Azo Dye Bioremediation: An Interdisciplinary Path to Sustainable Fashion
Environmental Technology & Innovation,
Journal Year:
2024,
Volume and Issue:
unknown, P. 103832 - 103832
Published: Sept. 1, 2024
Language: Английский
Evaluation of machine learning models for accurate prediction of heavy metals in coal mining region soils in Bangladesh
Ram Proshad,
No information about this author
Krishno Chandra,
No information about this author
Maksudul Islam
No information about this author
et al.
Environmental Geochemistry and Health,
Journal Year:
2025,
Volume and Issue:
47(5)
Published: April 23, 2025
Language: Английский
A hierarchical residual correction-based hyperspectral inversion method for soil heavy metals considering spatial heterogeneity
Yulong Wang,
No information about this author
Bin Zou,
No information about this author
Sha Li
No information about this author
et al.
Journal of Hazardous Materials,
Journal Year:
2024,
Volume and Issue:
479, P. 135699 - 135699
Published: Aug. 28, 2024
Language: Английский
Remote sensing of illegal dumps through supervised classification of satellite images: application in Oaxaca, Mexico
Cuadernos de Investigación Geográfica,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Nov. 19, 2024
Various
economic,
social,
and
cultural
factors
have
contributed
to
the
proliferation
of
illegal
dumps,
causing
urban
image
degradation,
population
health
impacts,
soil,
air,
water
contamination.
Scientists
developed
remote
sensing
techniques
identify
these
red
spots
thus
contribute
their
mitigation
control.
They
recently
used
detect
large
areas
waste
dumping
instead
using
expensive
field
monitoring.
Artificial
intelligence
algorithms
been
process
satellite
images
due
availability
increase
in
processing
capacity
computer
systems.
This
work
presents
results
a
remote-sensing
procedure
dumps
one
hydrographic
subbasin
Oaxaca,
Mexico,
through
supervised
land
cover
classification
Random
Forest
classifier.
Two
hundred
fifty-six
control
polygons
were
train
The
criteria
twelve
bands
Sentinel
2A
with
spatial
resolution
10x10
meters,
spectral
indices
NDVI,
MNDWI,
SAVI,
NDBI,
BSI,
surface
slope.
Google
Earth
Engine
platform
was
images.
There
288,100
hectares
classified
this
way:
65.4%
as
vegetation,
31.5%
like
bare
2.7%
soil
rest
or
garbage.
A
confusion
matrix
calculated
accuracy
model
0.9517.
not
able
accurately
distinguish
between
garbage
similarity
fingerprints.
NDVI
SAVI
most
important
for
detecting
litter,
those
might
building
fingerprint
litter
future.
Poorly
discarded
photointerpretation
post-processing.
Finally,
thirty-two
probable
identified,
which
confirmed
on
territory.
Language: Английский
How Has the Source Apportionment of Heavy Metals in Soil and Water Evolved over the Past 20 Years? A Bibliometric Perspective
Huading Shi,
No information about this author
Zexin He,
No information about this author
Chenning Deng
No information about this author
et al.
Water,
Journal Year:
2024,
Volume and Issue:
16(22), P. 3171 - 3171
Published: Nov. 6, 2024
Exploring
soil
heavy
metal
sources
is
of
great
significance
for
ensuring
the
safety
ecological
environments
and
agricultural
product
safety,
as
well
guiding
pollution
control
management
policies.
This
paper
retrieved
452
research
papers
on
source
analysis
published
over
2004–2024
period
from
Web
Science
database.
The
collected
literature
was
subjected
to
multidimensional
bibliometric
using
CiteSpace
6.3.R1.
results
showed
significantly
increasing
trends
in
scientific
outputs
number
soils
water
study
period.
In
addition,
related
topics
have
expanded
single
multiple
elements
environmental
media
increasingly
recognized
impact
contamination.
Research
methods
also
evolved
basic
statistical
complex
spatial
techniques,
covering
urban
soils.
Previous
studies
focused
different
areas,
has
now
extended
associated
human
health
risks.
present
provides
directions
future
guidance
effective
safe
utilization
land
resources.
Language: Английский