MOD13Q1 v061

MODIS/Terra Vegetation Indices 16-Day L3 Global 250 m SIN Grid


PI: Kamel Didan

Description

The Terra Moderate Resolution Imaging Spectroradiometer (MODIS) Vegetation Indices (MOD13Q1) Version 6.1 data are generated every 16 days at 250 meter (m) spatial resolution as a Level 3 product. The MOD13Q1 product provides two primary vegetation layers. The first is the Normalized Difference Vegetation Index (NDVI) which is referred to as the continuity index to the existing National Oceanic and Atmospheric Administration-Advanced Very High Resolution Radiometer (NOAA-AVHRR) derived NDVI. The second vegetation layer is the Enhanced Vegetation Index (EVI), which has improved sensitivity over high biomass regions. The algorithm chooses the best available pixel value from all the acquisitions from the 16 day period. The criteria used is low clouds, low view angle, and the highest NDVI/EVI value.

Along with the vegetation layers and the two quality layers, the HDF file will have MODIS reflectance bands 1 (red), 2 (near-infrared), 3 (blue), and 7 (mid-infrared), as well as four observation layers.

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Characteristics

Improvements/Changes from Previous Versions

  • The Version 6.1 Level-1B (L1B) products have been improved by undergoing various calibration changes that include: changes to the response-versus-scan angle (RVS) approach that affects reflectance bands for Aqua and Terra MODIS, corrections to adjust for the optical crosstalk in Terra MODIS infrared (IR) bands, and corrections to the Terra MODIS forward look-up table (LUT) update for the period 2012 - 2017.
  • A polarization correction has been applied to the L1B Reflective Solar Bands (RSB).

Product Maturity

Validation at stage 3 has been achieved for the MODIS Vegetation Index product suite. Further details regarding MODIS land product validation for the MOD13 data products are available from the MODIS Land Team Validation site.

Collection and Granule

Collection

Characteristic Description
CollectionTerra MODIS
DOI10.5067/MODIS/MOD13Q1.061
File Size~93 MB
Temporal ResolutionMulti-Day
Temporal Extent2000-02-18 to Present
Spatial ExtentGlobal
Coordinate SystemSinusoidal
DatumN/A
File FormatHDF-EOS
Geographic Dimensions1200 km x 1200 km

Granule

Characteristic Description
Number of Science Dataset (SDS) Layers12
Columns/Rows4800 x 4800
Pixel Size250 m

Layers / Variables

SDS Name Description Units Data Type Fill Value No Data Value Valid Range Scale Factor
250m 16 days NDVI 16 day NDVI NDVI 16-bit signed integer -3000 N/A -2000 to 10000 0.0001
250m 16 days EVI 16 day EVI EVI 16-bit signed integer -3000 N/A -2000 to 10000 0.0001
250m 16 days VI Quality VI quality indicators Bit Field 16-bit unsigned integer 65535 N/A 0 to 65534 N/A
250m 16 days red reflectance Surface Reflectance Band 1 N/A 16-bit signed integer -1000 N/A 0 to 10000 0.0001
250m 16 days NIR reflectance Surface Reflectance Band 2 N/A 16-bit signed integer -1000 N/A 0 to 10000 0.0001
250m 16 days blue reflectance Surface Reflectance Band 3 N/A 16-bit signed integer -1000 N/A 0 to 10000 0.0001
250m 16 days MIR reflectance Surface Reflectance Band 7 N/A 16-bit signed integer -1000 N/A 0 to 10000 0.0001
250m 16 days view zenith angle View zenith angle of VI Pixel Degree 16-bit signed integer -10000 N/A 0 to 18000 0.01
250m 16 days sun zenith angle Sun zenith angle of VI pixel Degree 16-bit signed integer -10000 N/A 0 to 18000 0.01
250m 16 days relative azimuth angle Relative azimuth angle of VI pixel Degree 16-bit signed integer -4000 N/A -18000 to 18000 0.01
250m 16 days composite day of the year Day of year VI pixel Julian day 16-bit signed integer -1 N/A 1 to 366 N/A
250m 16 days pixel reliability Quality reliability of VI pixel Rank 8-bit signed integer -1 N/A 0 to 3 N/A

Product Quality

The QA bit flags for the "250m 16 days pixel reliability" layer are provided in Table 4 and the "250m 16 days VI Quality" in Table 5 of the User Guide.

In areas where no valid VI is retrieved, VI Quality bits 11-13 are correctly assigned to indicate the land/water type. The other bits are set to 1 which can create a false notion of the parameter description; however, since no valid VI is retrieved these values can be ignored.

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.

The "250m 16 days VI Quality" 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 QC layers.

Known Issues

For complete information about known issues please refer to the MODIS/VIIRS Land Quality Assessment website.


About the image

Terra MODIS NDVI data from the MOD13Q1 product over part of Brazil July 27 - August 11, 2020.

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Documentation

User Guide
Algorithm Theoretical Basis Document (ATBD)
File Specification

Using the Data

Data In Action

Highlights from the Literature: January to March 2017

MODIS Vegetation Indices: A Zoological Approach

Highlights from the Literature: April to June 2018

Highlights from the NASA DEVELOP National Program Summer 2017 Term

Montana Climate Atlas Features MODIS Data

Highlights from the Literature: January to March 2018

Highlights from the Literature: October to December 2017

Highlights from the Literature: April to June 2017

Monitoring Phenology in the National Parks

Highlights from the Literature: October to December 2016

Highlights from the Literature: April to June 2015

Up a Creek Without a Paddle: Fish Conservation in Remote Regions

Highlights from the Literature: July to September 2015

Highlights from the Literature: July to September 2016

Highlights from the Literature: April to June 2016

Will Cape Town Run Out of Water?

Using MODIS to Meet the Challenges of West Nile Virus Outbreaks

Why Do Leaves Change Color?

Highlights from the Literature: October to December 2015

Highlights from the NASA DEVELOP National Program Summer 2015 Term

Highlights from the Literature: October to December 2014

Impacts of the Largest Dam in China on the Local Vegetation Cover

Highlights from the Literature: July to September 2018

Sensing Our Planet: NASA Earth Science Research Features 2017

Highlights from the Literature: October to December 2018

Highlights from the Literature: January to March 2019

Mapping Deforestation

Highlights from the Literature: July to September 2019

Highlights from the Literature: October to December 2019

Highlights from the NASA DEVELOP National Program Fall 2018 Term

Highlights from the Literature: January to March 2020

Highlights from the Literature: April to June 2020

Highlights from the Literature: July to September 2020

Highlights from the Literature: October to December 2020

Access Data

Citation

DOI: 10.5067/MODIS/MOD13Q1.061