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ibm
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Climate-Change-NER

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Our O
model O
results O
revealed O
that O
this O
predicted O
climate O
change O
could O
reduce O
the O
extent O
of O
a O
suitable O
habitat O
for O
giant B-climate-organisms
pandas I-climate-organisms
by O
up O
to O
62 O
% O
( O
under O
IPCC B-climate-organizations
SRES B-climate-datasets
A2 I-climate-datasets
scenarios O
; O
and O
37 O
% O
under O
IPCC B-climate-organizations
SRES B-climate-datasets
B2 I-climate-datasets
scenarios O
) O
. O
-DOCSTART- -X- O O a295078f98f657aa156c4d9c5719f43f
The O
purpose O
of O
this O
work O
is O
to O
assess O
the O
sugarcane B-climate-assets
yield O
variation O
in O
regional O
scale O
through O
NDVI B-climate-observations
images O
from O
a O
low O
resolution O
spatial O
satellite O
. O
We O
have O
used O
Principal O
Component O
Analysis O
( O
PCA O
) O
and O
Cluster O
Analysis O
to O
correlate O
sugarcane B-climate-assets
cultivated B-climate-assets
land I-climate-assets
with O
multitemporal O
NDVI B-climate-observations
images O
also O
verifying O
the O
influence O
of O
climate O
conditions O