Monitoring and Prediction of Land Surface Phenology Using Satellite Earth Observations—A Brief Review
Applied Sciences,
Год журнала:
2024,
Номер
14(24), С. 12020 - 12020
Опубликована: Дек. 22, 2024
Monitoring
and
predicting
land
surface
phenology
(LSP)
are
essential
for
understanding
ecosystem
dynamics,
climate
change
impacts,
forest
agricultural
productivity.
Satellite
Earth
observation
(EO)
missions
have
played
a
crucial
role
in
the
advancement
of
LSP
research,
enabling
global
continuous
monitoring
vegetation
cycles.
This
review
provides
brief
overview
key
EO
satellite
missions,
including
advanced
very-high
resolution
radiometer
(AVHRR),
moderate
imaging
spectroradiometer
(MODIS),
Landsat
program,
which
an
important
capturing
dynamics
at
various
spatial
temporal
scales.
Recent
advancements
machine
learning
techniques
further
enhanced
prediction
capabilities,
offering
promising
approaches
short-term
cropland
suitability
assessment.
Data
cubes,
organize
multidimensional
data,
provide
innovative
framework
enhancing
analyses
by
integrating
diverse
data
sources
simplifying
access
processing.
highlights
potential
satellite-based
monitoring,
models,
cube
infrastructure
advancing
research
insights
into
current
trends,
challenges,
future
directions.
Язык: Английский
Quantifying the relative importance of natural and human factors on vegetation dynamics in China’s western frontiers during 2010-2021
Environmental Research,
Год журнала:
2025,
Номер
unknown, С. 121120 - 121120
Опубликована: Фев. 1, 2025
Язык: Английский
Quantifying the contributions of climate change and human activities to grassland dynamics in southwest of China using a spatiotemporally varying residual method
International Journal of Digital Earth,
Год журнала:
2025,
Номер
18(1)
Опубликована: Апрель 21, 2025
Язык: Английский