Public perceptions towards urban horticulture in front-yard greenhouses: Unveiling ecosystem services and practices for sustainable and resilient city
Sustainable Futures,
Journal Year:
2024,
Volume and Issue:
7, P. 100205 - 100205
Published: May 2, 2024
In
the
pursuit
of
sustainability
and
resilience,
urban
horticulture
holds
immense
promise
for
cities.
This
paper
delves
into
captivating
realm
preferences
in
Iran,
unraveling
factors
that
shape
individuals'
inclinations.
The
results
highlight
influence
greenhouse
design
on
preferences.
Urban
dwellers
prioritize
cultural
ecosystem
services
over
regulating
provisioning
when
engaging
activities.
Anticipated
differ
among
various
socio-demographic
groups.
Different
elements
evoke
distinct
perceptions
services.
However,
certain
greenhouses
can
improve
overall
perception
due
to
strong
correlations
between
different
types
Language: Английский
Contributions to a global understanding of socioenvironmental justice related to urban forest: Trends from Brazilian cities in the southeastern Paraná State
Urban forestry & urban greening,
Journal Year:
2024,
Volume and Issue:
95, P. 128322 - 128322
Published: April 3, 2024
Language: Английский
Evaluating the impact of land use land cover changes on urban ecosystem services in Nashik, India: a RS-GIS based approach
Environmental Earth Sciences,
Journal Year:
2024,
Volume and Issue:
83(24)
Published: Dec. 1, 2024
Language: Английский
Synergies and trade-offs among key ecosystem services in Maze National Park and its environs, southwestern Ethiopia
Global Ecology and Conservation,
Journal Year:
2024,
Volume and Issue:
unknown, P. e03398 - e03398
Published: Dec. 1, 2024
Language: Английский
Biodiversity and Conservation of Forests
Forests,
Journal Year:
2023,
Volume and Issue:
14(9), P. 1871 - 1871
Published: Sept. 14, 2023
Forests
are
extremely
valuable
ecosystems,
associated
with
a
number
of
ecosystem
services
that
significant
importance
for
human
wellbeing
[...]
Language: Английский
Forecasting Dendrolimus sibiricus Outbreaks: Data Analysis and Genetic Programming-Based Predictive Modeling
Forests,
Journal Year:
2024,
Volume and Issue:
15(5), P. 800 - 800
Published: April 30, 2024
This
study
presents
an
approach
to
forecast
outbreaks
of
Dendrolimus
sibiricus,
a
significant
pest
affecting
taiga
ecosystems.
Leveraging
comprehensive
datasets
encompassing
climatic
variables
and
forest
attributes
from
15,000
parcels
in
the
Krasnoyarsk
Krai
region,
we
employ
genetic
programming-based
predictive
modeling.
Our
methodology
utilizes
Random
Forest
algorithm
develop
robust
forecasting
model
through
integrated
data
analysis
techniques.
By
optimizing
hyperparameters
within
model,
achieved
heightened
accuracy,
reaching
maximum
precision
0.9941
up
one
year
advance.
Language: Английский