Earthquake-induced landslide monitoring and survey by means of InSAR

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 Canaslan Çomu , F., Gü bo˘ ga, ¸S., and Smail, T.: Es i- ma ion o co-seismic land de o ma ion due o Mw7.3 2017 ea hquake in I an (12 No embe 2017) using Sen inel-1 DInSAR, Bull. 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