The VJ109GA surface reflectance band M5-M4-M3 data over the Mojave Desert, United States on March 8, 2022.
View full-size imageThe Visible Infrared Imaging Radiometer Suite (VIIRS) daily surface reflectance (VJ109GA) Version 2 product provides an estimate of land surface reflectance from the NOAA-20 VIIRS sensor. Data are provided for three imagery bands (I1-I3) at nominal 500 meter resolution (~463 meter) and nine moderate resolution bands (M1-M5, M7, M8, M10, M11) at nominal 1 kilometer (~926 meter) resolution. The 500 meter and 1 kilometer datasets are derived through resampling the native 375 meter and 750 meter VIIRS resolutions, respectively, in the Level 2 input product. These bands are corrected for atmospheric conditions such as the effects of molecular gases, including ozone and water vapor, and for the effects of atmospheric aerosols.
The inputs to the surface reflectance algorithm are top-of-atmosphere reflectance for the VIIRS visible bands,the VIIRS cloud mask and aerosol product, aerosol optical thickness and atmospheric data obtained from the NOAA National Centers for Environmental Prediction (NCEP) reanalysis system. Along with the twelve reflectance bands are reflectance band quality, sensor azimuth angle, solar azimuth angle, sensor zenith angle, solar zenith angle, and observations layers. The reflectance layers from the VJ109GA data product are used as input data for many of the VIIRS land products.
More details can be found in this VIIRS Land V2 Changes document.
Validation at stage 3 has been achieved for the VIIRS Land Surface Reflectance 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/VJ109GA.002 |
| File Size | ~105 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 | 30 |
| Columns/Rows | 2400 (500 m) and 1200 (1000 m) x 2400 (500 m) and 1200 (1000 m) |
| Pixel Size | 1000 m and 500 m |
| SDS Name | Description | Units | Data Type | Fill Value | No Data Value | Valid Range | Scale Factor |
|---|---|---|---|---|---|---|---|
| SensorAzimuth_c | Sensor Azimuth Angle | Degree | 16-bit signed integer | -32768 | N/A | -18000 to 18000 | 0.01 |
| SensorZenith_c | Sensor Zenith Angle | Degree | 16-bit signed integer | -32768 | N/A | 0 to 18000 | 0.01 |
| SolarAzimuth_c | Solar Azimuth Angle | Degree | 16-bit signed integer | -32768 | N/A | -18000 to 18000 | 0.01 |
| SolarZenith_c | Solar Zenith Angle | Degree | 16-bit signed integer | -32768 | N/A | 0 to 18000 | 0.01 |
| SurfReflect_M1_c | 1 km Surface Reflectance Band M1 | N/A | 16-bit signed integer | -28672 | N/A | -100 to 16000 | 0.0001 |
| SurfReflect_M2_c | 1 km Surface Reflectance Band M2 | N/A | 16-bit signed integer | -28672 | N/A | -100 to 16000 | 0.0001 |
| SurfReflect_M3_c | 1 km Surface Reflectance Band M3 | N/A | 16-bit signed integer | -28672 | N/A | -100 to 16000 | 0.0001 |
| SurfReflect_M4_c | 1 km Surface Reflectance Band M4 | N/A | 16-bit signed integer | -28672 | N/A | -100 to 16000 | 0.0001 |
| SurfReflect_M5_c | 1 km Surface Reflectance Band M5 | N/A | 16-bit signed integer | -28672 | N/A | -100 to 16000 | 0.0001 |
| SurfReflect_M7_c | 1 km Surface Reflectance Band M7 | N/A | 16-bit signed integer | -28672 | N/A | -100 to 16000 | 0.0001 |
| SurfReflect_M8_c | 1 km Surface Reflectance Band M8 | N/A | 16-bit signed integer | -28672 | N/A | -100 to 16000 | 0.0001 |
| SurfReflect_M10_c | 1 km Surface Reflectance Band M10 | N/A | 16-bit signed integer | -28672 | N/A | -100 to 16000 | 0.0001 |
| SurfReflect_M11_c | 1 km Surface Reflectance Band M11 | N/A | 16-bit signed integer | -28672 | N/A | -100 to 16000 | 0.0001 |
| SurfReflect_I1_c | 1 km Surface Reflectance Band I1 | N/A | 16-bit signed integer | -28672 | N/A | -100 to 16000 | 0.0001 |
| SurfReflect_I2_c | 1 km Surface Reflectance Band I2 | N/A | 16-bit signed integer | -28672 | N/A | -100 to 16000 | 0.0001 |
| SurfReflect_I3_c | 1 km Surface Reflectance Band I3 | N/A | 16-bit signed integer | -28672 | N/A | -100 to 16000 | 0.0001 |
| SurfReflect_QF1_c | Quality Flag 1 | Bit Field | 8-bit unsigned integer | 255 | N/A | 0 to 254 | N/A |
| SurfReflect_QF2_c | Quality Flag 2 | Bit Field | 8-bit unsigned integer | 255 | N/A | 0 to 254 | N/A |
| SurfReflect_QF3_c | Quality Flag 3 | Bit Field | 8-bit unsigned integer | 255 | N/A | 0 to 254 | N/A |
| SurfReflect_QF4_c | Quality Flag 4 | Bit Field | 8-bit unsigned integer | 255 | N/A | 0 to 254 | N/A |
| SurfReflect_QF5_c | Quality Flag 5 | Bit Field | 8-bit unsigned integer | 255 | N/A | 0 to 254 | N/A |
| SurfReflect_QF6_c | Quality Flag 6 | Bit Field | 8-bit unsigned integer | 255 | N/A | 0 to 254 | N/A |
| SurfReflect_QF7_c | Quality Flag 7 | Bit Field | 8-bit unsigned integer | 255 | N/A | 0 to 254 | N/A |
| land_water_mask_c | Total Additional Observations 1km | Bit Field | 8-bit unsigned integer | 255 | N/A | 0 to 7 | N/A |
| nadd_obs_row_1km | Observations coverage 1 km | N/A | 32-bit signed integer | -1 | N/A | 0 to 2147483647 | N/A |
| nadd_obs_row_500m | Observation coverage 500 m | N/A | 32-bit signed integer | -1 | N/A | 0 to 2147483647 | N/A |
| orbit_pnt_c | Orbit Pointer | N/A | 8-bit signed integer | -1 | N/A | 0 to 15 | N/A |
| iobs_res_c | Observation number | N/A | 8-bit unsigned integer | 255 | N/A | 0 to 254 | N/A |
| obscov_1km_c | Total Additional Observations 1km | Percent | 8-bit signed integer | -1 | N/A | 0 to 100 | .01 |
| obscov_500m_c | Total Additional Observations 500m | Percent | 8-bit signed integer | -1 | N/A | 0 to 100 | .01 |
The bit field mappings for Quality Flag (QF) layers 1 through 7 are provided in the User Guide under Section 3.3.
The Quality Control (QC) 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 complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website and in Section 4.0 of the User Guide.