Description
Here we provide a time series of this reconstructed LST data as sample data. Long-term monthly averages were summarized as monthly average LST maps for Germany. The long-term monthly averages are based on the monthly averages of the years 2003 - 2016, which were calculated from the daily averages. The sample data is upsampled to a spatial resolution of approx. 250 m.
The data is provided in GeoTIFF format. The Coordinate Reference System (CRS) is identical to the MOD11A1/MYD11A1 product (Sinusoidal) provided by NASA. In WKT as reported by GDAL:
PROJCRS[\\\\\\\\\\\\\\\"unnamed\\\\\\\\\\\\\\\\",
BASEGEOGCRS[\\\\\\\\\\\\\\"Unknown datum based upon the custom spheroid\\\\\\\\\\\\\\\",
DATE[\\\\\\\\\\\\\\"Not_specified_based_on_custom_spheroid\\\\\\\\\\\\\\\\",
ELLIPSOID[\\\\\\\\\\\\\\"Custom spheroid\\\\\\\\\\\\\\\\\",6371007.181,0,
LENGTHUNIT[\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\",1,
ID[\\\\\\\\\\\\\\\"EPSG\\\\\\\\\\\\\\\\",9001]]]],
PRIMEM[\\\\\\\\\\\\\\"Greenwich\\\\\\\\\\\\\\\\\\",0,
ANGLEUNIT[\\\\\\\\\\\\\\"degree\\\\\\\\\\\\\\\\",0.0174532925199433,
ID[\\\\\\\\\\\\\\\"EPSG\\\\\\\\\\\\\\\\",9122]]]],
CONVERSION[\\\\\\\\\\\\\\"Sinusoidal\\\\\\\\\\\\\\\\",
METHOD[\\\\\\\\\\\\\\"Sinusoidal\\\\\\\\\\\\\\\\\\"],
PARAMETER[\\\\\\\\\\\\\"Longitude of natural origin\\\\\\\\\\\\\\\\",0,
ANGLEUNIT[\\\\\\\\\\\\\\"degree\\\\\\\\\\\\\\\\",0.0174532925199433],
ID[\\\\\\\\\\\\\\\"EPSG\\\\\\\\\\\\\\\\",8802]],
PARAMETER[\\\\\\\\\\\\\\"False easting\\\\\\\\\\\\\\\\",0,
LENGTHUNIT[\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\",1],
ID[\\\\\\\\\\\\\\\"EPSG\\\\\\\\\\\\\\\\",8806]],
PARAMETER[\\\\\\\\\\\\\\"False northing\\\\\\\\\\\\\\\\",0,
LENGTHUNIT[\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\",1],
ID[\\\\\\\\\\\\\\\"EPSG\\\\\\\\\\\\\\\\",8807]]],
CS[Cartesian,2],
AXIS[\\\\\\\\\\\\\\\"easting\\\\\\\\\\\\\\\\",east,
ORDER[1],
LENGTHUNIT[\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\",1,
ID[\\\\\\\\\\\\\\\"EPSG\\\\\\\\\\\\\\\\",9001]]]],
AXIS[\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\ ORDER[2],
LENGTHUNIT[\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\",1,
ID[\\\\\\\\\\\\\\\\"EPSG\\\\\\\\\\\\\\\\",9001]]]]
naming convention:
lst_250m_lt_MM_avg.tif
MM is the two-digit month.
Example for January: lst_250m_lt_01_avg.tif
Meaning of the pixel values:
The pixel values are encoded in degrees Celsius * 10.
This means that the pixel value must be divided by 10 to obtain degrees Celsius.
Data type: Grid, Int16
Spatial resolution: 231.6563582846881673 m
Spatial expansion sinusoidal (W, S, E, N): 408410.160, 5256282.769, 1047318.396, 6122214.237
[1] Metz M., Andreo V., Neteler M. (2017): A new complete time series of land surface temperature from MODIS LST data. Remote sensing, 9(12):1333. DOI: http://dx.doi.org/10.3390/rs9121333
Thanks: We thank the NASA Land Processes Distributed Active Archive Center (LP DAAC) for providing the MODIS LST data. The dataset is based on the MODIS collection V006.
Resources
| Name | Format | Description | Link |
|---|---|---|---|
| 5 | https://mobilithek.info//mdp-api/files/aux/515138719261298688/lst_longterm_monthly_average_sinusoidal_germany.zip | ||
| 5 | https://mobilithek.info//mdp-api/files/aux/515138719261298688/lst_longterm_monthly_average_sinusoidal_germany.zip | ||
| 5 | https://mobilithek.info//mdp-api/files/aux/515138719261298688/lst_longterm_monthly_average_sinusoidal_germany.zip | ||
| 5 | https://mobilithek.info//mdp-api/files/aux/515138719261298688/lst_longterm_monthly_average_sinusoidal_germany.zip | ||
| 5 | https://mobilithek.info//mdp-api/files/aux/515138719261298688/lst_longterm_monthly_average_sinusoidal_germany.zip | ||
| 5 | https://mobilithek.info//mdp-api/files/aux/515138719261298688/lst_longterm_monthly_average_sinusoidal_germany.zip | ||
| 5 | https://mobilithek.info//mdp-api/files/aux/515138719261298688/lst_longterm_monthly_average_sinusoidal_germany.zip | ||
| 5 | https://mobilithek.info//mdp-api/files/aux/515138719261298688/lst_longterm_monthly_average_sinusoidal_germany.zip |
Tags
- land-surface-temperature
- modis
- meteorologisch-geografische-kennwerte
- atmosphärische-bedingungen
- gesundheit-und-sicherheit
- deutschland
Topics
- ENVI