Nighttime Land Surface Temperature from the VJ121A1N product over the western United States on June 18, 2018.
View full-size imageThe NOAA-20 Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Temperature and Emissivity (LST&E) Night Version 2 product (VJ121A1N) is compiled daily from nighttime Level 2 Gridded (L2G) intermediate products.
The L2G process maps the daily VJ121 swath granules onto a sinusoidal MODIS grid and stores all observations overlapping a gridded cell for a given night. The VJ121A1 algorithm sorts through all these observations for each cell and estimates the final LST value as an average from all cloud-free observations that have good LST accuracies. The nighttime average is weighted by the observation coverage for that cell. Only observations having observation coverage more than a certain threshold (15%) are considered for this averaging. The 1 kilometer dataset is derived through resampling the native 750 meter VIIRS resolution in the input product.
The VJ121A1N product is developed synergistically with the Moderate Resolution Imaging Spectroradiometer (MODIS) LST&E Version 6.1 product (MOD21A1N) using the same input atmospheric products and algorithmic approach. The overall objective for NASA VIIRS products is to ensure the algorithms and products are compatible with the MODIS Terra and Aqua algorithms to promote the continuity of the Earth Observation System (EOS) mission. Additional details regarding the method used to create this Level 3 (L3) product are available in the Algorithm Theoretical Basis Document (ATBD).
The VJ121A1N product contains seven Science Datasets (SDS): LST, quality control, emissivity for bands M14, M15, and M16, view zenith angle, and time of observation. A low-resolution browse image for LST is also available for each VJ121A1N granule.
More details can be found in this VIIRS Land V2 Changes document.
Validation at stage 1 has been achieved for the VIIRS Land Surface Temperature and Emissivity product suite. Visit VIIRS Land Product Quality Assessment Product Maturity for information on product maturity status.
| Characteristic | Description |
|---|---|
| Collection | NOAA-20 VIIRS |
| DOI | 10.5067/VIIRS/VJ121A1N.002 |
| File Size | ~1 MB |
| Temporal Resolution | Daily |
| Temporal Extent | 2018-01-01 to Present |
| Spatial Extent | Global |
| Coordinate System | Sinusoidal |
| Datum | N/A |
| File Format | HDF-EOS5 |
| Geographic Dimensions | 1200 km x 1200 km |
| Characteristic | Description |
|---|---|
| Number of Science Dataset (SDS) Layers | 7 |
| Columns/Rows | 1200 x 1200 |
| Pixel Size | 1000 m |
| SDS Name | Description | Units | Data Type | Fill Value | No Data Value | Valid Range | Scale Factor | Offset |
|---|---|---|---|---|---|---|---|---|
| Emis_14 | Daily Band 14 emissivity | N/A | 8-bit unsigned integer | 0 | N/A | 1 to 255 | 0.002 | 0.49 |
| Emis_15 | Daily Band 15 emissivity | N/A | 8-bit unsigned integer | 0 | N/A | 1 to 255 | 0.002 | 0.49 |
| Emis_16 | Daily Band 16 emissivity | N/A | 8-bit unsigned integer | 0 | N/A | 1 to 255 | 0.002 | 0.49 |
| LST_1KM | Daily 1km Land-surface Temperature | Kelvin | 16-bit unsigned integer | 0 | N/A | 7500 to 65535 | 0.02 | N/A |
| QC | Daily QC for LST and emissivity | N/A | 16-bit unsigned integer | N/A | N/A | 0 to 65535 | N/A | N/A |
| View_Angle | View zenith angle of LST | Degree | 8-bit unsigned integer | 255 | N/A | 0 to 130 | N/A | -65 |
| View_Time | Time of LST observation | Hours | 8-bit unsigned integer | 255 | N/A | 0 to 240 | 0.1 | N/A |
The final quality bit for the output product reflects the lowest quality values from all observations that went into the final average. The bit flags for the QC layer are defined in Table 7 on pages 22-23 of the User Guide.
The quality layer is stored in an efficient bit-encoded manner. The unpack_sds_bits executable from the LDOPE Tools is available to the user community to help parse and interpret the quality layer.
Quality assurance information should be considered when determining the usability of data for a particular science application. The ArcGIS MODIS-VIIRS Python Toolbox contains tools capable of decoding quality data layers while producing thematic quality raster files for each quality attribute.
For additional information on product quality, refer to the VIIRS Land Product Quality website.
For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website and the User Guide.