Welcome to the LANCE-MODIS data system operated by the GSFC
Terrestrial Information Systems Laboratory, Code 619.
LANCE-MODIS provides certain Aqua
and Terra MODIS L0, L1, L2, L2G, L3 products, and NPP VIIRS L2 products
on a near-real-time basis. On average, the MODIS L1 and L2 products are available
within 3 hours and VIIRS products with 3.5 hours of the observation time.
Data products may be accessed from the HTTPS site.
LANCE-MODIS produces Collections 6 and 6.1 (C6 and C6.1) MODIS land and atmosphere NRT products,
which are very similar to the standard MODIS products with some minor differences;
these differences (described in the About section) facilitate their shortened production schedules.
We currently provide both the earlier C6 and the more recent C6.1 collections as we transition from one to the other.
C6.1 represents the best quality MODIS science products to date. Hence, users are strongly encouraged to
switch to using C6.1 Level 1 and Atmosphere NRT products as soon as is feasible, since we plan to phase out C6 Level 1 and Atmosphere NRT production around November 1. 2017.
LANCE-MODIS is part of a larger system, called LANCE (Land, Atmosphere Near-real-time Capability for EOS,
which includes four near-real-time systems: the GES DISC AIRS and MLS systems, the
OMI SIPS, AMSR SIPS, and this system.
Detailed information about LANCE-MODIS including the hardware
configuration, the data flows, and metrics.
Information about LANCE-MODIS data products including latency
information, PGE versions, and a comparison of NRT and standard
Known issues with LANCE-MODIS data products.
Contact information for LANCE-MODIS user services.
Users must register before accessing LANCE-MODIS data products on
the HTTPS Site.
2012.09.10 - NRL-UND product
The Naval Research Laboratory and the University of North
Dakota developed a value-added aerosol optical depth dataset based
on MODIS Level 2 aerosol products. The NRL-UND product is a level 3
gridded product specifically designed for quantitative applications
including data assimilation and model validation. This dataset has
been given the ESDT identifier MxDAODHD
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