Agricultural Economics,
Journal Year:
2025,
Volume and Issue:
unknown
Published: March 16, 2025
ABSTRACT
Agricultural
and
environmental
economists
are
in
the
fortunate
position
that
a
lot
of
what
is
happening
on
ground
observable
from
space.
Most
agricultural
production
happens
open
one
can
see
space
when
where
innovations
adopted,
crop
yields
change,
or
forests
converted
to
pastures,
name
just
few
examples.
However,
converting
remotely
sensed
images
into
measurements
particular
variable
not
trivial,
as
there
more
pitfalls
nuances
than
“meet
eye”.
Overall,
however,
research
benefits
tremendously
advances
available
satellite
data
well
complementary
tools,
such
cloud‐based
platforms,
machine
learning
algorithms,
econometric
approaches.
Our
goal
here
provide
with
an
accessible
introduction
working
data,
show‐case
applications,
discuss
solutions,
emphasize
best
practices.
This
supported
by
extensive
supporting
information,
we
describe
how
create
different
variables,
common
workflows,
discussion
required
resources
skills.
Last
but
least,
example
reproducible
codes
made
online.
Remote Sensing in Ecology and Conservation,
Journal Year:
2024,
Volume and Issue:
10(4), P. 500 - 516
Published: Feb. 25, 2024
Abstract
Peatlands
in
the
Canadian
boreal
forest
are
being
negatively
impacted
by
anthropogenic
climate
change,
effects
of
which
expected
to
worsen.
Peatland
types
and
sub‐classes
vary
their
ecohydrological
characteristics
have
different
responses
change.
Large‐scale
modelling
frameworks
such
as
Model
for
Peatlands,
Fire
Behaviour
Prediction
System
Land
Data
Assimilation
require
peatland
maps
including
information
on
sub‐types
vegetation
critical
inputs.
Additionally,
class
height
variables
wildlife
habitat
management
related
carbon
cycle
wildfire
fuel
loading.
This
research
aimed
create
a
map
(bog,
poor
fen,
rich
fen
permafrost
peat
complex)
an
inventory
using
ICESat‐2.
A
three‐stage
hierarchical
classification
framework
was
developed
within
circa
2020.
Training
validation
data
consisted
locations
derived
from
various
sources
(field
data,
aerial
photo
interpretation,
measurements
documented
literature).
combination
multispectral
L‐band
SAR
backscatter
C‐Band
interferometric
coherence,
structure
ancillary
used
model
predictors.
Ancillary
were
mask
agricultural
areas
urban
regions
account
that
may
exhibit
permafrost.
In
first
stage
classification,
wetlands,
uplands
water
classified
with
86.5%
accuracy.
second
stage,
wetland
only,
mineral
wetlands
differentiated
93.3%
third
constrained
only
areas,
bogs,
fens,
fens
complexes
71.5%
Then,
ICESat‐2
ATL08
spaceborne
lidar
describe
regional
variations
class‐wise
based
wide
sample.
introduced
comprehensive
large‐scale
sub‐class
mapping
forest,
presenting
moderate
resolution
its
kind.
Environmental Research Letters,
Journal Year:
2025,
Volume and Issue:
20(2), P. 023001 - 023001
Published: Jan. 22, 2025
Abstract
Wetlands
are
the
single
largest
natural
source
of
atmospheric
methane
(CH
4
),
contributing
approximately
30%
total
surface
CH
emissions,
and
they
have
been
identified
as
uncertainty
in
global
budget
based
on
most
recent
Global
Carbon
Project
report.
High
uncertainties
bottom–up
estimates
wetland
emissions
pose
significant
challenges
for
accurately
understanding
their
spatiotemporal
variations,
scientific
community
to
monitor
from
space.
In
fact,
there
large
disagreements
between
versus
top–down
inferred
inversion
concentrations.
To
address
these
critical
gaps,
we
review
development,
validation,
applications
well
how
used
inversions.
These
estimates,
using
(1)
empirical
biogeochemical
modeling
(e.g.
WetCHARTs:
125–208
TgCH
yr
−1
);
(2)
process-based
WETCHIMP:
190
±
39
(3)
data-driven
machine
learning
approach
UpCH4:
146
43
).
Bottom–up
subject
(∼80
Tg
ranges
different
do
not
overlap,
further
amplifying
overall
when
combining
multiple
data
products.
substantial
highlight
gaps
our
biogeochemistry
inundation
dynamics.
Major
tropical
arctic
complexes
regional
hotspots
emissions.
However,
scarcity
satellite
over
tropics
northern
high
latitudes
offer
limited
information
inversions
improve
estimates.
Recent
advances
measurements
fluxes
FLUXNET-CH
)
across
a
wide
range
ecosystems
including
bogs,
fens,
marshes,
forest
swamps
provide
an
unprecedented
opportunity
existing
We
suggest
that
continuous
long-term
at
representative
wetlands,
fidelity
mapping,
combined
with
appropriate
framework,
will
be
needed
significantly
There
is
also
pressing
unmet
need
fine-resolution
high-precision
observations
directed
wetlands.
Agricultural Economics,
Journal Year:
2025,
Volume and Issue:
unknown
Published: March 16, 2025
ABSTRACT
Agricultural
and
environmental
economists
are
in
the
fortunate
position
that
a
lot
of
what
is
happening
on
ground
observable
from
space.
Most
agricultural
production
happens
open
one
can
see
space
when
where
innovations
adopted,
crop
yields
change,
or
forests
converted
to
pastures,
name
just
few
examples.
However,
converting
remotely
sensed
images
into
measurements
particular
variable
not
trivial,
as
there
more
pitfalls
nuances
than
“meet
eye”.
Overall,
however,
research
benefits
tremendously
advances
available
satellite
data
well
complementary
tools,
such
cloud‐based
platforms,
machine
learning
algorithms,
econometric
approaches.
Our
goal
here
provide
with
an
accessible
introduction
working
data,
show‐case
applications,
discuss
solutions,
emphasize
best
practices.
This
supported
by
extensive
supporting
information,
we
describe
how
create
different
variables,
common
workflows,
discussion
required
resources
skills.
Last
but
least,
example
reproducible
codes
made
online.
