![Maps of region and study area. (a) Location of Yangsan Fault in the Korean Peninsula. (b) Digital elevation map showing Yangsan Fault System and Quaternary faults of SE Korea [13,14,52]. Blue stars mark recent medium-scale earthquakes in SE Korea [30,31]. (c) Regional geological map of SE Korea (modified from [13,14,40,41,42,43,44,52]). (d) Detailed geological map of the Byeokgye section. The study area has surface rupture recognized as fault scarps, deflected streams, and nine Quaternary fault sites (the lineaments are modified from [43,44,51,52]).](https://www.researchgate.net/publication/391507428/figure/fig1/AS:11431281437132720@1747166697337/Maps-of-region-and-study-area-a-Location-of-Yangsan-Fault-in-the-Korean-Peninsula-b_Q320.jpg)
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Published: 6 May 2025
Citation: Lim, H.; Ha, S.; Kim, S.;
Kang, H.-C.; Son, M. Influence of
Digital Elevation Model Resolution on
the Normalized Stream Length–
Gradient Index in Intraplate Regions:
A Case Study of the Yangsan Fault,
Korea. Remote Sens. 2025,17, 1638.
https://doi.org/10.3390/
rs17091638
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Article
Influence of Digital Elevation Model Resolution on the
Normalized Stream Length–Gradient Index in Intraplate
Regions: A Case Study of the Yangsan Fault, Korea
Hyunjee Lim 1, Sangmin Ha 2, Sohee Kim 1, Hee-Cheol Kang 1,3 and Moon Son 1, *
1Department of Geological Sciences, Pusan National University, Busan 46241, Republic of Korea;
lim_hyunjee@pusan.ac.kr (H.L.); sksh0328@pusan.ac.kr (S.K.); kanghc@pusan.ac.kr (H.-C.K.)
2
Department of Geography Education, Korea University, Seoul 02841, Republic of Korea; hsm9181@korea.ac.kr
3Institute of Geohazard Research, Pusan National University, Busan 46241, Republic of Korea
*Correspondence: moonson@pusan.ac.kr
Abstract: The spatial variability of input parameters plays a crucial role in the interpretation
of geomorphic indices, with digital elevation models (DEMs) being the primary data source.
However, the influence of DEM resolution on these indices has rarely been investigated.
This study investigated the influence of DEM resolution on the assessment of tectonic
activity using the normalized stream length–gradient (SLk) index, which reflects variations
along river profiles. The SLk index is sensitive to changes in river gradients that may result
from active faulting or differential uplift, making it a valuable tool for identifying zones
of active tectonic deformation. Therefore, understanding the impact of DEM resolution
on SLk analysis is critical for accurately detecting and interpreting subtle tectonic signals,
particularly in intraplate regions where deformation is slow and geomorphic expressions
are faint and discontinuous. By comparing high-resolution LiDAR-derived DEMs (L-
DEMs) and low-resolution topographic map-derived DEMs (T-DEMs), we analyzed the
SLk index distributions along the Yangsan Fault, Korean Peninsula, an intraplate setting
with Quaternary activity. According to the results, SLk anomalies derived from L-DEMs had
a continuous distribution along the fault, closely aligning with known surface ruptures and
indicating active tectonic deformation. In contrast, SLk anomalies derived from T-DEMs
were sporadic and less continuous, especially in low-relief landscapes such as alluvial fans
and floodplains, highlighting the limitations of T-DEMs in detecting fault-related features.
High-resolution DEMs were better able to capture finer-scale geomorphic features, such as
fault scarps, deflected streams, and lineaments associated with active tectonics, providing
a more comprehensive view of fault-related deformation. This discrepancy highlights
the importance of resolution choice in tectonic assessments, as low-resolution DEMs may
underestimate the tectonic activities of intraplate faults by missing subtle topographic
variations. While the choice of DEM resolution may depend on study area, scope, and
data availability, high-resolution DEMs are critical for identifying tectonic activity in
intraplate regions where geomorphic features of faulting due to slow deformation are subtle
and dispersed.
Keywords: geomorphic index; SLk index; active fault; DEM resolution; Yangsan Fault
1. Introduction
Morphometrics, a branch of geomorphology, employs geomorphic indices to quantify
the shapes and patterns of landforms and provides powerful tools for assessing tectonic
Remote Sens. 2025,17, 1638 https://doi.org/10.3390/rs17091638
Remote Sens. 2025,17, 1638 2 of 16
activity [
1
,
2
]. Geomorphic indices such as the asymmetry factor, hypsometric curve and
integral, ratio of valley floor width to height, mountain-front sinuosity, and stream length–
gradient are commonly used for rapidly and quantitatively assessing landforms and tec-
tonic activity [
2
–
9
]. In regions along plate boundaries, geomorphic indices have long been
used to assess areas with high seismic activity and records of large earthquakes, supported
by abundant geomorphic evidence of recent or ongoing tectonic activity [e.g., 10–16].
However, interpreting geomorphic features remains challenging in intraplate re-
gions, such as the Korean Peninsula, where tectonic activity is low (slip rate of less than
1 mm/yr) [
10
–
14
]. The Korean Peninsula experiences strong seasonal climate variations,
leading to high rates of weathering and denudation [
15
]. The combined effects of climate
and long-term erosion have greatly affected the present-day topography and direct obser-
vations of structural landform changes [
16
,
17
]. Additionally, related human modifications,
such as the construction of dams, tunnels, and roads, particularly since the 1960s due to
government-led industrial development, have significantly altered landforms [
18
–
20
]. This
further increases the complexity of geomorphic analysis. Despite such limitations, the
recent increase in moderate earthquakes in intraplate regions such as the Korean Peninsula
has highlighted the need for evaluating tectonic activity using geomorphic indices. Several
researchers have utilized geomorphic indices to evaluate tectonic activity in major fault
zones of the Korean Peninsula, including the Yangsan, Ulsan, Miryang (e.g., [
21
,
22
]), and
Geumwang faults (e.g., [
17
]). Due to the extensive distribution of the study areas, the
studies employed digital elevation models (DEMs) based on 1:5000 scale topographic
maps to analyze relative tectonic activity centered on the fault zones [17,21,22]. DEMs are
particularly useful tools in geomorphic index analysis, and DEM resolution may affect the
characterization of tectonic environments. However, the accuracy and interpretative power
of these indices can be influenced significantly by DEM resolution.
Although DEMs produced from aerial photographs, digital topographic maps, and
LiDAR images vary greatly in resolution, research on the impact of DEM resolution on
geomorphic indices remains scarce in low tectonic activity regions. Existing studies have
focused primarily on active tectonic environments, e.g., [
1
,
23
–
28
], leaving gaps in our
understanding of how resolution affects index calculations in slowly deforming regions.
To address the gaps above, it is necessary to evaluate how DEM resolution influences
normalized stream length-gradient (SLk) index results and the interpretation of tectonic
activity. Previous studies have demonstrated that DEM resolution influences the accu-
racy of morphometric analyses significantly, as coarse-resolution data may fail to capture
subtle terrain variations essential for tectonic and geomorphic interpretation [
29
]. Further-
more, whereas the geomorphic indices are widely utilized to infer tectonic activity, studies
addressing their limitations—such as their sensitivity to DEM resolution and potential
misinterpretation—remain limited.
This study performed a SLk analysis of the Byeokgye section [study area; [
19
,
21
]]—with
the study area located in the southern part of the northern Yangsan Fault, Korea—using
DEMs derived from LiDAR images and topographic maps. By comparing SLk index
values obtained from different DEM resolutions, this study aims to provide new insights
into the influence of resolution influences interpretations of tectonic activity in intraplate
regions with low deformation rates. Additionally, this study highlights key methodological
considerations for future research in similar settings.
2. Study Area
The Korean Peninsula experiences fewer earthquakes than neighboring countries such
as Japan, Taiwan, China, and the Philippines, which lie on a plate boundary. However,
stress may accumulate over extended periods in intraplate regions. The three recent
Remote Sens. 2025,17, 1638 3 of 16
earthquakes (Gyeongju: M
w
5.5, 12 September 2016 [
30
]; Pohang: M
w
5.4, 15 November
2017 [
31
]; and Buan: M
L
4.82, 12 June 2024 [
32
]), as well as medium-scale instrumental
and historical earthquakes, reflect the high potential for disastrous tectonic activity within
Korea [
31
,
33
–
38
]. Most seismic activity is associated with major fault lines, among which
the Yangsan Fault is one of the largest and most important [30–38].
Researchers have extensively studied the Yangsan Fault, revealing a complex history of
Cenozoic evolution and Quaternary seismic activity (Figure 1). The Yangsan Fault extends
over 200 km on land, with an N-S to NNE-strike, a several-hectometer-wide fault zone, and
a 20–35 km dextral offset. It cuts through Cretaceous sedimentary rocks and Cretaceous to
Eocene igneous rocks [
39
–
46
]. Since the Late Cretaceous, the fault has undergone multiple
deformations, with each stage corresponding to different paleo-stress regimes. The Yangsan
Fault exhibited a dextral strike-slip movement with a minor reverse component during the
Quaternary, and certain segments remain active under a current stress regime in the E-W
or ENE-WSW compression [
47
,
48
]. This study focuses on the Byeokgye section, the longest
Quaternary surface rupture on the northern Yangsan Fault (Figure 1d) [
13
,
14
]. Previous
paleoseismic investigations, including trenching and outcrop studies, indicated multiple
faulting events after the deposition of Quaternary sediments [
13
,
14
,
49
–
53
]. The active fault
in the study area has a slip rate of 0.12–0.57 mm/yr
−1
, and the most recent earthquake
occurred 3000 years ago [
13
,
14
,
53
]. In topographic mapping, fault scarps and deflected
streams formed by surface rupture have been recorded [52].
Remote Sens. 2025, 17, x FOR PEER REVIEW 3 of 18
2. Study Area
The Korean Peninsula experiences fewer earthquakes than neighboring countries such
as Japan, Taiwan, China, and the Philippines, which lie on a plate boundary. However,
stress may accumulate over extended periods in intraplate regions. The three recent earth-
quakes (Gyeongju: Mw 5.5, 12 September 2016 [30]; Pohang: Mw 5.4, 15 November 2017 [31];
and Buan: ML 4.82, 12 June 2024 [32]), as well as medium-scale instrumental and historical
earthquakes, reflect the high potential for disastrous tectonic activity within Korea [31,33–
38]. Most seismic activity is associated with major fault lines, among which the Yangsan
Fault is one of the largest and most important [30–38].
Researchers have extensively studied the Yangsan Fault, revealing a complex history
of Cenozoic evolution and Quaternary seismic activity (Figure 1). The Yangsan Fault ex-
tends over 200 km on land, with an N-S to NNE-strike, a several-hectometer-wide fault
zone, and a 20–35 km dextral oset. It cuts through Cretaceous sedimentary rocks and
Cretaceous to Eocene igneous rocks [39–46]. Since the Late Cretaceous, the fault has un-
dergone multiple deformations, with each stage corresponding to dierent paleo-stress
regimes. The Yangsan Fault exhibited a dextral strike-slip movement with a minor reverse
component during the Quaternary, and certain segments remain active under a current
stress regime in the E-W or ENE-WSW compression [47,48]. This study focuses on the
Byeokgye section, the longest Quaternary surface rupture on the northern Yangsan Fault
(Figure 1d) [13,14]. Previous paleoseismic investigations, including trenching and outcrop
studies, indicated multiple faulting events after the deposition of Quaternary sediments
[13,14,49–53]. The active fault in the study area has a slip rate of 0.12–0.57 mm/yr−1, and
the most recent earthquake occurred 3000 years ago [13,14,53]. In topographic mapping,
fault scarps and deected streams formed by surface rupture have been recorded [52].
Figure 1. Maps of region and study area. (a) Location of Yangsan Fault in the Korean Peninsula.
(b) Digital elevation map showing Yangsan Fault System and Quaternary faults of SE Korea [
13
,
14
,
52
].
Blue stars mark recent medium-scale earthquakes in SE Korea [
30
,
31
]. (c) Regional geological map of
SE Korea (modified from [
13
,
14
,
40
–
44
,
52
]). (d) Detailed geological map of the Byeokgye section. The
study area has surface rupture recognized as fault scarps, deflected streams, and nine Quaternary
fault sites (the lineaments are modified from [43,44,51,52]).
Remote Sens. 2025,17, 1638 4 of 16
3. Data and Methods
3.1. Data
We used two different DEMs for the entire study area (Figure 2, approximately 4.2
×
9.1 km).
As part of a research and development project on active faults in the Korean Peninsula, we
acquired airborne LiDAR data over the southern part of the Northern Yangsan Fault. The
CENNA 208 aircraft and Lite mapper-6800 laser pulse transceiver manufactured by IGO Co.
(Trier, Germany) were used for data acquisition. Considering the regional characteristics,
we selected the full-waveform method for its data-acquisition capability in mountainous
areas. The period of data collection for LiDAR is from 8 December 2017 to January 2018,
and the flight and system parameters are defined in Table 1. LiDAR images were captured
in an east–west direction; however, to increase the point density and acquisition rate of
ground data for a steep slope, the north–south and slope directions were taken together.
This would enable the changes in each strip to represent the rapid changes in altitude in the
study area. We designed the flight plan to cover the entire study area (69.6 km
2
). A total of
124 flight lines with a total flight distance of 875.4 km were flown over 7 days, achieving a
60% overlap. This represents a more than fourfold increase in the number of flight lines
compared to previous studies of similar areas in Korea [
52
]. The point coordinate accuracy
of the LiDAR system is shown in Table 1. A total of 1,856,096,462 laser return points were
acquired, and 317,989,564 ground points remained after processing. The average point
density was 21.28 points/m
2
(maximum: 26.53 points/m
2
, minimum: 17.23 points/m
2
),
and the average ground point density was 3.64 points/m
2
(maximum: 4.35 points/m
2
,
minimum: 3.07 points/m
2
). The vertical precision measured during the accuracy field
verification was an average of 8.2 cm, a maximum of 15.7 cm, and a minimum of 1.2 cm.
The 1:5000 topographic maps are freely available and can be downloaded from the Na-
tional Geographic Information Institute (NGII), Korea (https://www.ngii.go.kr/; accessed
6 June 2022). We corrected elevation errors in the topographic map based on the 1-arc-
second Shuttle Radar Topography Mission provided by the USGS. Consequently, two
DEMs were generated—one derived from LiDAR (L-DEM) with a 0.5 m or finer resolution
and another derived from topographic maps (T-DEM) with a 10 m resolution—for the SLk
analysis. These specific resolutions were selected based on previous studies. We adopted a
0.5 m resolution for the L-DEM, following Ha et al. [
52
] and Oh and Kim [
54
], who used
this fine resolution effectively in lineament and fault trace analysis in the study area. The
10 m resolution for T-DEM was selected based on the findings of Woo et al. [
55
], where
1:5000 topographic maps of the Korean Peninsula yielded optimal accuracy.
Table 1. Range of flight and system parameters.
Observation date
8 December 2017 (20 strips)
12 December 2017 (2 strips)
14 December 2017 (26 strips)
22 December 2017 (14 strips)
27 December 2017 (22 strips)
1 January 2018 (27 strips)
2 January 2018 (19 strips)
# stripsr (ea) 124
Flying speed (km/h) 325
Flying altitude (m) 830–1193
Scan frequency (kHz) 200
Swath width (m) 1300
Laser return points (ea) 1,856,096,462
Ground point remained (ea) 317,989,564
Point density (points/m2)17.23–26.53 (avg. 21.28)
Ground point density (points/m2)3.07–4.36 (avg. 3.64)
Vertical precision (cm) 1.2–15.7 (avg. 8.2)
Remote Sens. 2025,17, 1638 5 of 16
Remote Sens. 2025, 17, x FOR PEER REVIEW 5 of 18
Figure 2. Drainage basins for (a) DEM derived from LiDAR (L-DEM) and (b) topographic maps (T-
DEM), and the drainage basin number. Thirteen drainage basins were analyzed in the L-DEM and
twelve in the T-DEM.
Table 1. Range of ight and system parameters.
Observation date
08 December 2017 (20 strips)
12 December 2017 (2 strips)
14 December 2017 (26 strips)
22 December 2017 (14 strips)
27 December 2017 (22 strips)
01 January 2018 (27 strips)
02 January 2018 (19 strips)
# stripsr (ea)
124
Figure 2. Drainage basins for (a) DEM derived from LiDAR (L-DEM) and (b) topographic maps
(T-DEM), and the drainage basin number. Thirteen drainage basins were analyzed in the L-DEM and
twelve in the T-DEM.
3.2. Normalized Stream Length–Gradient Index
Drainage basins are less affected by weathering and denudation than other land-
forms [
15
]. Indeed, they are preferred for studying tectonic movement because they
preserve much of the original landform characteristics [
15
]. Thus, the SLk analysis focused
on drainage basins—areas drained by a stream and its tributaries along a slope. In this
instance, the stream transports water and sediment, attempting to maintain equilibrium
with various environmental factors to minimize energy loss. Once equilibrium is reached, a
concave-graded longitudinal profile with a gently decreasing slope is created [
7
,
56
]. How-
ever, external factors such as faults or lithological boundaries can generate a knickpoint or
knickzone—an area of steep terrain with a convex longitudinal profile [
2
] characteristic of
a fault scarp caused by faulting or tectonic uplift. The stream length-gradient (SL) index,
which can quantitatively express the shape of a longitudinal profile, is a valuable tool for
evaluating tectonic activity. The SL was defined by [57] as follows (Equation (1)):
SL =
dH
dL ×L(1)
where dH is the change in elevation of the stream segment, dL is the length of the segment,
and Lis the length upstream from the midpoint of the segment [
57
]. In landscape evolution,
the SL index reflects the lithologic resistance of the underlying bedrock, with lower values
Remote Sens. 2025,17, 1638 6 of 16
typically observed in less resistant units and higher values in more resistant units [
2
].
Sedimentary rocks, characterized by relatively high erodibility, are commonly associated
with lower SL values due to the development of gentler channel gradients [
2
]. In contrast,
metamorphic and igneous rocks exhibit higher SL values, reflecting their greater resistance
to erosional processes [
2
]. On particular lithologies, anomalously high SL values indicate
areas of high tectonic activity or lithological contacts [2,57–59].
The erosion rate of a stream is greatly influenced by stream power, which also plays
an important role in predicting the topographic profile, such as the SL index. Stream
power is proportional to discharge and slope. Discharge is strongly correlated with the
total channel length up to the segment L[
57
]. Consequently, this length can be utilized to
adjust the gradient of each segment and increase discharge [
2
]. Because the length of each
stream is different, the SL index of each stream can be normalized by directly comparing
SL values [27,57,59], as illustrated in Equation (2) [27]:
k=
dHt
lnLt(2)
where k is the stream gradient, dH
t
is the elevation between the headwaters and stream
mouth, and L
t
is the total stream length; k is a suitable variable for normalizing the SL index
for comparison between streams [59]. The SLk was calculated using Equation (3) [27].
SLk =
SL
k(3)
As with the anomalously high SL values, anomalously high SLk values (SLk anoma-
lies) have also been related to stream channels, as evidenced by their strong associations
with peaks in erosional dynamics [
27
,
28
,
59
]. Consequently, the SLk anomaly identifies land-
scapes with unusually high SLk values, and, as a result, active tectonic characteristics and
lithological contacts (i.e., knickpoint and knickzone). It is common practice to classify SLk
index values systematically when inferring tectonic activity. The SLk index was previously
classified using variograms [
16
,
60
], standard deviations [
27
,
61
], and geometric intervals [
62
].
We selected the geometric interval method to ensure statistical reliability concerning the ef-
fect of DEM resolution on SLk [
62
], especially given the considerable number of SLk points
analyzed for both DEMs. This classification enhances tectonic interpretation by SLk anoma-
lies in this study area. We automatically extracted the drainage network from each DEM and
calculated SLk values using ArcGIS Pro with the Spatial Analyst extension and Arc Hydro
Tools (https://www.esri.com/en-us/industries/water-resources/arc-hydro/downloads;
accessed 17 August 2022).
3.3. Fieldwork
We performed a detailed ground-truthing investigation to validate the presence of
tectonic landforms. SLk anomalies may not always indicate tectonic landforms and litho-
facies discontinuities in the field since they may be influenced by man-made structures.
To overcome the issues related to artificial landforms, it is essential to conduct fieldwork
concurrent with data analysis. Ha et al. [
14
], Ha et al. [
51
], and Oh and Kim [
54
] reported
high and low activity lineaments and surface ruptures with trenches (Figures 1c and 2). We
conducted fieldwork along the SLk anomalies identified in the results.
4. Results
The number and shape of the drainage basins varied depending on the resolution of
the DEM. A total of 39 and 33 drainage basins were generated using the L-DEM and T-DEM,
respectively. Drainage basins that were not properly formed along the study area boundary
Remote Sens. 2025,17, 1638 7 of 16
and those without surface ruptures were excluded from the analysis. The final analysis
included 13 and 12 drainage basins–main streams derived from the L-DEM (total area:
19.88 km
2
) and T-DEM (total area: 19.07 km
2
), respectively (Figure 2). For the SLk analysis,
4200 and 1140 points were generated for the L-DEM and T-DEM, respectively. The SLk
values ranged from 0.0 to 65.9 in the L-DEM and from 0.0 to 34.7 in the T-DEM (Figure 3).
Classes 2 and 3 comprised > 60% of the SLk estimates in the L-DEM, while Class 1 comprised
> 60% of the SLk estimates in the T-DEM (Figure 4). Although the SLk value distributions
showed similar patterns, the extent of differences varied depending on the DEM resolution.
Remote Sens. 2025, 17, x FOR PEER REVIEW 8 of 18
Figure 3. Distribution of normalized stream length–gradient (SLk) index derived from (a) L-DEM
and (b) T-DEM mapped onto lineaments. Numbers in circles indicate lineaments, and colors deter-
mine lineament activity: red circles indicate high activity (Red-X) and black circles indicate low ac-
tivity (Black-X).
Figure 3. Distribution of normalized stream length–gradient (SLk) index derived from (a) L-DEM and
(b) T-DEM mapped onto lineaments. Numbers in circles indicate lineaments, and colors determine
lineament activity: red circles indicate high activity (Red-X) and black circles indicate low activity
(Black-X).
Remote Sens. 2025, 17, x FOR PEER REVIEW 8 of 18
Figure 3. Distribution of normalized stream length–gradient (SLk) index derived from (a) L-DEM
and (b) T-DEM mapped onto lineaments. Numbers in circles indicate lineaments, and colors deter-
mine lineament activity: red circles indicate high activity (Red-X) and black circles indicate low ac-
tivity (Black-X).
Figure 4. Comparison of SLk index percentage derived from L-DEM and T-DEM. The proportion of
Class 4 and 5 is higher in L-DEM than in T-DEM.
Remote Sens. 2025,17, 1638 8 of 16
The distribution of the SLk index was associated with lithology in both DEMs
(Figure 5). The SLk index is a good proxy for determining the influence of lithology (espe-
cially rock resistance) that considers the varying rates of erosion between rock types [
2
,
63
].
The two DEMs clearly illustrate these characteristics in the Miocene sedimentary and
Cretaceous volcanic rocks. In the Miocene sedimentary rocks located to the east, relatively
low SLk values (Class 1 and Class 2) are observed. Miocene sedimentary rocks are poorly
consolidated compared to the older Cretaceous sedimentary formations [
64
]. The low
cementation increases erodibility, resulting in reduced channel steepness and, consequently,
lower SLk values. In contrast, the Cretaceous volcanic rocks showed relatively higher
SLk values (Class 3), which can be attributed to their greater resistance to erosion in the
study area.
Figure 5. SLk index distribution derived from (a) L-DEM and (b) T-DEM mapped onto regional
lithological features.
A previous study reported several points of high-SLk (Classes 4 and 5) anomalies [
2
].
SLk anomalies accounted for 9% of the L-DEM and 5% of the T-DEM (Figure 4). The
Remote Sens. 2025,17, 1638 9 of 16
proportion of anomalies is approximately twice as high in the L-DEM as in the T-DEM.
SLk anomalies tended to align with high-activity lineaments, including surface rupture
and their extensions, in both DEMs (Figure 3). In the L-DEM, the longest high-activity
lineament (Red-1, 7.6 km) and the branched NNE-striking high-activity lineament (Red-2,
5.5 km) exhibited strong relationships with SLk anomalies (Figure 3a). The SLk anomalies
were also evident at the northern extension of the high-activity (Red-1) and two subsidiary
high-activity lineaments (Red-3 and -4) located to the west. The SLk anomalies in the
L-DEM aligned with the NNE (Black-1, -2, and -3) or the NW-striking (Black-4) low-activity
lineaments. The SLk indexes in the T-DEM showed similar anomalies to those in the L-DEM
only in the southern section of the main (Red-1) and northern section of the NNE-striking
branched high-activity lineaments (Red-2) (Figure 3b). However, SLk anomalies and low-
activity lineaments only showed strong relationships along the NNE-striking (Black-2,
central part) and the NW-striking lineaments (Black-4, southeastern part).
The SLk index represents the detailed topographic variations of fault-related landforms
(e.g., fault scarps, deflected streams) and effectively captures man-made features such as
levees, roads, farm paths, and irrigation [
54
]. We excluded locations with continuous Class
5 values—specifically LD-07 and TD-07, LD-08 and TD-08, LD-11 and LD-10, and LD-13
and TD-12—which correspond to large man-made reservoirs. The field surveys identified
SLk anomalies, including knickpoints associated with tectonic activity (Figure 6). For
instance, artificial embankments occur frequently in the low-relief landform of the study
area, along with significant human activity (Figure 6c,d). However, bedrock is exposed at
the base of these artificial embankments, and differences in the relative elevation of the
riverbed were identified using the exposed bedrock surface as a reference. The widespread
presence of artificial concrete embankments within the low-relief landforms was likely
part of an effort to prevent slope failure caused by natural processes, specifically tectonic
landforms (Figure 6c,d). Aerial investigation of the SLk anomaly derived from the L-DEM
in low-relief landforms through drone photography revealed a correspondence with the
surface ruptures. Notably, in the northern area, SLk anomalies derived from both DEMs
occurred along the NNE-striking branched surface rupture (Red-2) within 10 m of a trench
reported by [
14
,
52
] (Figure 6b). In the central area, the SLk anomaly derived from the
L-DEM was also either located directly on a surface rupture or within 2.0 m of fault scarps,
in close proximity to trench and outcrop locations documented by [14,52] (Figure 6e).
Remote Sens. 2025,17, 1638 10 of 16
Remote Sens. 2025, 17, x FOR PEER REVIEW 11 of 18
Figure 6. Fault-induced knickpoint outcrops detected by SLk analysis. (a) LiDAR hillshade map
with location of outcrops (modied from [14,52]). (b) Drone image of 2.1 m high knickpoint with
surface rupture and trench. (c) Photograph of 2.3 m knickpoint observed with articial embankment
for preventing collapse. (d) Image of knickpoint with a maximum height of 2.0 m. (e) Drone photo
of area corresponding to the 3.0 m knickpoint and 2.0 m fault scarp with fault rupture and trench.
5. Discussion
The resolution of the DEM inuenced the geometry of the drainage basin and stream
network delineation, particularly in low-relief and human-modied areas where subtle
topographic variations play a key role in hydrological partitioning (Figure 2), consistent
with previous ndings [65,66]. The shapes and numbers of drainage basins in the southern
Figure 6. Fault-induced knickpoint outcrops detected by SLk analysis. (a) LiDAR hillshade map
with location of outcrops (modified from [
14
,
52
]). (b) Drone image of 2.1 m high knickpoint with
surface rupture and trench. (c) Photograph of 2.3 m knickpoint observed with artificial embankment
for preventing collapse. (d) Image of knickpoint with a maximum height of 2.0 m. (e) Drone photo of
area corresponding to the 3.0 m knickpoint and 2.0 m fault scarp with fault rupture and trench.
5. Discussion
The resolution of the DEM influenced the geometry of the drainage basin and stream
network delineation, particularly in low-relief and human-modified areas where subtle to-
pographic variations play a key role in hydrological partitioning (Figure 2), consistent with
previous findings [
65
,
66
]. The shapes and numbers of drainage basins in the southern re-
gion were consistent regardless of DEM resolution, while notable differences were observed
in the northern and central regions. Specifically, while the drainage basin boundaries in the
eastern mountainous area demonstrated minimal variation, the floodplains and alluvial
fans in the western area differed depending on DEM resolution (Figure 2). The drainage
basins are more linear in the L-DEM than those in the T-DEM. This suggests that, in the
eastern and southern high-elevation mountainous areas, the impact of DEM resolution is
Remote Sens. 2025,17, 1638 11 of 16
minimal, while resolution is more important in the low-relief landforms of the western
and northern areas (Figures 2and 7). The floodplains and alluvial fans in the low-relief
landform have been altered with urbanization and agricultural development, including
road and bridge construction, sewerage treatment, river straightening, and agricultural
land expansion. Our findings suggest that the L-DEM effectively reflects these landforms,
whereas the T-DEM does not, which was directly associated with the impact of DEM
resolution based on landform, human disturbance, and elevation.
Remote Sens. 2025, 17, x FOR PEER REVIEW 12 of 18
region were consistent regardless of DEM resolution, while notable dierences were ob-
served in the northern and central regions. Specically, while the drainage basin bound-
aries in the eastern mountainous area demonstrated minimal variation, the oodplains
and alluvial fans in the western area diered depending on DEM resolution (Figure 2).
The drainage basins are more linear in the L-DEM than those in the T-DEM. This suggests
that, in the eastern and southern high-elevation mountainous areas, the impact of DEM
resolution is minimal, while resolution is more important in the low-relief landforms of
the western and northern areas (Figures 2 and 7). The oodplains and alluvial fans in the
low-relief landform have been altered with urbanization and agricultural development,
including road and bridge construction, sewerage treatment, river straightening, and ag-
ricultural land expansion. Our ndings suggest that the L-DEM eectively reects these
landforms, whereas the T-DEM does not, which was directly associated with the impact
of DEM resolution based on landform, human disturbance, and elevation.
Figure 7. River proles (blue line) and their associated SLk values (black line). The lineaments that
the rivers cross are given (see Figures 3 and 5 for descriptions of the lineaments), and lithologies
that the rivers cross are given (see Figure 5 for descriptions of the lithologies). Dashed colored lines
mark boundaries between SLk class divisions.
SLk values are strongly associated with lithology, regardless of DEM resolution,
likely due to the increased exposure of bedrock at higher elevations (Figures 5 and 7). In
areas of hard rock substratum, the consistent SLk distribution paerns across DEM reso-
lutions may be the result of varying structural landforms shaped by long-term dierential
weathering and erosion of minerals with various levels of resistance and the activity of
fault zones in the bedrock. However, in the southernmost basins of the study area, where
complex lithology and lineaments dominate (LD-13 in Figure 5a and TD-12 in Figure 5b),
distinguishing SLk values based on lithological variations became particularly dicult.
This may be associated with the longest ow being parallel to low-activity lineaments
(Black-5 and Black-6, Figure 3), which likely have a greater inuence than lithology.
Figure 7. River profiles (blue line) and their associated SLk values (black line). The lineaments that
the rivers cross are given (see Figures 3and 5for descriptions of the lineaments), and lithologies that
the rivers cross are given (see Figure 5for descriptions of the lithologies). Dashed colored lines mark
boundaries between SLk class divisions.
SLk values are strongly associated with lithology, regardless of DEM resolution, likely
due to the increased exposure of bedrock at higher elevations (Figures 5and 7). In areas of
hard rock substratum, the consistent SLk distribution patterns across DEM resolutions may
be the result of varying structural landforms shaped by long-term differential weathering
and erosion of minerals with various levels of resistance and the activity of fault zones
in the bedrock. However, in the southernmost basins of the study area, where complex
lithology and lineaments dominate (LD-13 in Figure 5a and TD-12 in Figure 5b), distin-
guishing SLk values based on lithological variations became particularly difficult. This
may be associated with the longest flow being parallel to low-activity lineaments (Black-5
and Black-6, Figure 3), which likely have a greater influence than lithology. Collectively,
our observations indicated that tectonic activity had a greater influence on the spatial
distribution of SLk values than lithological factors, even in low-activity regions.
The SLk anomalies, previously documented in association with surface ruptures,
outcrops, and trenches [
14
,
51
,
52
], are detected only in the L-DEM in the northern to central
regions (Figure 3, Figure 6c,e, and Figure 8a,b,d,e). Anomalies are also detected in the
south for both L-DEM and T-DEM (Figure 3, Figure 6b, and Figure 8c,f). In conclusion,
the areas of high tectonic activity derived from the T-DEM are confined to the northern
Remote Sens. 2025,17, 1638 12 of 16
area of the branched surface rupture and the southern area. In contrast, the recent tectonic
activity is evident in the presence of SLk anomalies derived from the L-DEM, which align
with high- and low-activity lineaments, including surface ruptures (Figure 3, Figure 7,
and Figure 8). These SLk anomalies suggested relatively high tectonic activity and are
distributed continuously from the northern to the southern parts of the study area.
Remote Sens. 2025, 17, x FOR PEER REVIEW 13 of 18
Collectively, our observations indicated that tectonic activity had a greater inuence on
the spatial distribution of SLk values than lithological factors, even in low-activity regions.
The SLk anomalies, previously documented in association with surface ruptures, out-
crops, and trenches [14,51,52], are detected only in the L-DEM in the northern to central
regions (Figures 3, 6c,e, and 8a,b,d,e). Anomalies are also detected in the south for both L-
DEM and T-DEM (Figures 3, 6b, and 8c,f). In conclusion, the areas of high tectonic activity
derived from the T-DEM are conned to the northern area of the branched surface rupture
and the southern area. In contrast, the recent tectonic activity is evident in the presence of
SLk anomalies derived from the L-DEM, which align with high- and low-activity linea-
ments, including surface ruptures (Figures 3, 7, and 8). These SLk anomalies suggested
relatively high tectonic activity and are distributed continuously from the northern to the
southern parts of the study area.
Figure 8. SLk anomalies in the (a,d) northern, (b,e) central, and (c,f) southern parts of the study area,
analyzed from the L-DEM and T-DEM. The blue dashed circle indicates the SLk anomaly that
matches the lineaments.
Figure 8. SLk anomalies in the (a,d) northern, (b,e) central, and (c,f) southern parts of the study
area, analyzed from the L-DEM and T-DEM. The blue dashed circle indicates the SLk anomaly that
matches the lineaments.
The L-DEM results are consistent with those of previous studies [
14
,
52
,
53
], which
documented continuous surface ruptures extending from the northern to southern parts
of the study area during the Quaternary. Paleoseismic evidence reported by [
14
] further
supports this interpretation; their trench investigations at five sites identified at least six
surface-faulting events, with the most recent event occurring approximately 3000 years
ago, as determined from stratigraphic relationships and calibrated radiocarbon ages. These
findings highlight the utility of high-resolution DEMs in capturing subtle geomorphic
expressions of tectonic deformation, especially in low-activity intraplate regions.
The higher classes of SLk values are better represented by the L-DEM than by the
T-DEM (Figure 3, Figure 4, Figure 7, and Figure 8), reflecting the good accuracy of elevation
and slope information for high-resolution DEMs, whereas coarser-resolution DEMs tend
Remote Sens. 2025,17, 1638 13 of 16
to underestimate critical steep points [
67
]. Class 1 is particularly prominent in the flood-
plain and alluvial fan of the study area when using the T-DEM (Figure 3b, Figure 7, and
Figure 8d,e). This reflects the high variation in the elevation change of the stream segment
(dH) according to the segment length (dL) at adjacent points in the L-DEM, whereas dH
is either 0 or almost absent between adjacent points in the T-DEM. Therefore, the L-DEM
is more sensitive to detecting elevation changes within the microtopography, capturing
details such as riverbeds, compared to the T-DEM. Future studies should consider the fact
that low-resolution DEMs tend to underestimate geomorphic indices and tectonic activity.
Troiani and Della Seta [
68
] indicated that low-resolution DEMs are highly suitable
for assessing tectonic activity across large areas. This is because high-resolution DEMs
generate finer stream segmentation, which, in turn, increases the sensitivity of the SLk
index to irregularities. However, the study by [
68
] focused on the Marche Apennines, Italy,
an interplate region with significantly higher tectonic activity and a much broader area
than the Korean Peninsula. Pedrera et al. [
16
] demonstrated that, despite very low tectonic
activity, active folding was identified in the eastern Baetic Cordillera of Spain using the SLk
index with a 10 m DEM resolution. However, the SLk index is only effective in locating
active folding in regions with hard rock substratum, whereas areas with soft sediments
(Neogene–Quaternary deposits) did not yield comparable results. These cases and this
study’s results suggest that, in intraplate settings where surface ruptures are weak and
low-relief landscapes are widespread, high-resolution DEMs are better suited for accurately
capturing topographic features in geomorphic analysis.
6. Conclusions
This study evaluated the influence of DEM resolution on tectonic activity assessment
using the SLk index by comparing high-resolution LiDAR-derived DEM (L-DEM) and
low-resolution topographic map-derived DEM (T-DEM) for the Yangsan Fault, Korea.
The SLk anomalies in the L-DEM, indicating high tectonic activity, extend continuously
from the northern to the southern parts of the study area. This is consistent with the
findings of previous studies documenting persistent surface ruptures along the Yangsan
Fault throughout the Quaternary across the study area. In contrast, the T-DEM analysis
revealed that the SLk anomalies are predominantly concentrated in the northern segmented
surface ruptures and limited areas in the south. This suggests that the lower resolution of
the T-DEM is unable to capture subtle topographic variations in the southern part of the
study area. In regions characterized by low-relief landscapes, such as the floodplains and
alluvial fans, the high-resolution DEM more accurately reflects landscape characteristics,
emphasizing its importance in geomorphic and tectonic studies.
The necessity of high-resolution DEMs for assessing tectonic activity depends on
various factors, including study objectives, spatial extent, and data availability. Our findings
demonstrate that high-resolution DEMs enable more detailed analyses, particularly in
intraplate regions where surface ruptures and landform variations are subtle. This is
especially critical in intraplate settings such as the Korean Peninsula, where the slip rate is
less than 1 mm/yr, as the low deformation rates and subtle geomorphic expressions require
high-resolution topographic data for precise tectonic analysis. In such a context, the use of
low-resolution DEMs may lead to underestimation of tectonic activity, potentially affecting
geomorphic interpretations in intraplate regions. Therefore, careful consideration of DEM
resolution is essential when using geomorphic indices for tectonic studies, as it directly
influences the accuracy and reliability of tectonic activity assessments. These findings
contribute to a better understanding of the implications of DEM resolution in tectonic
geomorphology and provide a basis for selecting appropriate datasets in future studies.
Remote Sens. 2025,17, 1638 14 of 16
Author Contributions: Conceptualization, H.L., S.H., S.K., H.-C.K. and M.S.; methodology, H.L.
and S.K.; software, H.L; investigation, H.L., S.H. and H.-C.K.; data curation, H.L.; writing—original
draft preparation, H.L.; writing—review and editing, S.H. and M.S.; visualization, H.L.; supervision,
M.S.; project administration, M.S.; funding acquisition, M.S. All authors have read and agreed to the
published version of the manuscript.
Funding: This research was supported by a grant (2022-MOIS62-001(RS-2022-ND640011)) from the
National Disaster Risk Analysis and Management Technology in Earthquake, funded by the Ministry
of the Interior and Safety (MOIS, Republic of Korea).
Data Availability Statement: The original contributions presented in this study are included in the
article. The DEM and shapefiles used for topographic analysis are available from the corresponding
author upon reasonable request. Interested researchers may contact the corresponding author to
discuss access and usage terms.
Conflicts of Interest: The authors declare no conflicts of interest.
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