Getting Started with MODIS Version 6 Vegetation Indices 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 Vegetation Indices Data” video series.
This video will cover the Quality information associated with Vegetation
Indices 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 Vegetation Indices product is distributed as a
Hierarchical Data Format or HDF file. Each MODIS HDF file contains
associated Quality science dataset layers, which provide users with
information regarding the usability and usefulness of the data products.
Here is an example of the science dataset layers for the Terra MODIS
Version 6 16-day Vegetation Indices 500 meter level 3 gridded product,
MOD13A1.The information extracted from these quality science datasets
can be used to filter data based on different levels of quality.
There are two Quality Assurance or QA science dataset layers that can
come with the MODIS Version 6 Vegetation Indices data products. The first is
the Vegetation Indices or VI - Quality layer, which provides pixel-level
quality assignment information. The other is the Pixel Reliability,
which provides simple ranks that capture the overall pixel quality.
The Pixel Reliability can be directly interpreted and requires no detailed
post-processing and interpretation. More detailed information about 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 VI Quality science dataset layers
are 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 16-Day Vegetation Indices
250 meter level 3 gridded MOD13Q1 data product.
Here is the integer value of one pixel from the 250 meter 16-Day
VI Quality layer, this number will convert to this 16-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 bit-string is read
from right to left. For example, the Bit-Word for Bit-No. 0-1, VI quality,
is 00 which means the pixel produced with good quality and no issues.
Bit-No. 2-5, the VI usefulness, is identified using the Bit-Word 0001,
which means the pixel is of lower quality, based on the 16 level rank from
0000 to 1111. Follow the same pattern to interpret the additional bits.
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 for examining QA information is the Application
for Extracting and Exploring Analysis Ready Samples or AppEEARS.
This application can be used to visualize the QA information and
allows users to filter data within AppEEARS by Modland QA bit.
Furthermore, AppEEARS also provides users with fully decoded MODIS 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. The Pixel Reliability QA information
does not require any post-processing unpacking of bits. Pixel Reliability
is an 8-bit integer that provides simple ranks that capture the overall
pixel quality. Ranks -1 to 3 apply to all of the Vegetation Indices products,
rank 4 relates directly to the Vegetation Indices Climate Modeling
Grid (CMG) products. Detailed materials about Vegetation Indices 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
Vegetation Indices data please visit the LP DAAC website at lpdaac.usgs.gov.