Environmental and Climate Technologies,
Journal Year:
2024,
Volume and Issue:
28(1)
Published: Jan. 1, 2024
Abstract
To
achieve
climate
neutrality
by
2050,
decarbonizing
the
building
sector
is
crucial,
as
it
currently
contributes
36
%
of
greenhouse
gas
emissions
in
Europe.
Monitoring
decarbonization
progress
essential
for
evaluating
our
trajectory
towards
long-term
goals,
facilitating
informed
decision-making.
However,
monitoring
this
issue
unfeasible
due
to
a
lack
real
data.
Despite
challenges
data
gathering,
directives
like
Infrastructure
Spatial
Information
Europe
(INSPIRE)
and
Energy
Performance
Buildings
Directive
(EPBD)
promote
open
accessibility.
overcome
barrier,
paper
suggests
using
georeferencing
automated
cross-referencing
obtain
monitor
effectively.
This
approach
materializes
proposal
national-scale
Urban
Building
Model
(UBEM)
Spain,
which
leverages
from
Certificates
(EPC)
potentially
Digital
Logbooks
(DBL)
enhance
it.
The
study
demonstrates
considerable
potential
approach,
not
only
characterizing
energy
performance
Spanish
buildings
based
on
location,
type,
age
but
also
estimating
consumption,
carbon
dioxide
emissions,
renovation
progress,
assessing
savings,
identifying
energy-inefficient
segments.
Finally,
compares
information
obtained
proposed
model
with
set
indicators
EPBD
recast
new
national
plans,
concluding
that
UBEM
manages
provide
collect
29
and,
when
combined
DBL,
would
be
able
59.
framework
holds
promise
replication
other
MS,
offering
valuable
insights
into
European
stock.
Sustainability,
Journal Year:
2025,
Volume and Issue:
17(3), P. 809 - 809
Published: Jan. 21, 2025
The
precise
selection
of
agricultural
land
is
essential
for
guaranteeing
global
food
security
and
sustainable
development.
Additionally,
suitability
(AgLS)
analysis
crucial
tackling
issues
including
resource
scarcity,
environmental
degradation,
rising
demands.
This
research
examines
the
synergies
trade-offs
among
development
goals
(SDGs)
using
a
hybrid
geographic
information
system
(GIS)–fuzzy
analytic
hierarchy
process
(FAHP)–geostatistical
framework
AgLS
in
Attur
Taluk,
India.
area
was
chosen
its
varied
agro-climatic
conditions,
riverine
habitats,
importance.
Accordingly,
data
from
ten
topographical,
climatic,
soil
physiochemical
variables,
such
as
slope,
temperature,
texture,
were
obtained
analyzed
to
carry
out
study.
geostatistical
demonstrated
spatial
variability
parameters,
providing
insights
into
key
factors
study
area.
Based
on
receiver
operating
characteristic
curve
analysis,
results
showed
that
FAHP
method
(AUC
=
0.71)
outperformed
equal-weighting
scheme
0.602).
Moreover,
mapping
designated
17.31%
highly
suitable
(S1),
41.32%
moderately
(S2),
7.82%
permanently
unsuitable
(N2).
identified
reinforcing
conflicting
correlations
with
SDGs,
emphasizing
need
policies
address
trade-offs.
findings
40%
alignment
climate
action
(SDG
13)
via
improved
resilience,
33%
clean
water
6)
by
identifying
low-salinity
zones,
50%
zero
hunger
2)
through
systems.
Conflicts
arose
SDG
13
(20%)
due
reliance
rain-fed
agriculture,
15
(11%)
2
(13%)
inefficiencies
low-productivity
zones.
A
plan
(SAP)
can
tackle
these
promoting
drought-resistant
crops,
nutrient
management,
participatory
land-use
planning.
provide
replicable
integrating
agriculture
sustainability
objectives
worldwide.
Advances in Applied Energy,
Journal Year:
2023,
Volume and Issue:
12, P. 100155 - 100155
Published: Oct. 6, 2023
The
urban
energy
infrastructure
is
facing
a
rising
number
of
challenges
due
to
climate
change
and
rapid
urbanization.
In
particular,
the
link
between
morphology
systems
has
become
increasingly
crucial
as
cities
continue
expand
more
densely
populated.
Achieving
neutrality
adds
another
layer
complexity,
highlighting
need
address
this
relationship
develop
effective
strategies
for
sustainable
infrastructure.
occurrence
extreme
events
can
also
trigger
cascading
failures
in
system
components,
leading
long-lasting
blackouts.
This
review
paper
thoroughly
explores
incorporating
into
models
through
comprehensive
literature
proposes
new
framework
enhance
resilience
interconnected
systems.
emphasizes
integrated
provide
deeper
insights
design
operation
addresses
failures,
interconnectivity,
compound
impacts
urbanization
on
It
emerging
opportunities,
including
requirement
high-quality
data,
utilization
big
integration
advanced
technologies
like
artificial
intelligence
machine
learning
proposed
integrates
classification,
mesoscale
microscale
process
consider
influence
morphology,
variability,
events.
Given
prevalence
climate-resilient
strategies,
study
underscores
significance
improving
accommodate
future
variations
while
recognizing
interconnectivity
within
International Journal of Applied Earth Observation and Geoinformation,
Journal Year:
2024,
Volume and Issue:
130, P. 103929 - 103929
Published: May 25, 2024
In
the
quest
for
large-scale
photovoltaic
(PV)
panel
extraction,
substantial
data
volumes
are
essential,
given
demand
sub-meter
rooftop
PV
resolution.
This
requires
concept
of
Latent
Photovoltaic
Locations
(LPL)
to
reduce
scope
amount
subsequent
processing.
order
minimize
manual
annotation,
a
pioneering
weakly-supervised
framework
is
proposed,
which
capable
generating
pixel-level
annotations
segmentation
based
on
image-level
and
provides
two
datasets
required
classification-then-segmentation
strategy
without
more
annotations.
The
strong
noise-resistance
Segment
Anything
Model
(SAM)
discovered
in
extremely
difficult
rough
coarse
pseudo-label
refinement,
which,
after
integrating
probability
updating
mechanism,
achieves
seamless
transition
from
scene
classification
semantic
segmentation.
resulting
national
LPL
distribution
map,
rendered
at
2
m
resolution,
showcases
commendable
92
%
accuracy
F1-score
91
%,
advantages
terms
efficiency
have
been
verified
through
large
number
experiments.
process
explores
how
use
fundamental
models
accelerate
remote
sensing
information
extraction
process,
crucial
current
trajectory
deep
learning
sensing.
relevant
code
available
https://github.com/Github-YRQ/LPL.
Buildings,
Journal Year:
2024,
Volume and Issue:
14(6), P. 1774 - 1774
Published: June 12, 2024
The
global
demand
for
energy
is
significantly
impacted
by
the
consumption
patterns
within
building
sector.
As
such,
importance
of
simulation
and
prediction
growing
exponentially.
This
research
leverages
Building
Information
Modelling
(BIM)
methodologies,
creating
a
synergy
between
traditional
software
methods
algorithm-driven
approaches
comprehensive
analysis.
study
also
proposes
method
monitoring
select
management
factors,
step
that
could
potentially
pave
way
integration
digital
twins
in
systems.
grounded
case
newly
constructed
educational
New
South
Wales,
Australia.
physical
model
was
created
using
Autodesk
Revit,
conventional
BIM
methodology.
EnergyPlus,
facilitated
OpenStudio,
employed
software-based
analysis
output
then
used
to
develop
preliminary
algorithm
models
regression
strategies
Python.
In
this
analysis,
temperature
relative
humidity
each
unit
were
as
independent
variables,
with
their
being
dependent
variable.
sigmoid
model,
known
its
accuracy
interpretability,
advanced
simulation.
combined
sensor
data
real-time
prediction.
A
basic
twin
(DT)
example
simulate
dynamic
control
air
conditioning
lighting,
showcasing
adaptability
effectiveness
system.
explores
potential
machine
learning,
specifically
reinforcement
optimizing
response
environmental
changes
usage
conditions.
Despite
current
limitations,
identifies
future
directions.
These
include
enhancing
developing
complex
algorithms
boost
efficiency
reduce
costs.
