Terra MODIS percent tree cover (PTC) data from the MOD44B product over the Great lakes, United States, 2016.
View full-size imageThe MOD44B Version 6 Vegetation Continuous Fields (VCF) yearly product is a global representation of surface vegetation cover as gradations of three ground cover components: percent tree cover, percent non-tree cover, and percent non-vegetated (bare). VCF products provide a continuous, quantitative portrayal of land surface cover at 250 meter (m) pixel resolution, with a sub-pixel depiction of percent cover in reference to the three ground cover components. The sub-pixel mixture of ground cover estimates represents a revolutionary approach to the characterization of vegetative land cover that can be used to enhance inputs to environmental modeling and monitoring applications.
The MOD44B data product layers include percent tree cover, percent non-tree cover, percent non-vegetated, cloud cover, and quality indicators. The start date of the annual period for this product begins with day of year (DOY) 65 (March 6 except for leap year which corresponds to March 5).
The MOD44B Version 6 VCF was produced with the same code and training as the Version 5 products, but improvements to the upstream inputs result in more accurate VCF products.
Validation at stage 3 has been achieved for the MODIS Vegetation Continuous Fields data product. Further details regarding MODIS land product validation for the MOD44B data are available from the MODIS Land Team Validation site.
| Characteristic | Description |
|---|---|
| Collection | Terra MODIS |
| DOI | 10.5067/MODIS/MOD44B.006 |
| File Size | 25 MB |
| Temporal Resolution | Yearly |
| Temporal Extent | 2000-03-05 to 2021-03-06 |
| 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 | 7 |
| Columns/Rows | 4800 x 4800 |
| Pixel Size | 250 m |
| SDS Name | Description | Units | Data Type | Fill Value | No Data Value | Valid Range | Scale Factor |
|---|---|---|---|---|---|---|---|
| Percent_Tree_Cover | Percent of pixel that is tree covered | Percent | 8-bit unsigned integer | 200=water;253=fill | N/A | 0 to 100 | N/A |
| Percent_NonTree_Vegetation | Percent of pixel that is nontree vegetation | Percent | 8-bit unsigned integer | 200=water;253=fill | N/A | 0 to 100 | N/A |
| Percent_NonVegetated | Percent of pixel non vegetated | Percent | 8-bit unsigned integer | 200=water;253=fill | N/A | 0 to 100 | N/A |
| Quality | Quality Control indicators | Bit Field | 8-bit unsigned integer | N/A | N/A | See Quality Table | N/A |
| Percent_Tree_Cover_SD | Standard deviation of percent tree covered | Percent | 16-bit unsigned integer | -100 | N/A | 0 to 10000 | 0.01 |
| Percent_NonVegetated_SD | Standard deviation of percent not vegetated | Percent | 16-bit unsigned integer | -100 | N/A | 0 to 10000 | 0.01 |
| Cloud | Pixel cloud cover indicators | Bit Field | 8-bit unsigned integer | N/A | N/A | See Cloud Table | N/A |
| Bit | Input Layers | State |
|---|---|---|
| 0 | DOY 065 to 097 | 0 Clear; 1 Bad |
| 1 | DOY 113 to 145 | 0 Clear; 1 Bad |
| 2 | DOY 161 to 193 | 0 Clear; 1 Bad |
| 3 | DOY 209 to 241 | 0 Clear; 1 Bad |
| 4 | DOY 257 to 289 | 0 Clear; 1 Bad |
| 5 | DOY 305 to 337 | 0 Clear; 1 Bad |
| 6 | DOY 353 to 017 | 0 Clear; 1 Bad |
| 7 | DOY 033 to 045 | 0 Clear; 1 Bad |
| Bit | Input Layers | State |
|---|---|---|
| 0 | DOY 065 to 097 | 0 Clear; 1 Cloudy |
| 1 | DOY 113 to 145 | 0 Clear; 1 Cloudy |
| 2 | DOY 161 to 193 | 0 Clear; 1 Cloudy |
| 3 | DOY 209 to 241 | 0 Clear; 1 Cloudy |
| 4 | DOY 257 to 289 | 0 Clear; 1 Cloudy |
| 5 | DOY 305 to 337 | 0 Clear; 1 Cloudy |
| 6 | DOY 353 to 017 | 0 Clear; 1 Cloudy |
| 7 | DOY 033 to 045 | 0 Clear; 1 Cloudy |
The Quality and Cloud layers are 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 these layers.
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.
For complete information about the MOD44B known issues please refer to the MODIS Land Quality Assessment website.