Getting Started with MODIS Version 6 Therm. Anom. & Fire Data Part 3

Getting Started with MODIS Version 6 Thermal Anomalies and Fire Data Part 3: Interpreting Quality Information. Presented by the Land Processes Distributed Active Archive Center or LP DAAC. This is part 3 of the “Getting Started with MODIS Version 6 Thermal Anomalies and Fire Data” video series. This video will cover the Quality information associated with Thermal Anomalies and Fire products. We will discuss the information the quality layers contain, tools that can be used to expose the quality information for further use, and where to find out more information on the LP DAAC’s website. Each Thermal Anomalies and Fire product is distributed as a Hierarchical Data Format or HDF file. Each MODIS Thermal Anomalies and Fire HDF file contains a Quality science dataset layer, which provides users with information regarding the usability and usefulness of the data products. Here is an example of the quality layer for the Terra MODIS Version 6 8-day Thermal Anomalies and Fire 1 kilometer level 3 gridded product, MOD14A2.The information extracted from this quality layer can be used to filter data based on different levels of quality. Each MOD14 Thermal Anomalies & Fire product contains one quality assurance, or QA, layer. The QA layer contains pixel-level quality assurance information. When QA data values are decoded, they provide information on the state of the pixel. This information tells users whether an observation is over land, water, or coast, as well as whether the pixel value is a day or night observation. The MOD14 and MYD14 swath data products also provide additional quality information on the pixel in the QA layer, for example, if atmospheric correction was performed. More detailed information about the specific QA layers for each product can be found in the product User Guide and Algorithm Theoretical Basis Document or ATBD. These documents are available in the “Documentation” section of each Digital Object Identifier or DOI Landing Page. The User Guide provides a more in-depth and up-to-date explanation of the product and the ATBD provides descriptions of the algorithms and calculations that are fundamental to the product. User Guides are updated for each new product version, while ATBD’s are not. The Thermal Anomalies and Fire Quality science dataset layer is binary encoded and bit-packed. Meaning each pixel in the QA layer contains an integer value that must be converted to a bit binary value for interpretation. The bit-string interprets various parameters, as shown by this chart. Here is an example of how to break down a bit binary value using the Terra MODIS MOD14A2 data product. Here is the integer value of one pixel from the 1 kilometer 8-Day Quality layer, this number will convert to this 8-bit binary value. This can be done using a calculator or conversion tool.  Once the binary value is found, the value can be interpreted using the chart. The MODIS Thermal Anomalies and Fire quality layer only uses 4 out of the 8 bits. The bit-string is read from right to left. For example, the Bit-Word for Bit-No. 0-1, land/water state, is 01 which means the pixel is of a coast. Bit-No. 2, day/night algorithm is 1, which means the pixel is from the day. There are several tools that can be used to interpret quality information. One of those tools is the Land Data Operational Products Evaluation or LDOPE QA “unpack_sds_bits” tool, which can be executed from the command line or invoked via scripts.  The unpack_sds_bits tool decodes requested bit fields and writes them to an output HDF file containing a new science dataset that can be viewed with software supporting the HDF or HDF-EOS data formats. More information about the LDOPE Tools can be found under the “Tools” section of the LP DAAC website. Another option to examine QA information is the Application for Extracting and Exploring Analysis Ready Samples or AppEEARS. AppEEARS provides users with fully decoded MODIS Thermal Anomalies and Fire quality information in a .csv file. Finally, the MODIS Python Toolbox provides users with a simple way to decode and interact with quality layers in ArcGIS. One of the tools in the toolbox is the Decode Quality tool. This tool takes the Quality science dataset as an input and creates individual GeoTiff files corresponding to each bit word or quality category described in the Quality science dataset.  Detailed materials about Quality Information are available on the E-Learning page on the LP DAAC website. Search for “quality” in the table to learn more about the QA information and the AppEEARS and Python tools mentioned in this video. Thank you for watching our video. For more information on MODIS Version 6 Thermal Anomalies and Fire data please visit the LP DAAC website at lpdaac.usgs.gov.