IEEE Geoscience and Remote Sensing Magazine - December 2023 - 140

RELEVANT SUMMARY TABLES (Continued)
TABLE S4. SUMMARY OF TC METHODS USED WITHIN THE STUDY.
CATEGORY
Empirical
CORRECTION METHOD
SE
CC
SCS+C
Minnaert
VECA
SM
Semiphysical
B correction
Cosine
SCS
PLC
D-S
Physical
Li method
BRATC
ot cos +
=
ot
=
ot
=
=
tt
tt
tt
EXPRESSION
tt () t
tt
ott=- ++ r
cosiS +C
Ai B
cos
iC
cos cos Sai C
iC
+
cos +
a
k
a
k
i
1F: =+ -
^
2F: =+ -
^
ot icos
=
ot
=
ot
=
=
tt tt n
n
tt ex ()(pcos cos=+i
tt
ot BiS
cosiS
tt
cos cos
i
tt XX
XX
S(
SS
S
tt
12
12
+
+
tt
(S1)
(S1)
coscos
ot io
Sv
coscos
+
+
ii
aiS
cos
() ()
) ()
W
m
tt tt n
n
W
mCsm
[S3]
[29]
[34]
[16]
[81]
[36]
[35]
SE: statistical-empirical; VECA: variable empirical coefficient algorithm; SM: slope matching; PLC: Path length correction; D-S, Dymond-Shepherd; BRATC,
BRDF-Based Atmospheric and Topographic Correction.
r
ot Ai B
t
t
cos +
ot maxminhc Wij
-X
ot maxminhc Wij
-X
[S1]
[S2]
cos cos
cos
REFERENCE
[29]
[29]
[82]
[132]
where Lp
v
is the path radiance. E ,s
E ,d E ,a and ETotal
are the solar-direct irradiance,
sky-diffuse irradiance, adjacent terrain-reflected irradiance, and total
irradiance, respectively. x is the optical thickness of the atmosphere. ,is
i ,v and
{ are the relative solar incident angle, relative sensor view angle, and relative
sensor azimuth angle, respectively. ()tdV
mittance, and S is the atmospheric spherical albedo. t{ {
t{ (, ),St{ and hh
hdVi (, V),
dSi
h
t{ { t{
dd (, ,, ),ii
SS VV
SS VV
t are the slope surface directional-directional,
hemispheric-directional, surface directional-hemispheric, and bihemispheric
reflectance, respectively.
Establishing the linear relationships between
(, ),
hd iVV
t{ and hh
dd (, ,, )
dh iSS
SS VV
(, ),
t and the flat surface directional-directional reflectance
ti {i { and then inserting them into (S1) produces a secondproducts.
Therefore, a good TC method should be both
physically sound and mathematically simple (e.g., PLC)
to facilitate its use and implementation in automated
image processing chains.
4) The remote sensing cloud computing platforms (e.g.,
GEE) and machine learning are starting to provide efficient
approaches, including for the monitoring of mountain
forests or land cover classification, which changed
the traditional mode of TC processing and analysis,
greatly improved the computing efficiency, and made
rapid time-series analysis possible.
Overall, research on this topic is increasing, with new
methods and directions. Quantifying the 426 publications
in more detail could provide greater insights (e.g., a
140
i is the atmospheric scattering transdd
(, ,, ),ii
References
[S1] G. Yongnian et al., " Variable empirical coefficient algorithm for removal of topographic
effects on remotely sensed data from rugged terrain, " in Proc. IEEE Int. Geosci.
Remote Sens. Symp., 2007, pp. 4733-4736, doi: 10.1109/IGARSS.2007.4423917.
[S2]
J. Nichol et al., " Empirical correction of low Sun angle images in steeply sloping terrain:
A slope-matching technique, " Int. J. Remote Sens., vol. 27, no. 3, pp. 629-635, 2007,
doi: 10.1080/02781070500293414.
[S3] M. Vincini et al., " An empirical topographic normalization method for forest TM data, "
in Proc. IEEE Int. Geosci. Remote Sens. Symp., 2002, vol. 4, pp. 2091-2093, doi:
10.1109/IGARSS.2002.1026454.
order equation. The solution with a positive value is the equivalent reflectance
value over a flat terrain.
literature citation map and evaluation criteria for TC studies)
than the current review in the future.
ACKNOWLEDGMENT
This work was partially supported by the National Natural
Science Foundation of China (Grants 41971282 and
42271323) and the Sichuan Science and Technology Program
(Grant 2021JDJQ0007). The corresponding author is
Gaofei Yin.
AUTHOR INFORMATION
Rui Chen (chenrui960301@my.swjtu.edu.cn)
received
his B.S. degree in surveying and mapping engineering
from the China University of Petroleum (East China),
IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE DECEMBER 2023
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