2019 | ||
FluxDataAllField2016–2017.csv | Eddy covariance data, 2016–2017 | ||
FluxDataAllField2017–2018.csv | Eddy covariance data, 2017–2018 | ||
FluxDataAllField2018–2019.csv | Eddy covariance data, 2018–2019 | ||
eddycovariance_rawdata_metafile.pdf | Definition of field (and unit) involved in each Eddy covariance data file | ||
MODIS_Download_Procedure.pdf | Procedure for downloading MODIS data | ||
README.txt | README File | ||
SMAP L1C over Maqu ELBARA site.tif | SMAP L1C coverage over Maqu |
