Optimizing Urban Critical Green Space Development Using Machine Learning
Mohammad Ganjirad,
No information about this author
M. R. Delavar,
No information about this author
Hossein Bagheri
No information about this author
et al.
Sustainable Cities and Society,
Journal Year:
2025,
Volume and Issue:
unknown, P. 106158 - 106158
Published: Jan. 1, 2025
Language: Английский
An enhanced machine learning model for urban air quality forecasting under intense human activities
Yelin Wang,
No information about this author
Fuxiang Xia,
No information about this author
Linlin Yao
No information about this author
et al.
Urban Climate,
Journal Year:
2025,
Volume and Issue:
60, P. 102359 - 102359
Published: March 1, 2025
Language: Английский
LOD1 3D city model from LiDAR: The impact of segmentation accuracy on quality of urban 3D modeling and morphology extraction
Fatemeh Chajaei,
No information about this author
Hossein Bagheri
No information about this author
Remote Sensing Applications Society and Environment,
Journal Year:
2025,
Volume and Issue:
unknown, P. 101534 - 101534
Published: April 1, 2025
Language: Английский
U-Surf: a global 1 km spatially continuous urban surface property dataset for kilometer-scale urban-resolving Earth system modeling
Earth system science data,
Journal Year:
2025,
Volume and Issue:
17(5), P. 2147 - 2174
Published: May 21, 2025
Abstract.
High-resolution
urban
climate
modeling
has
faced
substantial
challenges
due
to
the
absence
of
a
globally
consistent,
spatially
continuous,
and
accurate
dataset
represent
spatial
heterogeneity
surfaces
their
biophysical
properties.
This
deficiency
long
obstructed
development
urban-resolving
Earth
system
models
(ESMs)
ultra-high-resolution
modeling,
over
large
domains.
Here,
we
present
U-Surf,
first-of-its-kind
1
km
resolution
present-day
(circa
2020)
global
continuous
surface
parameter
dataset.
Using
canopy
model
(UCM)
in
Community
System
Model
as
base
for
satisfying
requirements,
U-Surf
leverages
latest
advances
remote
sensing,
machine
learning,
cloud
computing
provide
most
relevant
parameters,
including
radiative,
morphological,
thermal
properties,
UCMs
at
facet
level.
Generated
using
systematically
unified
workflow,
ensures
internal
consistency
among
key
making
it
first
coherent
significantly
improves
representation
land
both
within
across
cities
globally;
provides
essential,
high-fidelity
constraints
ESMs;
enables
detailed
city-to-city
comparisons
globe;
supports
next-generation
kilometer-resolution
scales.
parameters
can
be
easily
converted
or
adapted
various
types
UCMs,
such
those
embedded
weather
regional
models,
well
air
quality
models.
The
fundamental
provided
by
also
used
features
learning
have
other
broad-scale
applications
socioeconomic,
public
health,
planning
contexts.
We
expect
advance
research
frontier
science,
climate-sensitive
design,
coupled
human–Earth
systems
future.
is
publicly
available
https://doi.org/10.5281/zenodo.11247598
(Cheng
et
al.,
2024).
Language: Английский
Mechanism of Urban Spatial Morphology and Eco-Environmental Risk: A Case Study of Shenzhen, China
Yijia Yang,
No information about this author
Feng Zhao,
No information about this author
Zhu Xue-xin
No information about this author
et al.
International Journal of Environmental Research,
Journal Year:
2024,
Volume and Issue:
19(2)
Published: Dec. 23, 2024
Language: Английский
Reproduction of Road Scenarios for Simulated Driving Using LiDar Surveying Technique
Rosa Finelli,
No information about this author
Pasquale Sena,
No information about this author
Angelo Lorusso
No information about this author
et al.
Machines,
Journal Year:
2024,
Volume and Issue:
13(1), P. 4 - 4
Published: Dec. 25, 2024
Nowadays,
driving
simulation
devices
represent
a
continuously
evolving
and
developing
area
in
the
world
of
virtual
reality.
One
fundamental
elements
design
software
is
track
model.
This
work
aims
to
study
use
advanced
technologies
for
three-dimensional
modeling
racing
simulator.
Specifically,
it
employs
LiDAR
methodology
acquire
coordinates
1
km
long
circuit
located
on
Fisciano
campus
University
Salerno.
The
purpose
this
explain
present
novel
acquisition
within
realm
simulated
Following
study,
Virtual
Reality
Laboratory’s
simulator
at
Department
Industrial
Engineering
conducted
tests
validate
proposed
test
rides
analyzed
realism
experience,
thereby
validating
phase
was
complemented
by
series
proposals
possible
future
developments
field
applied
beyond.
In
end,
3D
model
obtained
demonstrated
high
definition
acquired
result
speed
with
which
multiple
data
were
simultaneously,
thanks
laser
scanner
used.
Language: Английский