A graph-factor-based random forest model for assessing and predicting carbon emission patterns - Pearl River Delta urban agglomeration
Journal of Cleaner Production,
Journal Year:
2024,
Volume and Issue:
469, P. 143220 - 143220
Published: July 20, 2024
Language: Английский
Predictive Modeling of soil salinity integrating remote sensing and soil variables: An ensembled deep learning approach
Energy Nexus,
Journal Year:
2025,
Volume and Issue:
unknown, P. 100374 - 100374
Published: Feb. 1, 2025
Language: Английский
Variability analysis of soil organic carbon content across land use types and its digital mapping using machine learning and deep learning algorithms
Environmental Monitoring and Assessment,
Journal Year:
2025,
Volume and Issue:
197(5)
Published: April 10, 2025
Language: Английский
Assessing Impact of Land Use/Land Cover Dynamic on Urban Climate Change in a Semi-Arid Region – Case Study of Agadir City (Morocco)
Ecological Engineering & Environmental Technology,
Journal Year:
2024,
Volume and Issue:
25(4), P. 172 - 187
Published: Feb. 23, 2024
This
research
sought
to
assess
historically
the
urban
expansion
of
Agadir
city
in
Morocco
within
35-year
timespan
(1984-2019),
and
influence
those
changes
on
regulating
services
Agadir.It
was
achieved
by
applying
support
vector
machine
supervised
(SVM)
algorithm
each
Landsat
products
derive
land
use/
cover
(LULC)
maps.High
accuracy
assessment
values
were
obtained
for
all
classified
maps.Spectral
radiance
model
exploited
successfully
highlight
spatiotemporal
thermal
behavior
surfaces.Terrestrial
carbon
dynamics
LULC
evaluated
a
process-based
model.The
outcomes
this
paper
revealed
an
important
with
loss
vegetation
bare
land.This
evolution
impacts
surface
temperature
(LST)
caused
storage
that
contributes
local
climate
change.These
findings
could
assist
policy-makers
characterize
sustainable
area,
especially,
interpret
how
where
might
alter
regulation
ecosystem
services.
Language: Английский
Dam Siltation in the Mediterranean Region Under Climate Change: A Case Study of Ahmed El Hansali Dam, Morocco
Water,
Journal Year:
2024,
Volume and Issue:
16(21), P. 3108 - 3108
Published: Oct. 30, 2024
Dams
are
vital
for
irrigation,
power
generation,
and
domestic
water
needs,
but
siltation
poses
a
significant
challenge,
especially
in
areas
prone
to
erosion,
potentially
shortening
dam’s
lifespan.
The
Ahmed
El
Hansali
Dam
Morocco
faces
heightened
due
its
upstream
region
being
susceptible
erosion-prone
rocks
high
runoff.
This
study
estimates
the
at
dam
from
construction
up
2014
using
bathymetric
data
Brown
model,
which
is
widely-used
empirical
model
that
calculates
reservoir
trap
efficiency.
Additionally,
evaluates
impact
of
Land
Use
Cover
(LULC)
changes
projected
future
rainfall
until
around
2076
based
on
rates.
results
indicate
LULC,
particularly
temporal
variations
precipitation,
have
dam.
Notably,
strongly
correlated
with
rate,
an
R2
0.92.
efficiency
sediment
trapping
(TE)
97.64%,
meaning
97.64%
catchment
area
trapped
or
deposited
bottom
estimated
annual
specific
yield
about
32,345.79
tons/km2/yr,
accumulation
rate
approximately
4.75
Mm3/yr.
half-life
be
2076,
precipitation
projections
may
extend
this
timeframe
strong
correlation
between
precipitation.
soil
erosion
driven
by
land
management
practices
plays
crucial
role
dynamics.
Hence,
offers
comprehensive
assessment
dynamics
dam,
providing
essential
information
long-term
effects
use
changes,
climate
projections.
These
findings
assist
decision
makers
managing
sedimentation
more
effectively,
ensuring
durability
extending
life.
Language: Английский
A Geospatial Analysis of Vegetation Cover Change and Watershed-Scale Biophysical Impacts in a Low-Income Country Context
Published: Jan. 1, 2024
Low-income
societies
have
limited
resources
for
continuous
data
generation
to
support
watershed
management.
We
utilize
open-source
geospatial
delineate
changes
in
vegetation
cover
between
1974
and
2022
the
Rokel
River
Basin
(RRB)
Western
Area
(WAB)
Sierra
Leone.
rank
watersheds
into
high-risk
a
>10%
net
decline
cover,
moderate-risk
≤10%
low-risk
gain
cover.
elucidate
impacts
of
these
on
carbon-nitrogen
(C:N)
ratio
soil
moisture.
Landsat
imagery,
indexes,
climate,
elevation
were
used
as
input
variables
Random
Forest
classifier
Google
Earth
Engine
(GEE).
Site
visits
made
74
RRB
communities
110
WAB
document
land
use
practices.
The
results
reveal
8
58
WAB,
with
identified
risk
factors
including
farming,
mining,
logging,
urbanization.
C:N
moisture
are
highest
areas
stable
they
sharply
complete
clearance.
With
climate
change
projections
indicating
future
intensification
hydrologic
cycle,
deforestation
could
exacerbate
vulnerability
droughts,
flooding
disasters,
sediment
transport
impacted
watersheds.
Language: Английский
Development of unique soil organic carbon stability index under influence of integrated nutrient management in four major soil orders of India
Journal of Environmental Management,
Journal Year:
2024,
Volume and Issue:
360, P. 121208 - 121208
Published: May 23, 2024
Language: Английский
Soil quality index: a tool to detect the sensitivity to soil erosion in an agricultural catchment from the Middle Atlas of Morocco.
IOP Conference Series Earth and Environmental Science,
Journal Year:
2024,
Volume and Issue:
1398(1), P. 012004 - 012004
Published: Oct. 1, 2024
Abstract
The
present
paper
focuses
on
the
application
of
Soil
Quality
Index
(SQI)
within
Tiguert
catchment,
situated
in
Middle
Atlas
Morocco.
studied
covering
approximately
10.2
km²,
experiences
a
semi-arid
climate
with
irregular
rainfall
and
is
designated
as
an
agricultural
area,
making
it
ideal
site
for
studying
intricate
interactions
between
natural
processes
human
activities.
SQI
developed
part
Mediterranean
Desertification
Land
Use
(MEDALUS)
project
tailored
to
unique
conditions
region.
In
case
calculated
using
formula
that
considers
topographical
slope,
horizontal
depth
soil,
parental
material,
soil
brightness.
Consequently,
results
depict
promising
scenario,
61%
classified
“High
Quality,”
indicating
robust
health
resilience
despite
challenges
posed
by
climate.
31%
categorized
“Moderate
Quality”
underscores
areas
requiring
specific
management
attention,
while
8%
identified
“Low
signals
localized
potentially
influenced
patterns.
Furthermore,
are
closely
linked
erosion
dynamics,
higher
values
associated
improved
resistance
erosion.
dynamic
connection
precipitation
patterns
over
40-year
analysis
indicates
impact
varying
health.
Extreme
events
correspond
percentages
category,
drier
periods
align
lower
percentages,
emphasizing
relationship
quality.
A
comprehensive
across
diverse
ecosystems
reveals
variations
health,
importance
land
approaches
different
use
types
optimize
overall
sustainability.
Language: Английский
Predicción de la fertilidad del suelo mediante aprendizaje automático en la provincia de Alto Amazonas, Perú
Revista Peruana de Investigación Agropecuaria,
Journal Year:
2023,
Volume and Issue:
3(2), P. e63 - e63
Published: Oct. 10, 2023
El
objetivo
del
trabajo
fue
predecir
la
fertilidad
suelo
en
provincia
de
Alto
Amazonas
con
el
uso
imágenes
satelitales
y
técnicas
aprendizaje
automático.
estudio
se
ubicó
Perú.
Se
realizaron
muestreos
suelos
toda
provincia,
totalizando
100
muestras.
Posteriormente
análisis
físicos
(textura)
químicos
suelo.
Las
obtuvieron
USGS
los
índices
vegetación
calcularon
base
estas
imágenes.
Finalmente,
utilizó
descriptivo
modelado
automático
utilizando
06
algoritmos
(GLM,
CUBIST,
KKNN,
SVM,
Random
Forest
NN)
que
seleccionaron
función
su
R2
RMSE.
En
este
observamos
mayoría
tienen
bajos
pH,
P,
Mg,
K
alta
acidez.
También
lograron
obtener
buenas
predicciones
para
Ca,
Mg
CIC
observó
algoritmo
más
exitoso
Forest.
Sin
embargo,
Al,
Cubist
tuvo
mejores
resultados.
Este
es
uno
primeros
trabajos
utiliza
Amazonía
peruana
espera
pueda
servir
como
futuros
proyectos.