Natural Resources Research,
Год журнала:
2023,
Номер
33(1), С. 129 - 161
Опубликована: Ноя. 25, 2023
Abstract
In
geospatial
data
interpolation,
as
in
mapping,
mineral
resource
estimation,
modeling
and
numerical
geosciences,
kriging
has
been
a
central
technique
since
the
advent
of
geostatistics.
Here,
we
introduce
new
method
for
spatial
interpolation
2D
3D
using
block
discretization
(i.e.,
microblocking)
purely
machine-learning
algorithms
workflow
design.
This
paper
addresses
challenges
patterns
regularities
nature,
how
different
approaches
have
used
to
cope
with
these
challenges.
We
specifically
explore
advantages
drawbacks
while
highlighting
long
complex
sequence
procedures
associated
kriging.
argue
that
techniques
offer
opportunities
simplify
streamline
process
mapping
especially
cases
strong
relationships
between
sample
location
concentration.
To
test
method,
synthetic
were
both
geometallurgical
porphyry
Cu
deposit.
The
very
useful
validating
performance
proposed
microblocking
able
reproduce
known
values
at
unsampled
locations.
Our
delivers
benefits
machine
learning-based
approach,
which
includes
its
simplicity
(a
minimum
2
hyperparameters),
speed
familiarity
scientists.
enables
scientists
working
on
employ
workflows
familiar
their
training,
tackle
problems
previously
solely
domain
geoscience.
exchange,
expect
our
will
be
gateway
attract
more
scientist
become
geodata
scientists,
benefitting
modern
data-driven
value
chain.
Computers and Electronics in Agriculture,
Год журнала:
2022,
Номер
198, С. 107017 - 107017
Опубликована: Май 18, 2022
Drones,
also
called
Unmanned
Aerial
Vehicles
(UAV),
have
witnessed
a
remarkable
development
in
recent
decades.
In
agriculture,
they
changed
farming
practices
by
offering
farmers
substantial
cost
savings,
increased
operational
efficiency,
and
better
profitability.
Over
the
past
decades,
topic
of
agricultural
drones
has
attracted
academic
attention.
We
therefore
conduct
comprehensive
review
based
on
bibliometrics
to
summarize
structure
existing
literature
reveal
current
research
trends
hotspots.
apply
bibliometric
techniques
analyze
surrounding
assess
previous
research.
Our
analysis
indicates
that
remote
sensing,
precision
deep
learning,
machine
Internet
Things
are
critical
topics
related
drones.
The
co-citation
reveals
six
broad
clusters
literature.
This
study
is
one
first
attempts
drone
agriculture
suggest
future
directions.
International Soil and Water Conservation Research,
Год журнала:
2023,
Номер
11(3), С. 429 - 454
Опубликована: Март 15, 2023
Soils
constitute
one
of
the
most
critical
natural
resources
and
maintaining
their
health
is
vital
for
agricultural
development
ecological
sustainability,
providing
many
essential
ecosystem
services.
Driven
by
climatic
variations
anthropogenic
activities,
soil
degradation
has
become
a
global
issue
that
seriously
threatens
environment
food
security.
Remote
sensing
(RS)
technologies
have
been
widely
used
to
investigate
as
it
highly
efficient,
time-saving,
broad-scope.
This
review
encompasses
recent
advances
state-of-the-art
ground,
proximal,
novel
RS
techniques
in
degradation-related
studies.
We
reviewed
RS-related
indicators
could
be
monitoring
properties.
The
direct
(mineral
composition,
organic
matter,
surface
roughness,
moisture
content
soil)
indirect
proxies
(vegetation
condition
land
use/land
cover
change)
evaluating
were
comprehensively
summarized.
results
suggest
these
above
are
effective
degradation,
however,
no
system
established
date.
also
discussed
RS's
mechanisms,
data,
methods
identifying
specific
phenomena
(e.g.,
erosion,
salinization,
desertification,
contamination).
investigated
potential
relations
between
Sustainable
Development
Goals
(SDGs)
challenges
prospective
use
assessing
degradation.
To
further
advance
optimize
technology,
analysis
retrieval
methods,
we
identify
future
research
needs
directions:
(1)
multi-scale
degradation;
(2)
availability
data;
(3)
process
modelling
prediction;
(4)
shared
dataset;
(5)
decision
support
systems;
(6)
rehabilitation
degraded
resource
contribution
technology.
Because
difficult
monitor
or
measure
all
properties
large
scale,
remotely
sensed
characterization
related
particularly
important.
Although
not
silver
bullet,
provides
unique
benefits
studies
from
regional
scales.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing,
Год журнала:
2024,
Номер
17, С. 5920 - 5945
Опубликована: Янв. 1, 2024
Agriculture
can
be
regarded
as
the
backbone
of
human
civilization.
As
technology
evolved,
synergy
between
agriculture
and
remote
sensing
has
brought
about
a
paradigm
shift,
thereby
entirely
revolutionizing
traditional
agricultural
practices.
Nevertheless,
adoption
technologies
in
face
various
challenges
terms
limited
spatial
temporal
coverage,
high
cloud
cover,
low
data
quality
so
on.
Industry
5.0
marks
new
era
industrial
revolution,
where
humans
machines
collaborate
closely,
leveraging
their
distinct
capabilities,
enhancing
decision
making
sustainability
resilience.
This
paper
provides
comprehensive
survey
on
related
aspects
dealing
with
practices
(I5.0)
era.
We
also
elaborately
discuss
applications
pertaining
to
I5.0-
enabled
for
agriculture.
Finally,
we
several
issues
integration
I5.0
sensing.
offers
valuable
insights
into
current
state,
challenges,
potential
advancements
principles
agriculture,
thus
paving
way
future
research,
development,
implementation
strategies
this
domain.
Agriculture,
Год журнала:
2025,
Номер
15(4), С. 377 - 377
Опубликована: Фев. 11, 2025
Machine
learning
(ML)
has
revolutionized
resource
management
in
agriculture
by
analyzing
vast
amounts
of
data
and
creating
precise
predictive
models.
Precision
improves
agricultural
productivity
profitability
while
reducing
costs
environmental
impact.
However,
ML
implementation
faces
challenges
such
as
managing
large
volumes
adequate
infrastructure.
Despite
significant
advances
applications
sustainable
agriculture,
there
is
still
a
lack
deep
systematic
understanding
several
areas.
Challenges
include
integrating
sources
adapting
models
to
local
conditions.
This
research
aims
identify
trends
key
players
associated
with
use
agriculture.
A
review
was
conducted
using
the
PRISMA
methodology
bibliometric
analysis
capture
relevant
studies
from
Scopus
Web
Science
databases.
The
study
analyzed
literature
between
2007
2025,
identifying
124
articles
that
meet
criteria
for
certainty
assessment.
findings
show
quadratic
polynomial
growth
publication
on
notable
increase
up
91%
per
year.
most
productive
years
were
2024,
2022,
2023,
demonstrating
growing
interest
field.
highlights
importance
multiple
improved
decision
making,
soil
health
monitoring,
interaction
climate,
topography,
properties
land
crop
patterns.
Furthermore,
evolved
weather
advanced
technologies
like
Internet
Things,
remote
sensing,
smart
farming.
Finally,
agenda
need
deepening
expansion
predominant
concepts,
farming,
develop
more
detailed
specialized
explore
new
maximize
benefits
sustainability.
Agriculture,
Год журнала:
2024,
Номер
14(7), С. 1005 - 1005
Опубликована: Июнь 26, 2024
This
review
focuses
on
digital
soil
organic
carbon
(SOC)
mapping
at
regional
or
national
scales
in
spatial
resolutions
up
to
1
km
using
open
data
remote
sensing
sources,
emphasizing
its
importance
achieving
United
Nations’
Sustainable
Development
Goals
(SDGs)
related
hunger,
climate
action,
and
land
conservation.
The
literature
was
performed
according
scientific
studies
indexed
the
Web
of
Science
Core
Collection
database
since
2000.
analysis
reveals
a
steady
rise
total
2000,
with
SOC
accounting
for
over
20%
these
2023,
among
which
SDGs
2
(Zero
Hunger)
13
(Climate
Action)
were
most
represented.
Notably,
countries
like
States,
China,
Germany,
Iran
lead
research.
shift
towards
machine
deep
learning
methods
has
surged
post-2010,
necessitating
environmental
covariates
topography,
climate,
spectral
data,
are
cornerstones
prediction
methods.
It
noted
that
available
primarily
restrict
resolution
km,
typically
requires
downscaling
harmonize
topography
(up
30
m)
multispectral
10–30
m).
Future
directions
include
integration
diverse
development
advanced
algorithms
leveraging
learning,
utilization
high-resolution
more
precise
mapping.
Agronomy,
Год журнала:
2024,
Номер
14(9), С. 1975 - 1975
Опубликована: Сен. 1, 2024
Due
to
current
global
population
growth,
resource
shortages,
and
climate
change,
traditional
agricultural
models
face
major
challenges.
Precision
agriculture
(PA),
as
a
way
realize
the
accurate
management
decision
support
of
production
processes
using
modern
information
technology,
is
becoming
an
effective
method
solving
these
In
particular,
combination
remote
sensing
technology
machine
learning
algorithms
brings
new
possibilities
for
PA.
However,
there
are
relatively
few
comprehensive
systematic
reviews
on
integrated
application
two
technologies.
For
this
reason,
study
conducts
literature
search
Web
Science,
Scopus,
Google
Scholar,
PubMed
databases
analyzes
in
PA
over
last
10
years.
The
found
that:
(1)
because
their
varied
characteristics,
different
types
data
exhibit
significant
differences
meeting
needs
PA,
which
hyperspectral
most
widely
used
method,
accounting
more
than
30%
results.
UAV
offers
greatest
potential,
about
24%
data,
showing
upward
trend.
(2)
Machine
displays
obvious
advantages
promoting
development
vector
algorithm
20%,
followed
by
random
forest
algorithm,
18%
methods
used.
addition,
also
discusses
main
challenges
faced
currently,
such
difficult
problems
regarding
acquisition
processing
high-quality
model
interpretation,
generalization
ability,
considers
future
trends,
intelligence
automation,
strengthening
international
cooperation
sharing,
sustainable
transformation
achievements.
summary,
can
provide
ideas
references
combined
with
promote
