pISSN 1226-4806 eISSN 1598-7477
Vol. 20, No. 6, p. 877 889, December 2016
ⓒThe Association of Korean Geoscience Societies and Springer 2016
Earthquake activities in the Philippines Islands and the adjacent areas
ABSTRACT: This study focused on the seismic activities in the Phil-
ippines Islands and the adjacent areas where the inter- and intra-plate
seismic sources are prevalent. To access this, the frequency-magnitude
distribution model was employed with the completeness seismicity
data. Then, the possible maximum magnitude, return period and
probability of earthquake occurrence, including the prospective areas
of upcoming earthquakes, were evaluated. The results indicated that
eastern Taiwan is among the most seismic-prone areas. The most prob-
able largest magnitude of earthquakes was estimated to be up to
8.0 Mw in a time period of 50 years, giving return periods of <1, 2–4,
5–20 and 20–40 years for earthquakes with a Mw of 5.0, 6.0, 7.0 and
8.0, respectively. Meanwhile, in the areas of Davao and eastern Manado,
where the group of Halmahera, Philippines and Sangihe Double
Subduction Zones are delineated (HSZ, PSZ and SSZ, respectively),
maximum earthquakes of 6.8–7.1 Mw are possible in a 5–10 year
period. For the northern Minahassa and eastern Sulu Trenches (MST
and SLT), which were defined as medium hazard areas, the return
periods were calculated at ~100–200 years for an earthquake magni-
tude of 7.0–8.0 Mw. According to the limits of the recorded earthquake
events, the Palawan, Sulu Archipelago and Sulu Trenches (PWT,
SAT and SLT, respectively) are classified as aseismic source zones.
For earthquake forecasting, six locations along the Manila Trench
(MLT), HSZ, PSZ and SAT are proposed as the areas that have a high
probability of generating a major earthquake in the near future.
Geographically, the most prospective areas are located near major
cities, such as Taipei, Manila, Davao and Manado. Thus, there is a
compelling need to develop effective mitigation strategies for both
tsunami and earthquake hazards.
Key words: seismicity, frequency-magnitude distribution, return period,
According to the Eurasian-Philippines Sea plate collisions,
the Philippines Islands and the adjacent areas are tectonically
complex. The relative plate motions range from 5–40 mm/
year (Galgana et al., 2007). In the northern part the Eurasian
plate subducts steeply eastward underneath the Philippines
Sea plate, whilst in the southern part the Philippines Sea plate
subducts underneath the Eurasian plate with a shallow west-
dipping. As a result, several micro-plates are squeezed between
these Eurasian-Philippines Sea plate boundaries that are
occupied by two major seismotectonic regimes, i.e., crustal
faults and subduction zones. The faults are mostly located
inland of the Philippines Islands, while nine major zones of
plate subduction lie along the offshore regions surrounding
the Philippines Islands and consist of the (1) East Luzon Trench
(ELT), (2) Halmahera Subduction Zone (HSZ), (3) Manila
Trench (MLT), (4) Minahassa Trench (MST), (5) Palawan
Trench (PWT), (6) Philippines Subduction Zone (PSZ), (7)
Sangihe Double Subduction Zone (SSZ), (8) Sulu Archipelago
Trench (SAT) and (9) Sulu Trench (SLT) (Fig. 1).
Due to the present-day activities of the above seismotectonic
regimes, the Philippines Islands and neighborhood countries
are frequently affected by earthquakes, tsunamis and volcanoes.
At least 65 volcanoes placed in the vicinity of the Philippines
Islands are defined as scientifically as active or potentially
active (Fig. 1). About 95 earthquake events with a moment
magnitude (Mw) > 7.0 were recorded over the recent 54-year
period of 1960–2014. In addition, since 1509 around 280
locations of tsunami run-up, caused mostly by earthquakes,
were reported by the National Oceanic and Atmospheric
Administration (NOAA). Thus, the Philippines Islands is one
of the most natural hazard-prone areas and so the present-day
situation needs to be clarified, in particular for the seismic and
Based on a literature review, Liu et al. (2007) defined the
tsunamigenic earthquake sources in the South China Sea
that might impact upon the coast lines of Taiwan and Hong
Kong. Beroya and Aydin (2008) analyzed the local seismic
hazard in the northern part of the Philippines, but recognized
only some earthquake sources and the active faults. In addition,
Ha et al. (2009) and Ruangrassamee and Saelem (2009)
determined the worst-case scenarios for tsunami hazards in
the South China Sea, including the Gulf of Thailand. By
assuming a maximum credible earthquake of Mw-9.0 gen-
erated at the MLT (no. 3), the most severe tsunami hazards were
located at the Philippines, Vietnam and the southern coast
of China. Meanwhile, for the Gulf of Thailand, the tsunami
travel time was estimated to be ~13 h with a maximum wave
height of ~0.65 m (Ruangrassamee and Saelem, 2009).
As noted above, most of the previous works have focused
only on some seismotectonic regimes and with the worst-case
scenarios usually being assumed. From these results, seismic-
and tsunamigenic-resistant designs or constructions require
a high budget. Probabilistic approaches would, therefore, be
useful in providing an alternative understanding of the risk
probability and so formed the main aim of this study. Using
Morphology of Earth Surface and Advanced Geohazards in Southeast Asia Research Unit (MESA RU),
Department of Geology, Faculty of Science, Chulalongkorn University, Bangkok 10330, Thailand
*Corresponding author: Pailoplee.S@gmail.com
878 Santi Pailoplee and Natchana Boonchaluay
the instrumental earthquake data (i.e., the earthquake catalogue),
the various parameters that imply the probabilistic seismic
activities were investigated. The outcomes are useful for allowing
a compromise between effective mitigation plans and the
required budget for not only the seismic hazard in the Philippines
Islands but also the tsunami hazard in the coastal communities
surrounding the South China Sea and the Gulf of Thailand.
Since 1965, the World-Wide Standard Seismograph Net-
work (WWSSN) has constructed several seismic stations in
order to observe globally the earthquake occurrences. As a
result there are at present at least three catalogues of instru-
mentally recorded earthquake events in the area of this study
Fig. 1. (a) Map of the Philippines Islands and the adjacent areas showing the nine subduction zones (thick grey lines with numbers in
adjacent circles) and the intraplate active faults (thin red lines). The green, purple and blue squares indicate the locations of tsunami
affected areas, volcanoes and major earthquakes, respectively. Yellow circles represent the epicentral distribution of the completeness
main shocks with Mw 4.2 recorded during 1980–2011. In the legend; T = trench, SZ = subduction zone.
Earthquake in Philippines 879
(latitude 4.2°S–26.1°N and longitude 110.0°E–132.2°E) (Fig. 1).
These are i) the International Seismological Centre, ii) the
US National Earthquake Information Center, and iii) the Global
Centroid Moment Tensor catalogues. However, within the
individual catalogues, three different scales of magnitude are
stated for different earthquake events; namely the Mw
wave magnitude (mb) and surface-wave magnitude (Ms).
Practically, each scale is derived by specific analytical pro-
cedures with different implied values and meanings. In order
to homogenize the catalogues used here, both the mb and Ms
scales were converted to Mw using the empirical relationships
contributed from the Global Centroid Moment Tensor data
of the study area.
Empirically, any earthquake catalogue is the result of spatially
and temporally heterogeneous networks of seismometers,
and processed using a variety of software, assumptions and
also judgments (Habermann, 1987; Zuniga and Wiemer, 1999).
The earthquake catalogues contributed by these different net-
works, therefore, have both advantages and disadvantages
themselves in terms of the continuity, recording time span and
limit of the recordable magnitude range. In statistical seismol-
ogy, a longer earthquake recording time span and a wider
detectable magnitude range lead to a greater accuracy in the
statistical seismicity analysis. Therefore, all three catalogues,
after being standardized to Mw
, were merged in order to extend
the recordable magnitude range as much as possible, as well
as the recording time span and numbers of earthquake events.
The identical earthquakes were then deleted according to
the assumption proposed by Suckale and Grünthal (2009).
This new composite catalogue contained 505,262 earthquakes
over a recorded range of 1.0–9.2 Mw for the period 1960–
To eliminate foreshocks and aftershocks, which do not
exactly represent the seismotectonic activities, the decluster-
ing assumption of Gardner and Knopoff (1974) was applied
following the previous seismicity investigations of So et al.
(2012) and Wen et al. (2012). Consequently, the declustering
process distinguished 12,717 clusters of earthquakes, from
which a total of 479,527 events (95%) were identified as
foreshocks or aftershocks and so were excluded from the cat-
alogue. As a result, 25,735 main shocks, expressing directly
the seismotectonic activities, were identified.
Besides homogenizing and declustering, almost all of the
earthquake catalogues are empirically contaminated by man-
made activities that bias the earthquake report and seismic
rate change, i.e., detection changes, reporting changes, and
magnitude shifts (Wyss, 1991; Zuniga and Wiemer, 1999).
Like most previous research works, the GENAS algorithm
(Habermann, 1983; 1987) was used for checking for man-made
changes and selecting the earthquake data suitable for quan-
titative investigation. According to the GENAS algorithm,
the main shocks in this dataset with a Mw4.2 recorded during
1980–2011 showed a constant cumulative rate and so imply
that human errors are not of significant concern (Fig. 2a). Thus,
the 1980–2011 part of earthquake catalogue was identified
as the completeness earthquake catalogue that can be used
reliably for earthquake activity investigation. In this study,
the focal depth of all events was limited to 0–60 km so as
to recognize only the intraplate (crustal fault) and interplate
(subduction zone) earthquake activities, which are the major
cause of seismic or tsunamigenic devastation.
3. EARTHQUAKE ACTIVITIES
According to Ishimoto and Iida (1939) and Gutenberg and
Richter (1944), the frequency and magnitude of earthquakes
is related empirically in the so called frequency-magnitude
distribution (FMD), as expressed in Equation (1);
log(N)=abM or ln(N)=ln
where N is the average number of earthquakes per year
having a magnitude M, a and b are coefficients that vary
depending directly on the time and space of the earthquake
data, and and are closely related to the a- and b-values
by Equations (2a) and (2b), respectively;
and . (2b)
From Equation (1), the FMD was derived using the bulk
completeness data obtained in section 2. Figure 2b illustrates
the FMD plot constrained by the straight linear regression fit
of the earthquake data. Based mainly on the entire-magnitude-
range method proposed by Woessner and Wiemer (2005),
the a- and b-values of the bulk earthquake data were estimated
to be 5.59 and 0.73, respectively. Moreover, the earthquake
recording capability of the existing seismic network was limited
at Mw 4.8 indicating the determined magnitude of com-
pleteness (Mc) (Woessner and Wiemer, 2005).
For detailed investigation, the FMD, including the a- and
b-values, were evaluated spatially according to Pailoplee et al.
(2013). At first in any individual specific area, the spatial
distribution of the radius extended for acquiring 30 earthquake
events were investigated throughout the study areas. This
revealed that an average radius of 110 km (about 1°) is capable
of obtaining at least 30 earthquake events, which is a suitable
level for statistical investigation of the FMD (Wiemer, 2001).
Therefore, in order to avoid double use of the earthquake data,
the area surrounding the earthquake sources mentioned in
section 1 was gridded with a 1° × 1° spacing. Empirically, for
each individual grid node, any earthquake within a fixed 110-
km radius was then selected and contributed to the FMD.
In order to estimate the constant a- and b-values of the FMD,
a number of statistical formulas were proposed previously,
e.g., Aki, 1965; Utsu, 1965, 1966; Shi and Bolt, 1982; Bender,
1983; Tinti and Mulargia, 1987. However according to the
exp aln 10=
880 Santi Pailoplee and Natchana Boonchaluay
unavoidable use of binned magnitudes, and by the measure-
ment errors on the magnitude, Marzocchi and Sandri (2003)
revealed that the most commonly used fomular of Aki (1965)
produce a strong bias of b-value and its uncertainty estimation.
Meanwhile for the other formulars in particularly for Bender
(1983), the biases of b-value estimation was reduced drastically
(Marzocchi and Sandri, 2003). The models of Bender (1983)
implemented in the ZMAP program (Wiemer, 2001) was,
therefore, applied in this study to estimate the b value and its
uncertainty. The obtained values were then contoured and
mapped along the recognized seismogenic source, as shown
in Figure 3. Some specific areas were expanded to show
additional details of the FMD plot, as illustrated in Figure 4.
However, due to the insufficiency of the earthquake data, the
FMD in the vicinity of the PWT, SAT and the southern part
of SLT (nos. 5, 8 and 9) were not available.
Based on Figure 3a, three prominent areas with compar-
atively high a-values were found, being at the (i) eastern Manila,
(ii) northern Davao, where the crustal faults are dominated
inland of the Philippines Islands, and (iii) region in the vicinity
of Manado where the MST and SSZ (nos. 4 and 7) are occu-
pied. Meanwhile, the area surrounding the northern segment
of SAT (no. 8) revealed low a-values of 1.0–2.0 (Fig. 3a).
The distribution of b-values (Fig. 3b) conformed mostly to
the distribution of the a-values, in that areas that showed a
comparatively low or high a-value also illustrated a corresponding
low or high b-value.
Regarding the accuracy, most of the study area, in particular
along the subducting belt, shows a standard deviation (SD)
of the FMD regression of less than 0.2 (Fig. 3c), implying a
low variation in the obtained a- and b-value maps. The obtained
FMD of most of the area had a >80% goodness of fit indicating
a reliable FMD (Fig. 3d). However, there are some areas along
the MST and eastern rims of the SLT (nos. 4 and 9) that have
a SD of more than 0.2, where any interpretation and discussion
is, therefore, tentative.
In a seismological context, the a-value is taken to imply the
entire seismicity rate of any space and time. Regarding only
the a-values, the inland crustal faults and offshore MST and
SSZ (nos. 4 and 7) then had released earthquakes with a bulk
seismicity rate higher than the other regions (Fig. 3a). However,
the b-value seismologically is the ratio of small-to-large sized
earthquakes. The higher the b-value, the less possible it is to
generate a large event. Accordingly, the areas conforming to
high a- and b-values are not likely then to act as high hazard
regions, whereas areas with low a- and b-values are capable
of generating large earthquakes with a few numbers of events.
Thus, the earthquake activities in individual areas were eval-
uated further by deriving and then weighting between the a-
and b-values, as detailed next in section 3.1.
3.1. Possible Maximum Magnitude
According to Yadav et al. (2011), the maximum earthquake
capable of being generated in the next t years can be evaluated
from both the α- and β-values via Equation (3);
Therefore, the a- and b-value maps obtained in section 3
Fig. 2. (a) Cumulative number of the completeness earthquakes after declustering and eliminating man-made changes. Black circles indi-
cate earthquakes with Mw 7.0. (b) FMD plot of the completeness earthquake data, i.e., Mw 4.2 recorded during 1980–2011. Triangles are
the earthquake number in each magnitude whereas squares represent the cumulative number of earthquakes with an Mw equal to or larger than
each magnitude. Solid line is the linear regression after evaluating the Mc following the assumption of Woessner and Wiemer (2005).
Earthquake in Philippines 881
Fig. 3. Maps of the Philippines Islands and the adjacent areas showing the (a) a-value, (b) b-value, (c) standard deviation of each obtained
b-value, and (d) the goodness fit of the FMD. The circles indicate the 110-km radius from four specific areas (a–d) where the FMD plots
are demonstrated in Figure 4.
882 Santi Pailoplee and Natchana Boonchaluay
(Figs. 3a and b) were converted spatially to their corresponding
α- and β-values following Equations (2a) and (2b), respec-
tively. Thereafter, the possible maximum magnitude that might
occur in the next 5, 10, 30 and 50 years was evaluated and
mapped (Fig. 5).
Based on Figure 5, the highest seismic activities were found
at the offshore region of the eastern part of Taiwan. Tectoni-
cally, this seismic-prone area can generate an earthquake
with a maximum magnitude of 6.8, 7.4, 7.7 and up to 8.0 Mw
in the next 5, 10, 30 and 50 year-periods, respectively. In addi-
tion, the areas in the vicinity of Davao and Manado, i.e.,
HSZ, PSZ and SSZ (nos. 2, 6 and 7), were also found to be
prominent hazardous seismic source zones and could generate
a potential earthquake with Mw 6.8–7.1 in the next 5–10
years (Figs. 5a and b). Meanwhile, the crustal faults located
mostly inland of the Philippines Islands were defined as inter-
mediate hazard levels compared to the other subduction zones.
Based on this study, the Philippines Islands have a possibility
to experience shallow crustal earthquakes with a potential
maximum magnitude of 5.6–7.4 Mw over a 5–50 year time
period (Fig. 5). Within the limits of the recorded earthquake
events, the PWT, SAT and SLT (nos. 5, 8 and 9) areas were
classified as aseismic source zones, where the likely earth-
quake activity is not prominent (Fig. 5).
3.2. Return Period of Earthquakes
In addition to the possible maximum magnitude, Yadav et
al. (2011) expressed the return period of earthquakes based
on the α and β parameters, where the return period (TM) of
an earthquake with magnitude M can be analyzed according
to Equation (4),
Variations in the return period of earthquakes with a mag-
Fig. 4. The demonstrated FMD plots
of the four specific sites shown in
Earthquake in Philippines 883
Fig. 5. Map of the Philippines Islands and the adjacent areas showing the maximum earthquake magnitude likely to be generated in each
area in the next (a) 5, (b) 10, (c) 30 and (d) 50 years, respectively.
884 Santi Pailoplee and Natchana Boonchaluay
Fig. 6. Map of the Philippines Islands and the adjacent areas showing the estimated recurrence interval of earthquakes with an individual
Mw of (a) 5.0, (b) 6.0, (c) 7.0 and (d) 8.0.
Earthquake in Philippines 885
Fig. 7. Map of the Philippines Islands and the adjacent areas showing the spatial distribution of the probabilities of an earthquake with
a magnitude of (a) 5.0, (b) 6.0, (c) 7.0 and (d) 8.0 Mw that could be generated in the next 50 years.
886 Santi Pailoplee and Natchana Boonchaluay
nitude of 5.0–8.0 Mw (Fig. 6) revealed that the calculated
return periods normally conformed to the possible maximum
magnitude described in section 3.1. For an individual mag-
nitude of interest, the offshore region of the eastern part of
Taiwan and the eastern part of PSZ (no. 6), including the area
surrounding HSZ and SSZ (nos. 2 and 7), revealed shorter
return periods compared to the other regions. For example,
return periods of <1, 2–4, 5–20, and 20–40 years were esti-
mated for earthquakes with a Mw 5.0–8.0 in these areas, whilst
in the northern MST (no. 4) and eastern SLT (no. 9) areas, lon-
ger return periods were found with an average recurrence
interval for earthquakes with a magnitude of 7.0–8.0 Mw of
~100–200 years (Figs. 6c and d).
3.3. Probability of Earthquake Occurrence
For the probabilistic point of view, Yadav et al. (2011) also
proposed the probabilities of earthquake occurrences, Pt (M),
for any time span of interest (t) and recognized earthquake
magnitude (M). The relationship between the FMD param-
eters (i.e., α and β) and the Pt (M) is shown in Equation (5).
The probabilities (%) of a Mw 5.0–8.0 earthquake occurring
in the next 50 years are shown in Figure 7. For a Mw 5.0–6.0
earthquake (Figs. 7a and b), the probability of occurence
increases with time to almost 100% over the next 50 years for
the whole region of the subducting belt, whereas at Mw 7.0–8.0
the probabilities vary site by site. For a Mw 7.0 earthquake, most
seismic source zones showed a probability of occurrence of
~70–90% (Fig. 7c), whilst there are only some pockets at eastern
Taiwan, Davao and eastern Manado that still illustrated a
probability of occurrence for a Mw 8.0 earthquake in the next
50 years of >70% (Fig. 7d).
4. PROSPECTIVE EARTHQUAKE SOURCE
Beside the earthquake activities, as proposed by Yadav et al.
(2011), a large number of research works have applied the b-
of the FMD for earthquake forecasting differently. For instance,
comparatively low b-values were shown to correlate empir-
ically with a high level of accumulated stress in that specific
area (Scholz, 1968; Wyss, 1973), whilst congruency between
a low b-value area and the location of following earthquakes
has been reported (e.g., Schorlemmer et al., 2003; Nuannin
et al., 2005; Chan et al., 2012). In particular, Nuannin et al.
(2005) proposed that by using the 50 earthquake events closest
to individual site of interest a comparatively low b-value can
be used as an effective precursor of the upcoming earthquakes.
Thus, the investigation of the prospect of an upcoming
earthquake in each area in this study was evaluated using the
In order to affirm compliance of the 1980–2011 complete-
ness earthquake dataset to the assumption of Nuannin et al.
(2005), it was separated into the three subsets of 1980–1995,
1980–2000 and 1980–2005. These three datasets were then
evaluated for their spatial b-value distributions following Nuan-
nin et al. (2005)’s assumption. In each grid node, the b-value
was determined using the dataset of the 50 earthquakes located
closest to the evaluation point and then mapped (Figs. 8a–c).
For each individual b-value map, earthquakes with Mw 7.0
were overlaid on the map in order to check for the reliability
of using the spatially mapped b-values (implemented with
Nuannin et al. (2005)’s condition) to reliably forecast forth-
coming earthquakes. The outcome showed a good correlation
between the obtained b-value and the location of subsequent
earthquakes. Therefore, the most up-to-date earthquake dataset
of 1980–2010 was used in this evaluation and the results are
mapped in Figure 8d.
Based mainly on the present-day b-value map (Fig. 8d), six
areas with a comparative low b-value were located. These were
at (i) eastern Taiwan, (ii) northwestern Manila, (iii) western
Manila, (iv) western Davao, (v) eastern Davao and (vi) eastern
Manado (Fig. 8d).
For western Davao and eastern Manado (iv and vi), two major
earthquakes occurred in this area in 2010 (Mw-7.3 earthquake
on April 4th and Mw-7.5 earthquake on July 23th). In addition,
for the eastern part of Taiwan (i), 13 main shocks with a
magnitude of 4.3–5.8 were generated during the 4 months
from January 7th to April 21st, 2013 including more than 50
events of foreshocks and aftershocks. Thus, for the prospect
areas of the forthcoming earthquakes, these six areas are strong
candidates, in particularly for northwestern and western Manila
(ii and iii), including eastern Davao (v), where the obtained
low b-values were found in a recently quiescent area.
5. DISCUSSION AND CONCLUSION
In this study, the earthquake hazard in the Philippines Islands
and the adjacent areas were investigated using the earthquake
FMD. The completeness earthquake catalogue was provided
in order to spatially evaluate the a- and b-value coefficients of
FMD, which are needed for the seismic hazard determination.
From the obtained a- and b-value maps, the possible maximum
magnitude, recurrence interval and probability of occurrence
(Yadav et al., 2011) of earthquakes with a Mw > 5.0 were
For the potential largest earthquake magnitude, the offshore
region of the eastern part of Taiwan was defined as the most
hazardous zone and was capable of generating earthquakes
with a magnitude up to 8.0 Mw in the next 50 years, and with
return periods of <1, 2–4, 5–20 and 20–40 years for earth-
quakes with a Mw of 5.0, 6.0, 7.0 and 8.0, respectively.
In addition, the other high seismic-prone areas were located
at (i) Davao and (ii) eastern Manado, where the HSZ, PSZ
and SSZ (nos. 2, 6 and 7) are delineated. Earthquakes may
occur in these areas with a maximum magnitude of 6.8 and
Earthquake in Philippines 887
Fig. 8. The b-value maps of the Philippines Islands and the adjacent areas analyzed from the earthquake data recorded during (a) 1980–
1995, (b) 1980–2000, (c) 1980–2005 and (d) 1980–2010. Red stars are the Mw 7.0 earthquakes posed after the earthquake data used
for determining the b-value.
888 Santi Pailoplee and Natchana Boonchaluay
7.1 Mw in a 5 and 10 year-period, respectively. For the northern
MST and eastern SLT areas (nos. 4 and 9), the average time
intervals for earthquake occurrences were around 100–200
years for earthquake magnitudes of 7.0–8.0 Mw. In contrast,
within the limits of the recorded earthquake events, the area
in the vicinity of PWT, SAT and SLT (nos. 5, 8, and 9) were
classified seismically as aseismic source zones.
For the probabilities (%) of earthquake occurences in the
next 50 years, an earthquake with a Mw 5.0–6.0 is likely over
the whole study area with an almost 100% probability, whilst
the probability for 7.0 and 8.0 Mw earthquake vary across the
region, but were almost 100% and >70%, respectively, in the
the high hazard areas at Taiwan, Davao and eastern Manado.
With respect to regional earthquake forecasting, the b-values
were mapped using the condition proposed by Nuannin et al.
(2005) after confirming compliance to the assumption over
three sub-datasets of earthquakes recorded before 2005. Using
the 1980–2010 dataset, six prominent areas with low b-values
were found at (i) eastern Taiwan, (ii) northwestern Manila,
(iii) western Manila, (iv) western Davao, (v) eastern Davao
and (vi) eastern Manado. Thus, mitigation plans should be
contributed in these surrounding areas.
ACKNOWLEDGMENTS: This research was supported by the ASEAN
Studies Center, Chulalongkorn University. Thanks are also extended to
T. Pailoplee for the preparation of the draft manuscript. I thank the
Publication Counseling Unit (PCU), Faculty of Science, Chulalongkorn
University, for a critical review and improved English. I acknowledge
the thoughtful comments and suggestions by the editors and anonymous
reviewers that enhanced the quality of this manuscript significantly.
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Manuscript received December 1, 2014
Manuscript accepted March 9, 2016