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, O
the O
abundance O
of O
information O
from O
satellites O
, O
government O
records O
, O
social O
media O
, O
and O
human B-climate-assets
health I-climate-assets
sources O
, O
now O
requires O
complex O
and O
challenging O
data O
integration O
approaches O
. O
Here O
, O
we O
describe O
Fire B-climate-models
Events I-climate-models
Delineation I-climate-models
( O
FIRED B-climate-models
) O
, O
an O
event O
- O
delineation O
algorithm O
, O
that O
has O
been O
used O
to O
derive O
fire B-climate-hazards
events O
( O
N O
= O
51,871 O
) O
from O
the O
MODIS B-climate-datasets
MCD64 I-climate-datasets
burned B-climate-properties
area I-climate-properties
product O
for O
the O
coterminous O
US O
( O
CONUS O
) O
from O
January O
2001 O
to O
May O
2019 O
. O
The O
optimized O
spatial O
and O
temporal O
parameters O
to O
cluster O
burned B-climate-properties
area I-climate-properties
pixels O
into O
events O
were O
an O
11 O
- O
day O
window O