Advances in environmental engineering and green technologies book series,
Год журнала:
2023,
Номер
unknown, С. 114 - 134
Опубликована: Ноя. 24, 2023
Google
Earth
Engine
(GEE)
has
emerged
as
a
powerful
platform
for
modeling
and
monitoring
extreme
hydrometeorological
events.
In
recent
years,
GEE
been
used
extensively
studying
floods,
droughts,
other
natural
disasters.
It
offers
comprehensive
suite
of
tools
that
can
help
researchers
practitioners
better
understand
the
complex
interactions
between
weather,
climate,
water
resources.
By
providing
access
to
wealth
satellite
imagery,
climate
data,
geospatial
datasets,
enables
users
model
monitor
these
events
with
unprecedented
accuracy
efficiency.
This
book
chapter
explores
various
ways
in
which
be
events,
understanding
their
needs,
including
case
studies
practical
examples.
It's
worth
noting
this
mainly
focuses
on
using
remote
sensing
data
analysis
into
monitoring.
Research Square (Research Square),
Год журнала:
2023,
Номер
unknown
Опубликована: Ноя. 7, 2023
Abstract
The
effects
of
global
warming
and
climate
change
are
being
felt
through
more
extreme
prolonged
periods
drought.
Multiple
meteorological
indices
used
to
measure
drought,
but
they
require
hydrometeorological
data;
however,
other
measured
by
remote
sensing
quantify
vegetation
vigor
can
be
correlated
with
the
former.
This,
this
study
investigated
correlation
between
both
index
types
type
season.
correlations
were
also
spatially
modeled
in
a
drought
event
southwestern
Spain.
In
addition,
three
maps
different
levels
detail
terms
categorization
compared.
results
generally
showed
that
grassland
was
most
well
category
SPEI
FAPAR,
LAI
NDVI.
This
pronounced
autumn
spring,
which
is
when
changes
senescence
occur.
spatiotemporal
analysis
indicated
very
similar
behavior
for
grasslands
grouped
an
area
adaptation
as
having
high
evapotranspiration
forecast.
Finally,
forest-based
forecast
analysis,
best
explained
performance
again
NDVI,
lag
up
20
days.
Therefore,
remotely
sensed
good
indicators
status
variably
explanatory
traditional
indicators.
Moreover,
complementing
made
it
possible
detect
areas
particularly
vulnerable
change.
Advances in environmental engineering and green technologies book series,
Год журнала:
2023,
Номер
unknown, С. 114 - 134
Опубликована: Ноя. 24, 2023
Google
Earth
Engine
(GEE)
has
emerged
as
a
powerful
platform
for
modeling
and
monitoring
extreme
hydrometeorological
events.
In
recent
years,
GEE
been
used
extensively
studying
floods,
droughts,
other
natural
disasters.
It
offers
comprehensive
suite
of
tools
that
can
help
researchers
practitioners
better
understand
the
complex
interactions
between
weather,
climate,
water
resources.
By
providing
access
to
wealth
satellite
imagery,
climate
data,
geospatial
datasets,
enables
users
model
monitor
these
events
with
unprecedented
accuracy
efficiency.
This
book
chapter
explores
various
ways
in
which
be
events,
understanding
their
needs,
including
case
studies
practical
examples.
It's
worth
noting
this
mainly
focuses
on
using
remote
sensing
data
analysis
into
monitoring.
