Aqua MODIS fire data from the MYD14A2 product over western United States, August 13 - 20, 2018.
View full-size imageThe Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Thermal Anomalies and Fire 8-Day (MYD14A2) Version 6 data are generated at 1 kilometer (km) spatial resolution as a Level 3 product. The MYD14A2 gridded composite contains maximum value of individual fire pixel classes detected during the eight days of acquisition.
The Science Dataset (SDS) layers include the fire mask and pixel quality indicators.
Validation at stage 3 has been achieved for all MODIS Thermal Anomalies and Fire products. Further details regarding MODIS land product validation for the MYD14 data product is available from the MODIS land team validation site.
| Characteristic | Description |
|---|---|
| Collection | Aqua MODIS |
| DOI | 10.5067/MODIS/MYD14A2.006 |
| File Size | ~0.44 MB |
| Temporal Resolution | Multi-Day |
| Temporal Extent | 2002-07-04 to 2023-02-25 |
| Spatial Extent | Global |
| Coordinate System | Sinusoidal |
| Datum | N/A |
| File Format | HDF-EOS |
| Geographic Dimensions | 1200 km x 1200 km |
| Characteristic | Description |
|---|---|
| Number of Science Dataset (SDS) Layers | 2 |
| Columns/Rows | 1200 x 1200 |
| Pixel Size | 1000 m |
| SDS Name | Description | Units | Data Type | Fill Value | No Data Value | Valid Range | Scale Factor |
|---|---|---|---|---|---|---|---|
| FireMask | Confidence of fire | Class Flag | 8-bit unsigned integer | 0 | N/A | 1 to 9 | N/A |
| QA | Pixel Quality Indicators | Bit Field | 8-bit unsigned integer | N/A | N/A | 0 to 6 | N/A |
| Value | Description |
|---|---|
| 0 | Not processed (missing input data) |
| 1 | Not processed (obsolete; not used since Collection 1) |
| 2 | Not processed (other reason) |
| 3 | Non-fire water pixel |
| 4 | Cloud (land or water) |
| 5 | Non-fire land pixel |
| 6 | Unknown (land or water) |
| 7 | Fire (low confidence, land or water) |
| 8 | Fire (nominal confidence, land or water) |
| 9 | Fire (high confidence, land or water) |
The Quality Assurance (QA) 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 QA layer.
The QA bit flags for the QC layer are provided in Table 6 of the User Guide.
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.
In addition to data access and transformation processes, AppEEARS also has the capability to unpack and interpret the quality layers.
Known issues are described on the MODIS/VIIRS Land Quality Assessment website and in Section 7.2 of the User Guide which covers Pre-November 2000 Data Quality, Detection Confidence, Flagging of Static Sources, and the August 2020 MODIS Aqua Outage.