Enhancing a Simple MODIS Cloud Mask Algorithm for the Landsat Data Continuity Mission

The upcoming Landsat Data Continuity Mission (LDCM) will include new channels centered around 1.38
$\mu\hbox{m}$
and 12
$\mu \hbox{m}$
. This work studies the potential impact of these new channels on LDCM's cloud detection capabilities by using MODerate resolution Imaging Spectroradiometer (MODIS) data as a proxy. Thresholds for the 1.38
$\mu\hbox{m}$
band and the so-called “split window” technique (using the brightness temperature difference of bands centered at 11
$ \mu\hbox{m}$
and 12
$\mu\hbox{m}$
) are derived using atmospheric profiles from the ECMWF ERA-40 reanalysis and a MODIS-band radiance simulator. The thresholds are incorporated into a previously published cloud mask scheme and applied on low- and mid-latitude (60
$^{\circ}$
S to 60
$^{\circ}\ \hbox{N}$
) MODIS radiance data from two different days, six months apart. While the previous scheme yields agreement rates to the MODIS cloud mask just below 80
$\%$
, the addition of the 1.38
$\mu\hbox{m}$
and split window tests increases the agreement by 7–9%. The earlier scheme is still appropriate for cloud masking of historical Landsat images and for carrying consistent cloud detection into the future. The enhanced scheme of this paper, on the other hand, with its improved masking of primarily high thin clouds, can be either used independently or combined with other masking techniques for generating reliable LDCM cloud mask products that can potentially include confidence indicators based on the degree of agreement between multiple cloud masks.