Menba Kastamonu Üniversitesi Su Ürünleri Fakültesi Dergisi,
Journal Year:
2024,
Volume and Issue:
10(2), P. 29 - 42
Published: Aug. 26, 2024
Sanayi
devriminden
bu
yana
küresel
olarak
gerçekleşen
ısınma
etkisi,
insan
toplumlarını
tehdit
ettiği
gibi
birçok
flora
ve
fauna
yaşamını
da
etmektedir.
Bu
nedenle
iklim
değişikliği
yol
açtığı
ısınma,
günümüzde
karşı
karşıya
olduğumuz
önemli
çevresel
sorunlardan
biri
kabul
edilmektedir.
Küresel
değişikliğinin
etkiler,
yer
yüzünün
farklı
coğrafyalarında
şekillerde
hissedilmektedir.
Örneğin,
Türkiye
özellikle
de
güney
bölgeleri
sahip
olduğu
coğrafi
konum
itibariyle
değişikliğine
savunmasız
ülkeler
arasında
almaktadır.
çalışmada,
Güneydoğu
Anadolu
Bölgesi
sınırları
içerisinde
alan
Dicle
Bölümünün
bir
yöresi
olan
Diyarbakır
Havzasında
(Diyarbakır
Çanağı
Yöresi),
sıcaklık
eğilimlerinin
incelenmesi
amaçlanmıştır.
amaç
kapsamında,
çalışma
alanında
dağılış
gösteren
Batman,
Diyarbakır,
Ergani
Siirt
meteoroloji
istasyonlarının
1964-2023
yıllarına
ait
yıllık
mevsimlik
ortalama
sıcaklık,
maksimum
minimum
kayıtlarına
trend
analizleri
uygulanmıştır.
analizler
Mann-Kendall
Testi,
Spearman’s
RHO
Mertebe
Korelasyon
Testi
Sen’s
Trend
Yöntemi
kullanılarak
gerçekleştirilmiştir.
Elde
edilen
testlerine
göre,
tüm
istasyonların
sıcaklıklarında
istatistiksel
anlamlı
eğilimleri
tespit
edilmiştir.
Yıllık
sıcaklıklarda
ise
sadece
istasyonlarında
Tüm
yaz
mevsimi
sıcaklıklarının
kuvvetli
eğilimi
gösterdiği
belirlenmiştir.
Computational Urban Science,
Journal Year:
2025,
Volume and Issue:
5(1)
Published: April 8, 2025
Abstract
Urban
areas
globally
have
become
home
to
over
half
of
the
world's
population,
leading
intensification
urban
heat
island
(UHI)
effect,
where
cities
experience
higher
temperatures
than
their
rural
counterparts.
The
current
study
develops
a
new
model
predicting
UHI
intensity
for
216
across
all
climate
zones
both
Global
North
and
South
using
machine
learning
techniques,
focusing
on
years
2019
2023.
Utilising
novel
dataset,
integrating
climate,
economic,
land
use
data
from
worldwide,
model,
trained
Support
Vector
Regression
(SVR),
demonstrates
mean
absolute
error
(MAE)
0.86
°C.
Results
reveal
that
wind
speed
significantly
mitigates
intensity,
while
in
temperate
climates
exhibit
more
pronounced
effects
compared
those
located
within
tropical
climbs.
Additionally,
results
show
crucial
role
coastal
proximity
reducing
find
no
significant
differences
between
South.
Findings
offer
important
empirical
actionable
insights
alongside
robust
tool
planners
policymakers
measure,
map,
monitor
contributing
development
liveable
sustainable
environments.
Advances in Meteorology,
Journal Year:
2024,
Volume and Issue:
2024, P. 1 - 19
Published: April 22, 2024
The
rapid
development
of
urbanization
makes
the
phenomenon
urban
heat
islands
even
more
serious.
Predicting
impact
land
cover
change
on
island
has
become
one
research
hotspots.
Taking
Wuhan,
China,
as
an
example,
this
study
simulated
type
in
2020
through
Cellular
Automata-Markov-Chain
(CA-Markov)
model.
was
and
analyzed
conjunction
with
Weather
Research
&
Forecasting
Model
(WRF),
simulation
results
wind
velocity
temperature
were
confirmed
using
weather
station
observation
data.
Based
this,
Wuhan
2030
predicted.
found
to
be
well-fit
by
CA-Markov
use
data,
average
inaccuracy
about
2.5°C
for
stations.
Wind
speed
had
a
poor
fitting
effect;
error
roughly
2
m/s.
built-up
area
center
high
both
before
after
prediction,
water
low
area,
peak
happened
at
night.
According
forecast
results,
there
will
2030,
greater
intensity
than
2020.
Brazilian Journal of Biology,
Journal Year:
2024,
Volume and Issue:
84
Published: Jan. 1, 2024
Abstract
Human
activities
are
altering
the
existing
patterns
of
Land
Use
Cover
(LULC)
and
Surface
Temperature
(LST)
on
a
global
scale.
However,
long-term
trends
LULC
LST
largely
unknown
in
many
remote
mountain
areas
such
as
Karakorum.
.
The
objective
our
study
therefore
was
to
evaluate
historical
changes
land
use
cover
an
alpine
environment
located
Islamabad
Capital
Territory,
Pakistan.
We
used
Landsat
satellite
pictures
(namely
5
TM
8
OLI)
from
years
1988,
2002,
2016
applied
Maximum
Likelihood
Classification
(MLC)
approach
categorize
classes.
Temperatures
were
calculated
using
thermal
bands
(6,
10,
11)
series
data.
correlation
between
Modification
Index
(HMI)
well
evaluated
by
utilizing
data
Google
Earth
Engine
(GEE).
Over
period,
urbanized
area
increased
9.94%,
whilst
agricultural
bare
soil
decreased
3.81%
3.94%,
respectively.
findings
revealed
significant
change
with
decrease
1.99%
vegetation.
highest
class
exhibited
progressive
trend,
increase
12.27%
48.48%.
Based
analysis,
built-up
shows
temperature,
followed
barren,
agricultural,
vegetation
categories.
Similarly,
HMI
for
different
categories
indicates
that
higher
have
levels
human
alteration
compared
lower
categories,
strong
(R-value
=
0.61)
LST.
can
be
utilized
promote
sustainable
urban
management
biodiversity
conservation
efforts.
work
also
has
potential
it
protect
delicate
ecosystems
interference
formulate
strategies
regulations
growth,
including
aspects
utilization
zoning,
reduction
heat
stress,
infrastructure.