Na . Haza ds Ea h Sys . Sci., 22, 1609–1625, 2022
h ps://doi.o g/10.5194/nhess-22-1609-2022
© Au ho (s) 2022. This wo k is dis ibu ed unde
he C ea i e Commons A ibu ion 4.0 License.
Ea hquake-induced landslide moni o ing
and su ey by means o InSAR
Tayeb Smail1, Mohamed Abed1, Ahmed Meba ki2,3, and Milan Lazecky4,5
1Depa men o Ci il Enginee ing, Uni e si y o Blida 1, Blida Ci y, Alge ia
2Uni e si y Gus a e Ei el, UPEC, CNRS, Labo a o y Mul i Scale and Simula ion (MSME/UMR 8208),
5 bl d Desca es, 77454 Ma ne-la-Vallée, F ance
3Jiangsu Key Labo a o y o Haza dous Chemicals Sa e y and Con ol, Nanjing Tech Uni e si y,
5 New Mo an Rd, Gulou, Nanjing, 211816, Jiangsu, China
4IT4Inno a ions, VSB-TU Os a a, 17, Lis opadu 15, 70833 Os a a-Po uba, Czech Republic
5School o Ea h and En i onmen , Uni e si y o Leeds, Leeds LS2 9JT, UK
Co espondence: Tayeb Smail ([email p o ec ed]) and Ahmed Meba ki (ahmed.meba ki@uni -ei el. )
Recei ed: 7 July 2021 – Discussion s a ed: 15 July 2021
Re ised: 13 Ap il 2022 – Accep ed: 15 Ap il 2022 – Published: 13 May 2022
Abs ac . This s udy uses in e e ome ic syn he ic ape u e
ada (SAR) echniques o iden i y and ack ea hquake-
induced landslides as well as lands p one o landslides, by
de ec ing de o ma ions in a eas s uck by ea hquakes. The
pilo s udy a ea in es iga es he Mila egion in Alge ia, which
su e ed signi ican landslides and s uc u al damage (ea h-
quake: Mw5, 7 Augus 2020). DInSAR analysis shows no -
mal in e e og ams wi h small inges. The cohe ence change
de ec ion (CCD) and DInSAR analysis we e able o iden i y
many landslides and g ound de o ma ions also con i med by
Sen inel-2 op ical images and ield inspec ion. The mos im-
po an displacemen (2.5 m), loca ed in he Khe ba neigh-
bo hood, caused se e e damage o dwellings. I is wo h no-
ice ha CCD and DInSAR a e e y use ul since hey we e
also able o iden i y g ound c acks su ounding a la ge zone
(3.94 km2a ea) in G a em Ci y, whe eas he Sen inel-2 op-
ical images could no de ec hem. Al hough displacemen
ime-se ies analysis o 224 in e e og ams (Ap il 2015 o
Sep embe 2020) pe o med using LiCSBAS did no de ec
any p e-e en geo echnical p ecu so s, he pos -e en anal-
ysis shows a 110 mm y −1subsidence eloci y in he back
hillside o Khe ba.
1 In oduc ion
Al hough i is s ill challenging o p edic exac ly whe e and
when na u al haza ds (ea hquakes, landslides, loods, e c.)
migh occu , he capaci y o moni o and su ey he zones
p one o impo an landslides and he capaci y o iden i y
and loca e hose impac ed by ea hquakes a e key issues in
isk mi iga ion, educ ion, p epa edness, and adap a ion. Ac-
ually, since ea hquakes and landslides migh occu in many
places wo ldwide, hey migh cause a huge numbe o ic-
ims, impo an socio-economic damage, and asse damage
and losses. Thei impac can be signi ican ly educed hanks
o sa elli e imaging, which allows p edic ion and ea ly ale s
o some landslide cases (Jacquema and Tiampo, 2021;
Mazzan i e al., 2012; Mo e o e al., 2021).
I is hen wo h de ec ing o p edic ing c i ical g ound
changes a speci ic places, ei he a e a geo echnical haza d
occu s due o landslides and ea hquakes mainly o be o e i
is suddenly igge ed (Bakon e al., 2014; Gal e e al., 2015).
Such challenges can be ackled by egula image-p ocessing-
o ien ed landslide a ea moni o ing, in he a e ma h o ea h-
quakes, using SAR in e e ome ic me hods and op ical im-
ages, o ins ance. Ac ually, since SAR (syn he ic ape u e
ada ) is an ac i e senso sys em ha uses mic owa e sig-
nals o collec da a backsca e ed om he ea h’s su ace,
he use o sa elli e imaging sys ems like in e e ome ic SAR
me hods appea s o be a cos -e ec i e way o measu ing
Published by Cope nicus Publica ions on behal o he Eu opean Geosciences Union.
1610 T. Smail e al.: Ea hquake-induced landslide moni o ing and su ey by means o InSAR
millime e -le el displacemen s o he ea h su ace (He e a
e al., 2009) a a egional scale and can be used as an ea ly
wa ning sys em o he sa e y o s uc u es and hei su -
oundings (Gal e e al., 2015; Roque e al., 2015).
The expec ed ou comes a e based upon he p ocessing
o SAR da a as hey use di e en ial InSAR (DInSAR), co-
he ence change de ec ion (CCD), and ime se ies analy-
sis (LiCSBAS so wa e). LiCSBAS exploi s he LiCSAR
da a ha p ocess InSAR da ase s au oma ically (Sen inel-1),
aking ad an age o high- esolu ion SAR sensing, in o de o
ack g ound changes and landslides.
The SAR analyses aim o de ec g ound de o ma ions
h ough DInSAR and CCD in es iga ions as hey conside ,
o illus a i e pu poses, a ci y in Alge ia s uck by an ea h-
quake (7 Augus 2020: Alge ia, Mila): he g ound de o ma-
ions and displacemen s, in Khe ba Ci y and G a em Ci y
(no heas e n pa o Mila down own, 2km), a e in es i-
ga ed. The a ec ed a eas span o e 3.94 km2 o G a em and
2.1 km2 o he Khe ba landslides. Fu he mo e, a ime-se ies
analysis o LiCSAR da a pe o med by LiCSBAS so wa e
in es iga es he possible exis ence o p ecu so s in geo ech-
nical condi ions.
2 Land and g ound mo emen moni o ing and
su eying in he a e ma h o an ea hquake
2.1 Sa elli e images and me hods – case s udy
The p esen esea ch s udy is mul i old. I aims o use InSAR
image p ocessing o a ious pu poses, in he case o land-
slides and ea hquakes.
–We use InSAR in he a e ma h o an ea hquake in o -
de o iden i y he geo echnical displacemen s o de-
o ma ions, hei ex en , and loca ions. The Di e en ial
ada in e e ome y and he Cohe ence Changes De ec-
ion a e he mos adap ed me hods o g ound and soil
su ace change de ec ion (Jung and Yun, 2020; Meng
e al., 2020; Pawluszek-Filipiak and Bo kowski, 2020;
Tampuu e al., 2020; Tzou a as e al., 2020). A ci y,
Mila, in no he n Alge ia, is conside ed as he pilo
s udy. I was s uck by an ea hquake in Augus 2020.
The landslides and su ace c acks we e a ec ed signi -
ican ly du ing he ea hquake e en s, wi h wo dis inc
zones being almos 15 km om each o he (Khe ba and
G a em).
–We use ime-se ies analysis o in es iga e he displace-
men s and hei eloci ies be o e and a e he occu -
ence o he main shock. Fo he ci y o Mila, he
ime se ies is pe o med o a pe iod ex ending om
Ap il 2015 o Oc obe 2020, i.e., a long pe iod be o e
(5 en i e yea s) he main shock in o de o a oid a dis-
u bance o bias ha migh be ela ed o seasonal e -
ec s such as ains and ege a ion e ec s (Lazeck e al.,
2020a), and a sho pe iod (4 mon hs) ahead o he e en
da e in o de o in es iga e he his o ical de elopmen o
he landslide.
–We compa e and co ela e he InSAR image p ocessing
esul s wi h he sa elli e op ical image obse a ions.
2.2 Pilo zone, ea hquakes, and landslides – obse ed
diso de s
The case s udy a ea lies in Mila P o ince, which is loca ed
in he no heas pa o Alge ia (Medi e anean zone), nea
he dam o Beni Ha oun. The Medi e anean zone is seis-
mically ac i e because o he no hwa d con e gence (4–
10 mm y −1) o he A ican pla e ela i e o he Eu asian
pla e along a complex pla e bounda y (F izon de Lamo e
e al., 2000; Mouloud and Bad eddine, 2017; Peláez Mon-
illa e al., 2003; USGS, 2021b). Th oughou he las yea s,
se e al landslide e en s ha e aken place in he wide egion
o Mila (Me ghadi e al., 2018). Me ghadi e al. (2018) con-
s uc ed a de ailed landslide in en o y map o he s udy a ea.
The seismic ac i i ies and landslides pose a pe sis en h ea
o buil -up a eas and acili ies, such as oadways, b idges,
and unnels, which need con inuous moni o ing and su ey.
A e an ea hquake (Mw5, 7 Augus 2020, epicen-
e 36.550◦N–6.271◦E, dep h =10 km, USGS, 2021a) ha
s uck his egion, impo an landslides we e mos ly obse ed
in Mila Ci y and i s su oundings (see Figs. 1–3). Al hough
he ea hquake was mode a e, Beni Ha oun Dam and he wo
la ge b idges buil on he RN 27 highway need o be in-
spec ed and hei possible displacemen s moni o ed.
In he p esen wo k, wo a eas a e s udied, i.e., Khe ba
and G a em ci ies. The al i ude a he op poin 1 (Fig. 2a)
in Khe ba hill is 654 and 411 m o he uppe poin (2),
loca ed 2.14 km away wi h 11.34 % slope. The maximum
g ound ho izon al o se eached 2.5m, and he e ical de-
o ma ions exceed 1.8m (Fig. 3b) a he op o Khe ba hill
(poin A Fig. 2a). The slope ailu e bounda y o Khe ba Ci y
is mapped as shown in Fig. 2b. The G a em a ea o in e -
es (AoI) is loca ed no heas o Mila in hilly g ound wi h an
a e age slope eaching 12.5 % (see Fig. 2c).
2.3 Pilo zone – da a and image collec ion
The da ase used o his s udy is collec ed om he Eu-
opean Space Agency (ESA), ia he Cope nicus Open
Access po al, and om he Alaska Sa elli e Facili y
(ASF DAAC, 2021). The C-band Sen inel-1 A and B,
launched in 2014 and 2016, espec i ely, p o ide egu-
la da ase s. The Sen inel-1 senso s ha e a wa eleng h o
5.546 cm (ESA, 2021a, b), sui able o change de ec ion and
moni o ing o la ge a eas, and a e igh side-looking wi h an
incidence angle anging app oxima ely om 20 o 46◦(ESA,
2012). Fo he InSAR use, he in e e ome ic wide (IW)
swa h single look complex (SLC) da a a e selec ed and p o-
cessed wi h he open-sou ce so wa e SNAP (Sen inel Ap-
Na . Haza ds Ea h Sys . Sci., 22, 1609–1625, 2022 h ps://doi.o g/10.5194/nhess-22-1609-2022
T. Smail e al.: Ea hquake-induced landslide moni o ing and su ey by means o InSAR 1611
Figu e 1. Mila loca ion map (le panel), ascending and descending o bi oo p in s. Red s a s indica e ea hquake epicen e (QGIS, ESRI
basemap).
Figu e 2. The 3D iew o AoIs, Khe ba AoI, and G a em using QGIS wi h DEM SRTM 1sec and ESRI basemap. Panels (a, b) show he
Khe ba AoI, and (c) shows he G a em case a ea. The ed polygon is he bounda y o change de ec ed by InSAR.
plica ions Pla o m). I is wo h using da a om many o -
bi s o moni o he AoIs due o di e en o ien ed di ec ions,
incidence angles o sa elli es, and he g ound opog aphy.
The op ical images o Sen inel-2 sa elli es a e ob ained om
ESA, whe eas downloading and p ocessing da a a e done ia
QGIS, Semi-Au oma ic Classi ica ion Plugin (SCP) (Con-
gedo, 2021).
Fo he Mila egion, he AoI is co e ed by h ee o bi s;
wo a e ascending (66, 59) and one is descending (161)
(Fig. 1). Since he p esen s udy in ends o de ec he a -
eas in luenced by landslides, many p e-e en and pos -e en
da a we e used. Eigh een Sen inel-1 A and 17 Sen inel-1 B
images (a o al o 35) we e downloaded o moni o Mila’s
a ea o he pe iod om 1 July o 26 Oc obe 2020. Table 1
summa izes he app op ia e in e e og ams, i.e., hose ha ing
small pe pendicula baselines and sho empo al baselines.
Tables 1–3 p esen all he images, wi h hei labels as IFG-
ID, O bi s, and da es o acquisi ion.
The empo al baselines o all InSAR pai s a e 6 d, excep
he las h ee pai s o he ascending o bi 66 ha ha e 12d.
Fu he mo e, since a bad cohe ence map o he IFG-24 (O -
bi 161) may lead o misin e p e a ion o esul s, p io acqui-
si ion da a (be o e 3 Augus ) a e selec ed o gene a e he co-
e en in e e og am (IFG-22). The e o e he empo al base-
line is 12 d. The g ay ows in Table 1 ep esen he co-e en
in e e og ams o he h ee o bi s. The pe pendicula base-
lines also gua an ee a good quali y o InSAR s udies (B aun,
2019). As LiCSBAS ime se ies analysis aims o in es iga e
long-pe iod displacemen s and eloci ies o e a la ge a ea:
34 in e e og ams om o bi 66 and 190 in e e og ams col-
lec ed om he 161 ascending acks (Table 2), a e selec ed
o he p esen s udy.
h ps://doi.o g/10.5194/nhess-22-1609-2022 Na . Haza ds Ea h Sys . Sci., 22, 1609–1625, 2022
1612 T. Smail e al.: Ea hquake-induced landslide moni o ing and su ey by means o InSAR
Figu e 3. G ound c acks due o landslides in Khe ba, Mila, ∼2.5m o se owa ds he no h. (a) D one ae ial pho o om LNHC (2021).
(b, c) La e al displacemen s (pho os: cou esy M. Yacoub Ali, Uni e si y o Se i , Alge ia).
Table 1. Cha ac e is ics o Sen inel-1 InSAR pai s used o his s udy.
IFG-ID T ack Mda e Sda e Bp [m]B [d]
IFG-0
66 Ascending
22 Jul 2020 28 Jul 2020 -9.99 6
IFG-1 28 Jul 2020 3 Aug 2020 40.90 6
IFG-2 28 Jul 2020 3 Aug 2020 40.62 6
IFG-3 3 Aug 2020 9 Aug 2020 −51.47 6
IFG-4 3 Aug 2020 9 Aug 2020 −50.76 6
IFG-5 9 Aug 2020 15 Aug 2020 −27.57 6
IFG-6 9 Aug 2020 15 Aug 2020 27.62 6
IFG-7 15 Aug 2020 21 Aug 2020 −16.19 6
IFG-8 21 Aug 2020 27 Aug 2020 42.43 6
IFG-9 27 Aug 2020 2 Sep 2020 −28.59 6
IFG-10 2 Sep 2020 8 Sep 2020 29.26 6
IFG-11 8 Sep 2020 14 Sep 2020 17.95 6
IFG-12 14 Sep 2020 20 Sep 2020 −6.05 6
IFG-13 20 Sep 2020 2 Oc 2020 −4.64 12
IFG-14 2 Oc 2020 14 Oc 2020 18.13 12
IFG-15 14 Oc 2020 26 Oc 2020 −49.36 12
IFG-16
59 Ascending
27 Jul 2020 2 Aug 2020 69.64 6
IFG-17 2 Aug 2020 8 Aug 2020 −75.10 6
IFG-18 8 Aug 2020 14 Aug 2020 −8.86 6
IFG-19 14 Aug 2020 20 Aug 2020 175.97 6
IFG-20 20 Aug 2020 26 Aug 2020 −226.75 6
IFG-21
161 Descending
22 Jul 2020 28 Jul 2020 −169.19 6
IFG-22 28 Jul 2020 9 Aug 2020 30.39 12
IFG-23 28 Jul 2020 3 Aug 2020 99.88 6
IFG-24 3 Aug 2020 9 Aug 2020 −70.12 6
IFG-25 9 Aug 2020 15 Aug 2020 2.14 6
IFG-26 15 Aug 2020 21 Aug 2020 121.22 6
IFG-27 21 Aug 2020 27 Aug 2020 −196.82 6
B : empo al baseline; Bp: pe pendicula baseline.
Na . Haza ds Ea h Sys . Sci., 22, 1609–1625, 2022 h ps://doi.o g/10.5194/nhess-22-1609-2022
T. Smail e al.: Ea hquake-induced landslide moni o ing and su ey by means o InSAR 1613
Table 2. LiCSAR ames, analysis pe iods, and he o al numbe o
IFGs used in his s udy.
F ame ID Da e Pe iod IFGs
S a End
161A_05343_090806 26 Ap 2015 26 Sep 2020 66 mon h 190
066D_05394_131311 5 Ap 2020 26 Sep 2020 6 mon hs 34
Table 3. Sen inel-2 op ical images collec ed o he s udy case.
F ame Da e Du a ion
ID o
he main
shock (days)
Image 1 30 Jul 2020 −7 d
Image 2 9 Aug 2020 +2 d
3 Me hodology desc ip ion and esul s
Fou aspec s a e in es iga ed and compa ed in he p esen
case s udy:
– he SAR In e e ome ic (InSAR) me hodology, which
is subdi ided in o h ee sub-g oups,
–DInSAR o he phase changes ( inges),
–CCD o he cohe ence change de ec ion,
– ime se ies analysis and LiCSAR da a,
– he op ical image p ocessing.
E e y image con ains he desc ip ion o i s sou ce, i.e., IFG-
ID (Tables 1–3) o he image’s acquisi ion da es.
3.1 SAR in e e ome ic me hodology
The syn he ic ape u e ada (SAR) is an ac i e mic owa e
imaging sys em. I is independen o sunligh and pene a es
clouds, unlike passi e op ical imaging sys ems. The in e -
e ome ic SAR me hod uses he phase componen s o co-
egis e ed SAR images o he same pixel o es ima e he
opog aphy and o measu e he su ace change in he a -
ge a ea (Kim, 2013). A leas wo cons ella ion images a e
needed o gene a e an in e e og am, which con ains opo-
g aphic, a mosphe ic e ec , baseline e o , and noise com-
ponen s (Gouda zi, 2010; Kim, 2013; Ne zband e al., 2007):
φ=φdisp +φ la +φ opo +φa m +φo bi +φnoise,(1)
whe e φdisp is he line-o -sigh (LOS) displacemen , φ la he
la ea h phase, φ opo he opog aphic phase, φa m an a -
mosphe ic phase, φo bi he baseline phase, and φnoise noise
phase con ibu ion (Kim, 2013).
The main s eps o p ocessing da a using SNAP so -
wa e (DInSAR and CCD) a e depic ed in Fig. 4. I is wo h
no icing ha o CCD p ocessing, i is no necessa y o ol-
low he whole wo k low (DInSAR, phase unw apping, and
phase o displacemen ).
3.1.1 Di e en ial ada in e e ome y (DInSAR)
Di e en ial ada in e e ome y (DInSAR) exploi s he
phase di e ence o measu e cohe en changes o de o ma-
ion be ween wo image acquisi ions. I is o en used o
g ound subsidence measu emen (Canaslan Çomu e al.,
2020; Gal e e al., 2015). One o DInSAR’s limi a ions is
ha he changes a e no measu able in he case o non-
cohe en e en s (e.g., apid landslide) (B aun, 2019) such as
he p esen s udy.
3.1.2 Cohe ence change de ec ion (CCD)
The es ima ed cohe ence is conside ed a quali y indica o o
an in e e og am (Jacquema and Tiampo, 2021). Ac ually,
i indica es ha he phase and ampli ude o he ecei ed sig-
nal exp ess he deg ee o simila i y be ween he image pai .
The pixel cohe ence γo wo SAR images is es ima ed on
he basis o Nneighbo ing pixels (Jia e al., 2019; Wang e
al., 2018).
γ=
N
P
i=1
S1iS∗
2i
sN
P
i=1
|S1i|2N
P
i=1
|S2i|2
,(2)
whe e S1iand S2ia e he complex signal alues o he SAR
image pai , Nis he window o neighbo ing pixels, and ∗is
he complex conjuga e.
The cohe ence alues ange be ween 0 and 1 so ha he
map is ep esen ed as a g ay colo , whe e 0 is whi e and 1 is
black.
3.1.3 Time se ies analysis and LiCSAR da a
The “Looking in o Con inen s om Space wi h Syn he ic
Ape u e Rada ” (LiCSAR) sys em au oma ically p ocesses
Sen inel-1 da ase s o InSAR use and gene a es w apped
and unw apped in e e og ams and cohe ence maps (Lazeck
e al., 2020b), wi h a inal p oduc esolu ion o ∼26.5 m
(Lazeck e al., 2020a). Fo such pu poses, he open-sou ce
LiCSBAS so wa e, adop ed in he p esen s udy, is used o
InSAR ime se ies analysis based on LiCSAR da a. I can
gene a e maps o LOS displacemen eloci y and de o ma-
ion ime se ies o all p ocessed ames. Fu he mo e, i is
easy o implemen and does no equi e high-pe o mance
compu ing acili ies (Mo ishi a, 2021).
In addi ion, he mechanism o landslides can be ho -
oughly s udied h ough LiCSBAS analyses. They ely on he
InSAR ime-se ies analysis package in eg a ed in o LiCSAR
h ps://doi.o g/10.5194/nhess-22-1609-2022 Na . Haza ds Ea h Sys . Sci., 22, 1609–1625, 2022
1614 T. Smail e al.: Ea hquake-induced landslide moni o ing and su ey by means o InSAR
Figu e 4. Wo k low cha o he DInSAR p ocessing using (SNAP) so wa e.
(Lazeck e al., 2020b). Such ime-se ies analyses a e e y
use ul in iden i ying, o a gi en landslide o g ound de o -
ma ion and displacemen , he p io pa e ns o g ound mo e-
men s e sus he ime.
3.2 Op ical image p ocessing
The op ical senso s a e passi e de ec ion means ha need
sunligh and clea wea he condi ions o exploi he da a. The
Sen inel-2 is a mul i-spec al ins umen (MSI) ha measu es
e lec ed sola adiance in 13 bands wi h a mode a e spa ial
esolu ion o 10 m in he ed, g een, blue, and nea -in a ed
bands (Lane e e al., 2021).
The op ical da a collec ed om he ESA pla -
o m (Sen inel-2) a e ea ed and plo ed using QGIS
so wa e o gene a e ue-colo images (bands 2, 3, and 4
co esponding o RGB). The p esen s udy skips he image
o 3 Augus 2020 due o bad wea he condi ions, so ha only
he wo images collec ed and men ioned in Table 3 we e
used o alida e he g ound changes de ec ed by InSAR.
4 Applica ion o he case s udy and esul s
The case s udies a e loca ed in wo di e en si es, and bo h
a eas o in e es a e loca ed in Alge ia. They ha e a hilly e-
lie : he i s one is loca ed no heas o Mila Ci y (G a em)
and he second is in he wes e n pa o Mila Ci y (Khe ba).
To moni o he AoIs, se e al images a e p ocessed and used
wi h di e en o bi di ec ions ( o al o 35 ascending and de-
scending acquisi ions; see Fig. 1) o ca ch de o ma ion om
di e en angles along he senso ’s LOS. The InSAR ech-
nique is used in bo h a eas o de ec land de o ma ion and
landslides igge ed by he ea hquake.
The adop ed me hods a e applied o he Mila case s udy
o
–de ec and measu e he co-e en su ace displacemen s
and landslides, caused by he ea hquake (CCD and
DInSAR);
–moni o hei dynamic e olu ion in he i s weeks and
mon hs, in he pos -e en pe iod (CCD and LiCSAR
da a);
–analyze hei possible ini ia ion ahead o he ea hquake
by mon hs and yea s, in he p e-e en pe iod (Time-
se ies me hods and LiCSAR da a);
–co obo a e he esul s by compa ing se e al me hod
ou pu s, i.e., SAR (CCD, DInSAR, LiCSAR), ae ial op-
ical pho o (Sen inel-2), and ield su eys.
The quali y o he SAR image is consis en wi h he opog a-
phy slopes and a ea oughness. Ac ually, he AoI has ough
opog aphy, hills, and i e s (Fig. 2). Selec ing ei he ascend-
ing o descending passes, elying on which will a oid some
limi a ion o InSAR, is an ex emely essen ial ac ion o in e
he de o ma ion om a ious angles. The e o e, conside ing
he egional opog aphy and geology o he AoI is necessa y
o p ocess InSAR and in e p e esul s.
The di e en ial InSAR (DInSAR) me hod is help ul o in-
es iga e co-seismic e ec s and de ec g ound changes. The
p oduced in e e og ams and cohe ence images a e p ojec ed
o WGS84 e e ence, wi h a pixel size o 13.4m. The un-
w apped in e e og ams p esen phase con ibu ion o many
noise esou ces (a mosphe ic) (see Fig. 5). In gene al, s ong
ea hquakes cause la ge-scale inge pa e ns a ound he epi-
cen e , which is no he case in he e en unde s udy (a mod-
e a e ea hquake). P ocessing DInSAR analysis may hen
lead o misin e p e a ion due o a mosphe ic con ibu ion in
di e en ial phase in e e og ams (Figs. 5 and 6). In he s udy
case, no egional de o ma ion due o he ea hquake is ob-
se ed, and he e is no need o con inue in es iga ing he dam
and he wo b idges by simple DInSAR. Howe e , o moni-
o he dam and b idges, i is highly ecommended o use
Na . Haza ds Ea h Sys . Sci., 22, 1609–1625, 2022 h ps://doi.o g/10.5194/nhess-22-1609-2022
T. Smail e al.: Ea hquake-induced landslide moni o ing and su ey by means o InSAR 1615
Figu e 5. W apped in e e og ams om Sen inel-1 o IFG-3+IFG-4, IFG-17, and IFG-22. The ed s a is he epicen e loca ion
(USGS,2021a).
Figu e 6. Mila a ea, InSAR cohe ence maps o IFG-3+IFG-4, IFG-17, and IFG-22.
Figu e 7. De ec ed inges in in e e og ams 3, 17, and 22, wi h images ocused on he G a em zone.
PS-InSAR o egional and local g ound de o ma ion de ec-
ion (Hoope e al., 2004; Rapan e al., 2020; Sanab ia e al.,
2014).
This mode a e ea hquake has igge ed small de o ma ion
and landslides in G a em, Khe ba, and Azeba. The IFG-3 and
IFG-4 a e me ged in o one image due o he AoIs (Khe ba
and G a em), which a e loca ed in wo di e en image ac-
quisi ions o he descending o bi numbe 66.
4.1 Case o G a em
The de ec ion o de o ma ion o changes be ween wo In-
SAR images e eals a small change in he egion o G a em.
This change is obse ed as small inges, wi h each inge
co esponding o a displacemen o a hal -wa eleng h (λ=
5.546 cm) in he LOS di ec ion (Figs. 7 and 9). Usually, co-
he en change does no appea in cohe ence images as a da k
egion, bu in he s udy case, he ou e bo de line o he inge
egion shows incohe ence change, which is clea ly isible in
cohe ence maps (Fig. 8).
A ime-se ies analysis hen needs o be pe o med o p o e
whe he his con ou was o med on he e en occu ence
da e (7 Augus 2020). The cohe ence maps o he co-e en
pe iod p esen a da k polygon ha is ela ed o incohe en
change o de o ma ion. Bu inside he AoI, he esul s show
h ps://doi.o g/10.5194/nhess-22-1609-2022 Na . Haza ds Ea h Sys . Sci., 22, 1609–1625, 2022
1616 T. Smail e al.: Ea hquake-induced landslide moni o ing and su ey by means o InSAR
Figu e 8. Cohe ence maps o G a em AoI: he images ep esen p e-e en (a, d, g), co-e en (b, e, h), and pos -e en (c, , i) o o bi s 66,
59, and 161. No e: he co-e en maps o he h ee o bi s show he decay o cohe ence ha is igge ed by he ea hquake.
some cohe en changes, which mean ha his a ea has de-
o med as a block up o down.
Acco ding o phase and cohe ence maps, he a ec ed a ea
is app oxima ely 3.94 km2, wi h an a e age unou dis ance
o 2.6 km om op o downhill (Fig. 2a dis ance om poin 1
o poin 2).
4.2 Case o Khe ba
DInSAR has abundan ly demons a ed i s eliabili y as a
echnique o moni o ing slow mo emen s (Cascini e al.,
2013; Wempen, 2020). In he p esen s udy, Khe ba’s land-
slides exceed he capabili ies o DInSAR since his me hod
canno measu e he de o ma ions due o incohe en change
a he i s e en (Fig. 10). Phase images o he egion o in-
e es (RoI) show a clea deco ela ion, and consequen ly, he
phase in o ma ion is no longe con enien o analysis.
In such cases o incohe en changes in he scene, DInSAR
is useless, whe eas he cohe ence change de ec ion (CCD)
me hod emains use ul and sui able o moni o he e en .
4.2.1 CCD imes se ies analyses
Fo he case s udy, he cohe ence maps (Figs. 11–13) show
e y low cohe ence in he Khe ba a ea, indica ing ha some
changes ha e occu ed. The CCD quan i ies changes be-
ween wo SAR images and is ep esen ed as a decay o co-
he ence alues (co-e en maps). Dec eases in cohe ence al-
ues can be caused by a a ie y o ac o s such as geo echnical
landslides as well as wa e and ege a ion. To dis inguish be-
Na . Haza ds Ea h Sys . Sci., 22, 1609–1625, 2022 h ps://doi.o g/10.5194/nhess-22-1609-2022
T. Smail e al.: Ea hquake-induced landslide moni o ing and su ey by means o InSAR 1617
Figu e 9. The 3D iew o G a em a ea, images o IFG-3. Each inge is he wa eleng h di ided by 2 in LOS, and ed zones ep esen exis ing
building compounds (QGIS, ESRI basemap).
Figu e 10. Khe ba main e en in e e og ams; biased pixels inside he ed line co espond o incohe en changes.
Table 4. Mean cohe ence change alues inside he RoI.
O bi P e-e en Co-e en Pos -e en P e-e en Pos -e en
cohe ence cohe ence cohe ence change change
mean mean mean
66 28Jul_03Aug 03_09Aug 09_15Aug −23 % +24 %
0.66 0.51 0.63
59 27Jul_02Aug 02_08Aug 08_14Aug −22 % +15 %
0.77 0.60 0.69
161 22Jul28Jul 28Jul09Aug 09Aug 15Aug −9 % +37 %
0.57 0.52 0.71
ween na u al low cohe ence and induced su ace changes, a
second cohe ence map (p e-e en o pos -e en ) is equi ed
o se e as a e e ence, which can be compa ed wi h he main
co-e en images. I is p e e able o mask he es o he non-
changed a ea using a a io o p e-e en o co-e en images
and il e alues equal o o less han 1 (see Fig. 13).
The CCD ime-se ies analysis displays he changes in he
AoI o e ime o he Khe ba landslide. The da k egion ep-
esen s he main changes ha occu ed du ing he co-e en
pe iod (ea hquake da e). The landslide shape is di ided in o
wo oes a he lowe side o he hill, as shown in Figs. 11
and 12.
Du ing he i s week ollowing he ea hquake, changes
a e de ec ed in he lowe side o he hill and las ed un il he
la e da e o Augus 2020 (IFG-8 o bi s 66, IFG-27 o bi 161,
and IFG-20 o o bi 59). A e wa ds, many o he sou ces o
noise we e p esen in he AoI, which makes his echnique
less e icien (wea he , human ac i i ies). Mos o he p o-
cessed images a e 6 d in e als, excep o bi 161 in which he
co-e en in e e og am (IFG-24) was no good enough (bad
h ps://doi.o g/10.5194/nhess-22-1609-2022 Na . Haza ds Ea h Sys . Sci., 22, 1609–1625, 2022
1624 T. Smail e al.: Ea hquake-induced landslide moni o ing and su ey by means o InSAR
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