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Loss and gain of land of Manpura island of Bhola district: An integrated approach using remote sensing and GIS

DOI:10.3329/dujbs.v22i1.46271
Authors:
Md Shahjahan Ali
Md Shahjahan Ali
Md Shahjahan Ali
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Fazlul Haque
Fazlul Haque
Fazlul Haque
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Shah Md Mizanur Rahman
Shah Md Mizanur Rahman
Shah Md Mizanur Rahman
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Kazi Farhed Iqubal at State University of Bangladesh
Kazi Farhed Iqubal
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Abstract and Figures

The erosion‐accretion pattern in Manpura island has been depicted over a 37 years period from 1973 ‐ 2010. Data of different years revealed that the island is under the threat of erosion and the total area has gradually decreased from 148 to 114 Km 2. Although Manpura island is under the threat of erosion, some lower mid parts get in irregular erosion ‐ accretion processes, where area of water bodies has decreased up to a significant level (15 Km 2) and the area of mangrove forests have also decreased to 6 Km 2. According to this study, total land loss of Manpura island is 34 Km 2 in the last 37 years and major erosion took place along the northern shore line.
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DhakaUniv.J.Biol.Sci.22(1):29‐37,2013(January)
LOSSANDGAINOFLANDOFMANPURAISLANDOFBHOLA
DISTRICT:ANINTEGRATEDAPPROACHUSING
REMOTESENSINGANDGIS
MD.SHAHJAHANALI1,MD.FAZLULHAQUE1,SHAHMD.MIZANURRAHMAN1,KAZI
FARHEDIQUBAL2,NAZMA3ANDASHFAQUEAHMED*
DepartmentofBotany,UniversityofDhaka,Dhaka‐1000,Bangladesh
Keywords:Meghnaestuary,ManpuraIsland,Landerosion,Mangroves,Remotesensing
Abstract
Theerosion‐accretionpatterninManpuraislandhasbeendepictedovera37
yearsperiodfrom1973‐2010.Dataofdifferentyearsrevealedthattheislandis
underthethreatoferosionandthetotalareahasgraduallydecreasedfrom148
to114Km2.AlthoughManpuraislandisunderthethreatoferosion,somelower
midpartsgetinirregularerosion‐accretionprocesses,whereareaofwater
bodieshasdecreaseduptoasignificantlevel(15Km2)andtheareaofmangrove
forestshavealsodecreasedto6Km2.Accordingtothisstudy,totallandlossof
Manpuraislandis34Km2inthelast37yearsandmajorerosiontookplacealong
thenorthernshoreline.
Introduction
TheMeghnaestuaryisaverydynamicestuarineandcoastalsystemwhereratesof
erosionandaccretionareveryhigh.Theriverswidenseverelyerodingtheirbanks.The
offshoreislandsgraduallymigratesouthwards,andthemainlandbuildsouttowardsthe
estuary(1).Sedimentconcentrationsarehighintheentireestuary,notonlyduringthewet
monsoonseasonbutalsointhedryseasonresultingintheaccretionofsmallislands(1).
Tidalcurrentsaregenerallystrongenoughtomaintainsedimentsinsuspension.The
river‐bornesedimentsbecometrappedintheestuarybytheeffectsofpumpingresidual
circulation(2).
Tidalactionisalsoahighlydynamicphenomenonthatvariesnotonlywiththe
seasonsoftheyearbutalsochangethroughouttheyearresultinginaneverchanging
geography.ThewavesfromtheIndianOceantravelratherfastthroughthedepthofthe
BayofBengalandarrivesatCox´sBazarandHiranPointataboutthesametime(3).The
shallowareainfrontofthedeltacausessomerefractionanddistortionofthetidalwave.
ThroughadeeptidalinletintheeasternpartoftheBay,thetidestravelfastalongthe
*Authorforcorrespondence.<aashfaque67@yahoo.com>.1BangladeshSpaceResearchandRemoteSensing
Organization(SPARRSO),MinistryofDefense(MoD),GovernmentofBangladesh.2Departmentof
EnvironmentalScience,StateUniversityBangladesh.3LocalGovt.EngineeringDepartment,Governmentof
Bangladesh.
30ALIetal.
easterncoastwhilenumerousshoalsandislandsinthewestofferfrictionalresistanceto
thepropagationofwaves,resultinginaphaselagbetweentheeasternandwesternpart
oftheestuary.Duetothisphaselaganddifferenceintidalrange,aneast‐westcurrentis
developedduringtherisingtide(4).
TheestimatedaverageannualsedimentloadcarriedbytheriversofBangladeshto
theBayofBengalisaround2billiontonsannually(5).TheGangesandtheBrahmaputra
areheavilyladenwithfinesediments.TheGangesrivercarriesfinesedimentswitha
heavyclayloadwhereastheBrahmaputrariverparticularlytransportsfinesandandsilt
insuspension.TheMeghnariverappearstobearelativelylowsedimentladenriver.Of
thethreerivers,theshareofGangeswithannualaverageconcentrationof1300mg/land
theBrahmaputrawith1000mg/lisalmostequalwhiletheshareofMeghnawith100mg/l
isaboutone‐tenth(4).
TheGanges‐Brahmaptra‐Meghna(GBM)riversystemwiththeirnumerous
tributariesanddistributariescarry,distributeanddisposewaterandsedimentsinthe
BengalBasinincludingdeltaicpartandtheBayofBengal.TheGanges,Jamunaand
BrahmaputrariverscoalesceintotheMeghnainthebasinalpartandthenfallintothe
BayofBengal.ThehugeinfluxofsuspendedsedimentswhicharecarriedouttotheBay
ofBengal,bythesemightyriverssystem,theGBMsystem,resultedintheformationof
manyoffshoreislands(6).TheManpuraIslandwhichissituatedatMeghnaestuaryisone
ofthem.
TheMeghnaestuarypassedthroughmanychangesduringthelast200years.The
majorchangeswerethemigrationofchannelsandgrowthofsomenewislandsinthe
southernpart.InRennellʹsmapof1789,theMeghnawasfoundtoflowinaneasterly
directionwithsomesoutherlyflowingminordistributaries(7).In1898,withinatimespan
of109years,themainflowofMeghnabifurcatedintotwochannels,onetotheeastand
theothertothewestofHatiaisland.In1945,withinaperiodof45years,thestrengthof
thecurrentoftheeasternchannelbecameweakwiththedominationofthesoutherly
flowwhichiscalledtheShahbazpurchannel.A12kmlongMeghnacrossdam‐1was
constructedin1957,whichdivertedthedirectionoftheflowtowardsthesouththrough
theShahbazpurchannel(6).Thechannelisdividedintotwodownwardparalleldirections
keepingtheManpuraislandinthemiddle.Thestrongdownwardflowtendstocause
erosiontothefrontiershoreandinsomeadjacentlowerpartsoftheisland.
Remotesensingimageryprovidesinformationaboutvariouslandformtypesin
spatialformatwhichisusefulforerosionassessment(8).Itisanimportantsupplementto
groundobservationsandtobuildupthepaleographicrecordsofearthresources.The
rapidevolutioninsatelliteremotesensingintermsofspatial,spectral,radiometricand
temporalresolutionsofdifferentsensorsandtheavailabilityofearthrelatedsynoptic
dataindigitalformathaverevolutionizedthetechniquesforresourceplanningandtheir
management.
LOSSANDGAINOFLANDOFMANPURAISLANDOFBHOLADISTRICT31
Thepresentstudyisaimedtoestimatetheerosionandtheaccretionoflandmassof
ManpuraislandusingLandsatMSSandTMimagesovertheperiodof37yearssince
1973.Usingofremotelysenseddataprovidesmanyadvantagesincludingsynoptic
coverage,availabilityoflow‐costorfreesatellitedata,availabilityofhistoricalsatellite
data,andrepeatedcoverage.Withtheadvancesinthehardwareandsoftwareusedfor
processingalargevolumeofsatellitedatatheusefulnessofremotelysenseddatahas
increased(9).Thestudyresultedinpreparationofpaleographicmapandphysiographic
dataoftheisland.Theaccruedinformationmayprovidehelpforfurtherstudyandfor
takinguptheplanfordevelopmentactivitiesofManpuraisland.
MaterialsandMethods
ThepresentstudyhasbeenconductedonManpuraislandunderBholadistrictwhich
lieswithin90°52.28′Eto22°20.85′Nand90°98.00′Eto22°02.63′N.Itissituatedinthe
northernpartoftheBayofBengal,atthemouthoftheMeghnariver.Manpuraislandis
boundedontheeastbytheHatiyaislandandonthewestbyShahbazpurchannel,on
thenorthbyCharPatliaandCharNizam.Theisland’ssouthsideisopentotheBayof
Bengal.ThestudywasconductedonthemainManpuraisland.Astherearenoother
stablesmallislandsclosetooraroundthemainisland,thechanginggeomorphological
effectsovertheentireareaarenotmuchmoreimportantforstudy.
TheManpuraislandisaflatlandmass;thehighestpeakisaroundthreemetersabove
thesealevel.Therearesomehighlandsontheisland,buttheseareman‐made,likeroads
andembankments.ThesoiloftheManpuraislandiscalcareousalluviumandsaline(10).
Begumetal.(11,12)havestudiedthemorphological,mineralogicalandedaphologiccal
aspectsofsoilofManpuraislandandfoundpredominatelyloamysoilwithanaverage
contentof51%siltand21%claywithcoloursvaryingfromverydarkgreytodarkgrey.
Itisseasonallyflooded,poorlydrainedanddevelopedinveryyoungmediumtextured
deposits.ItoccursextensivelyontheyounglowerMeghnaestuarinefloodplain(3).The
climateofthestudyareaistypicalmonsoonal.Basedonthepressure,rainfalland
temperature,theclimateoftheislandcanbedescribedunderfourseasons:(a)winter,(b)
summerofpre‐monsoon,(c)monsoonand(d)autumnofpostmonsoon.
ThetidalwavesfromIndianOceantravelratherfasterthroughthedeepBayof
Bengal.ThesewavesarriveatCoxʹsBazarandatHironPointofKhulnaataboutthe
sametime(
3).
Theextensiveshallowareainfrontofthedeltacausessomerefractionand
distortionofthetidalwaves.Asaresult,thewavesbunchupandhitstheislands,
especiallyattheloweranditsassociatedeastandwestsurroundings,whichcausesthe
erosionoftheislands(Fig.2).
32ALIetal.
Fig.1.LocationofthestudyareawithinBangladesh.
Fig.2.ThewavedirectionintheBayofBengal.
ThebottomtopographyofthesurroundingareasofManpuraislandischaracterizedby
numeroussubmergedshoalsandbarrierbars.Watermovingovertheseshoalsand
barrierbarsinducescomplicatedturbulencewhichcanalsobeareasonforerosionofthe
island(3).
LOSSANDGAINOFLANDOFMANPURAISLANDOFBHOLADISTRICT33
Wavessignificantlyinfluencetheerosionanddepositionalprocess,especiallyduring
monsoon.Thesouth‐westmonsoontendstoaccumulatewaterinthenorth‐easternpart
oftheBay.Thisaccumulatedwatertogetherwiththehugemonsoonalwaterofthe
channelsaffectthesea‐levelandcauseswellingofwaterataboutonemeterwhichmay
stimulateerosion(3).
Asithasbeenmentionedthatduetothebuildingofcrossdams(Meghnacrossdam‐
1andcrossdam‐2),thepositionofflowdirectionoftheformerchannelshavebeen
laterallymigratedfromeasttowardthewest.AsaresultofthistheShahbazpurchannel
becameprominent.Thechannelwasdividedintotwosouthwardparalleldirections,
keepingtheManpuraislandatthemiddleofitsflow.Thestrongdownwardcurrentof
thechannelhitstheupperfrontieroftheislandwhichcausesitserosion(3).
Inthepresentstudy,satellitedata,availablepublishedmaps,reportsandsecondary
datahavebeenused.LandsatMSSimagesofdifferentperiods,from1973to2010(Table
1)hasbeenusedforquantifyingthelandmassareasofManpuraisland.Alltheimages
werereceivedinthewinterseason,whennormallytheskyisclearandcloudfree.
LandsatsatellitepassesthecoastalareaofBangladeshafter10minutesofitscrossingthe
equatorat09.30a.m.localtime.Waterleveldatahasbeentakenfromyearlytidetable
publishedbyDepartmentofHydrography,BangladeshInlandandWaterTransport
Authority.ThewaterleveldatawererecordedatCharChunarstationofsouth‐west
Hatiacoast,whichisadjacenttotheeastShahbazpurchannel.Normally,thetidalwaves
intheBayofBengalriseuptothreemetersfromitsnormallevel.Fromtherecorded
valuesofwaterheight,itisseenthat,LandsatMSSof1980andTMof1989imagesareat
high/mediumhighperiodandresttwoimagesareduringverylowtidalconditions.
TidalrecordforLandsatMSSimageof1973wasnotfoundintherecordtable.
Themethodologyadoptedforthisstudyinvolvesboththedigitalimageprocessing
andGISbasedanalysis.Landsatimagesweregeometricallycorrectedandgeo‐referenced
withrespecttoanexistingcorrectedLandsatimageusingtheRasterModuleofERDAS
Imagine.TheRGBcolourcompositesimageswerepreparedforthestudyasshownin
Table1.
Standardvisualinterpretationmethodbasedontone,texture,pattern,shapeandsize
ofthefeatureswasusedforextractionofnecessaryinformation.Mainlythreelayersof
informationwereextracted,likelandmass,riverandmangroveforestareasfromallthe
fivetemporalimages.
Arc/Infosoftwarewasusedforgeneratingthetopologyoftheextractedlayersand
attributeswereaddedintheattributetableforeachthemeandaspatialdatabasewas
created.Threegeneratedspatialdatalayerswerethenconsideredforanalysisbasedon
34ALIetal.
theestimationoferosionandaccretionpatternoflandmassoftheislandovertheperiod
of37yearsfrom1973‐2010.Acompositepaleographicmapwaspreparedcomprising
theinterpretedlandmassboundariesoftheislandwhichshowedtheconfigurationof
Manpuraislandoverthesaidhistoricalperiod.
ResultsandDiscussion
 Thestudyhasidentifiedboththeaccretionandtheerosionpatternsbypreparinga
paleographicmapoftheManpuraislandduringaspanof37years(1973‐2010).Massive
changeshaveoccurredinthenorthernshoreoftheisland.Totalof3.0kmoflandfrom
topnorthernpartoftheislandwaserodedawayduringtheperiodof37years.During
thisperiod,theislandlostlandalong500meterslaterallyalongtheentireeastsideand
about800metersoflandwasdroppedintotheseaalongthenorthwesthalfoftheisland.
Theislandalsolostits400hectaresoflandinitssouthernextremityoverthesaid
historicalperiod.Aregularpatternoferosionisobservedalongboththesidesof
northernhalf,whereassomeexceptionswerenoticedalongthelowerandmid‐lower
partoftheisland(Fig.3).

Fig.3.MapshowingtheconfigurationofManpuraislandovertheperiod1973‐2010.
LOSSANDGAINOFLANDOFMANPURAISLANDOFBHOLADISTRICT35
Comparativestudyoftheyears1973,1980,1989,1997and2010revealedthatthetotal
areaoftheislandgraduallydecreasedfrom148to114Km2.Ratesoflanderosion
(Km2/year)were2.57,0.016,1.0and0.55throughtheyears1973‐1980,1980‐1989,1998‐
1997and1997‐2010.So,thegeneraldecreasingtrendofthelandmassofManpuraisland
pointsoutthattheislandisunderthestressoferosionalprocess.Erosionismoreactive
insouthernandnorthernextremityoftheisland(Fig.4)wherethetotalerodedareawas
foundtobe34Km2.
0
20
40
60
80
100
120
140
160
1973 1980 1989 1997 2010
Sqkm
Year
Total(River+Land)
RiverArea
LandArea(incl.mangrove)
MangroveArea
Fig.4.ChangeoftotallandareaofManpuraIslandfrom1973to2010anditsprobable
trendoferosion.
Consideringthehighandlowtidephenomenon,itcanbeanalyzedthat,landmass
areasacquiredfromthelowtidehours’imagesof1997and2010arefoundtobesmaller
thanhightideperiods’imageof1980and1989.Thedifferenceoflandmassareaswould
havebeenmuchhigheriftheimagesof1980and1989weretakenduringlowwaterlevel
hours.So,thegradualdecreasingresultoflandmassovertheperiodsminimizesthe
questionsofusingtheimagesindifferenttidallevelconditions.
Thestudyalsorevealedthattotalwaterbodyareadecreasedfrom17to1Km2.This
wasbecauseofthehugedownwardsedimentsenteringintheriverfromupperstream,
whichgottrappedinbytheupwardbumpingtidalflowfromthebay.Asaresult,river
levelsarefilledupandtotalinlandwaterareawasdecreased(Table2).FromTable2the
statisticsofmangroveforestintheislandshowsthat,in1973totalmangroveareawas26
Km2,whichwasreducedto20Km2by2010.Before37years,extensionsofmangrove
areasweredonemainlyalongtheinlandriverbanksandonthelowerpartoftheisland.
Therewerealsosomeplantedmangroveareassurroundingtheseashoreregionofthe
island.Astheriverswerenarroweddownduetohumaninterference,mostofthe
36ALIetal.
mangroveareasinthemidandupperpartoftheislandhavebeendiminished.Butitis
observedthatmuchdensemangroveareashavebeendevelopedinthesouthernpartand
thesamesituationisprevailingsince1997,whicharehelpinginsomewaytoprotectthe
extremesoutherntipoftheisland.Ahmedetal.(13)reportedthechangesofmangrove
vegetation,riverandcanalsandlandareaofSundarbanMangroveForests(SMF)of
Bangladeshforaperiodof21yearswhichshowedanincreasinglandmassoftwo
Rangesfor1989to2000whichsubsequentlydecreasedinthenextdecade(2000to2010).
Girietal.(9)reportedanincreaseinthenetforestareaby1.4%fromthe1970sto1990sand
adecreaseby2.5%from1990to2000ofthetotalSundarbanMangroveForestofboth
BangladeshandIndia.
Table1.CharacteristicsofLandsatdatausedforthestudy.
Data(Bands/RGB)DateIntervalsTidalheight
LandsatMSS(421)02Feb.1973 ‐‐ ‐‐
LandsatMSS(421)15Jan.198007years2.12m
LandsatTM(432)12Jan.198909years1.90m
LandsatTM(432)19Jan.199708years0.62m
LandsatTM(432)30Jan.201013years0.44m
Table2.Area(Km2)statisticsofgeneratedlayersofManpuraisland.
YearTotal
(river+land)
RiverLand
(includingmangrove)
Mangrove
forests
1973 14816.80131.3525.56
19801327.83124.2829.84
19891293.00125.9019.89
19971212.63118.2619.55
20101141.42112.2919.54
Remotesensingdatahavebeenutilizedinquantifyingthechangeoflandmass
patternofManpuraisland.Thepaleographicmapoftheislandwaspreparedusing
LandsatMSSandLandsatTMmulti‐dateandmulti‐spectralimageryovertheperiodof
1973‐2010.
Although,thestudyhasbeencarriedoutonboththeerosionandaccretionhistoryof
theisland,specialemphasiswasgivenontheerosionalprocessoflandmass.Itisbecause
ofthecontinuouserosionprocessofthelandareathatdominatedtheveryfewaccretion
eventswhichoccurredduringthestudyperiod.
ThestudydemonstratedthechanginglandmassofthemainManpuraislandonly.A
fewfar‐offsubmergedislandswhicharevisibleinlowtideconditionswerenot
consideredinthisstudy.
LOSSANDGAINOFLANDOFMANPURAISLANDOFBHOLADISTRICT37
Thedepletionofmangrovesintheupperpartoflandmassandstrongdownward
pressureofwaterthroughShahbazpurchannelsalongwithbumpingtidesandlong
shorecurrentarethecausalfactorsinlanderosionoftheisland.
Thisstudywouldbehelpfultoconductthetemporalphysiographyandtosome
extent,thenaturalphenomenonforinitializingthedevelopmentplanofManpuraisland.
Acknowledgment
Mr.MuziburRahmanHowlader,(Chairman,SPARRSO,Dhaka)hasgivenguideline
andpermissionforusingtherecentsatelliteimagesoftheManpuraislandandsome
otherrelevantinformationandpublicationstotheauthors.Thesupportfromthis
organizationishighlyappreciated.
References
1.AhmedA,MOhlson,SHoqueandMGMoula2010.Edaphicconditionsunderdifferent
hydrologicalregimesinthecoastalzoneofBangladesh.DhakaUniv.J.Biol.Sci.19(1):
27‐40.
2. SaifuddinA1996.Residualtidalandsedimentvolume,theircirculationpatternsandland
coverchangesintheMeghnaestuary.J.CivilEngineering26(1):61‐83
3. TarafderSA1995.StratigraphicalandHydro‐chemicalinvestigationsoftheKutubdiaIsland
withspecialreferencetothegeologicalevolution.FinalReport,Dhaka.
4. SkidmoreAK,WBijker,KSchmidtandLKumar1997.UseofremotesensingandGISfor
sustainablelandmanagement.ITCJournal3‐4:302‐315.
5. PotdarSS,RSrivastava,MSSNagaraju,JPrasadandRKSaxena2003.Mappingoferosional
soillossinNanda‐KhairiwatershedofNagpurdistrictofMaharashtrausingremotely
senseddataandGIStechniques.Agropedology13:10‐18.
6. BurroughPAandRAMcDonnell1998.PrincipalsofGeographicalInformationSystems,Oxford
UniversityPress.
7. ChoudhuryNV1973.RemotesensingofnaturalresourceofBangladeshthroughEarth
ResourceTechnologySatelliteProgramm.
8. SahaSKandBMSingh1991.SoilerosionassessmentandmappingofAglarriverwatershed
(U.P.)usingremotesensingtechnique.J.IndianSocietyofRemoteSensing19:67‐76.
9. GiriC,BPengra,ZZhu,ASingh,LLTieszen2007.Monitoringmangroveforestdynamicsof
theSundarbansinBangladeshandIndiausingmulti‐temporalsatellitedatafrom1973to
2000.Estuar.Coast.andShelfSci.73:91‐100.
10. DurandJMandYHKerr1989.Animproveddecorrelationmethodfortheefficientdisplayof
mulhspectraldata,IEEETrans.Geosci.RemoteSens27(5):611‐619.
11. BegumA,MSHussain,SMUllahandFOttner2004.Morphologicalandmineralogicalfeatures
ofsomesoilsfromManpuraislandinBangladesh.J.Asiat.Soc.Bangladesh,Sci.30(1):
17‐24.
38ALIetal.
12.BegumA,MSHussainandSMUllah2004.Astudyofpedologicalandedaphologicalaspects
oftheManpuraislandincoastalareaofBangladesh.S.AsianJ.Agric.1(2):84‐91.
13. AhmedA,AAziz,AZMNAKhan,MNIslam,KFIqubal,NazmaandMSIslam.2011.Tree
diversityasaffectedbysalinityintheSundarbanMangroveForests,Bangladesh.
BangladeshJ.Bot.40(2):197‐202.
(Manuscriptreceivedon28April,2012;revisedon7January,2013)
... Assessment of erosion susceptibility at large spatial scales (global) is quite ineffective since coastal processes are complex, being highly influenced by local factors and requires a large amount of data in GISbased models (Fitton et al., 2016). There are a number of GIS-based studies conducted on coastal erosion at regional and local scales (Dolan et al., 1980;Saha and Singh, 1991;White and El-Asmar, 1999;Shifeng et al., 2002;Azab and Noor, 2003;Potdar et al., 2003;Wang, 2003;Zoran and Anderson, 2006;Hegde and Reju, 2007;Jimmy, 2010;Prabaharan et al., 2010;Alves et al., 2011;Iqubal and Ali, 2011;Lins-de-Barros and Muehe, 2011;Shibly and Takewaka, 2012;Alam and Uddin, 2013;Chowdhury and Tripathi, 2013;Islam et al., 2013;Sarwar and Woodroffe, 2013;Fernandez-Nunez et al., 2015;Reeder-Myers, 2015). Most of the studies, however, identified coastal erosion by lines in vector-based GIS model (Harvey and Woodroffe, 2008;Lins-de-Barros and Muehe, 2011). ...
... The LSCE model is applied here for the coastal area of Bangladesh as a case study. Previous GIS-based studies (Saha and Singh, 1991;Potdar et al., 2003;Prabaharan et al., 2010;Iqubal and Ali, 2011;Shibly and Takewaka, 2012;Alam and Uddin, 2013;Islam et al., 2013;Sarwar and Woodroffe, 2013) have assessed shoreline retreat and the rate of erosion and accretion in the coastal area of Bangladesh and the Bay of Bengal region. However, the present research analysed the spatial (i.e. ...
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Full-text available
  • Apr 2022
Coastal morphological change and landscape dynamics have been creating a new window for taking immediate sustainable management strategies for coastal resources management. The dynamic nature of coastal morphological response includes erosion/accretion of landmass, development of an island by sedimentation, movement of the island, and change in geometry and shape. The objectives of the study illustrate morphological change, driver, and mechanism of morphological change, and the effects of morphological change on coastal landscape dynamics. The study also explores spatio-temporal landscape dynamics effects on coastal ecosystem services and livelihood pattern of the coastal community. The novelty of the present research is that how morphological change influence in response to landscape dynamics and its ecosystem services by exploring historical data including shoreline change, century scale erosion and accretion, stability of the islands since 1776 to 2021. In this study, historical maps (i.e., Rennell’s map in 1776 and Tassin map in 1840), Topographic Survey map (1943) and remotely sensed digital image (i.e., Landsat TM in 1990, 2000 and 2010, and Landsat OLI in 2021) have been used to quantify coastal geomorphological change and landscape dynamics through RS and GIS tools and techniques. The finding of the study showed remarkable change occurred in geomorphology of the Monpura Island over the period of 245 years. The spatial coverage of the island has been declined dramatically, which is quantified ∼2905 ha from 1776 to 2021. In the century scale from 1840 to 1943, erosion is observed higher than accretion, and the statistics showing that 8963.40 ha eroded along the east flank of Island. In the northern flank of the Island, Net Shoreline Movement (NSM) and the rate of shoreline movement which expressed by EPR showed highest and flowed by ∼4 km and -126.55 m/y toward landmass. During the epoch 1990–2021, because of morphological change and anthropogenic interventions, the crop land of the Island has been significantly declined by ∼38%, while the rivers and settlement spatial coverage have been increased by ∼768% and ∼153%, with an annual rate of change ∼25% and ∼5% respectively. These outcomes and prepared maps of the current research will be supportive for the local inhabitant, coastal morphologist, and environmental resources management manager, national and international policy advisor, government and non-movement stakeholder, researcher to observe coastal morpho-dynamics including shoreline dynamics, coastal erosion and accretion and its impacts on landscape and ecosystem services.
... Another factor is the continuous erosion and accretion around the boundary, particularly on the eastern and western side of the island (Islam et al., 2021b). Moreover, people migrated to this island as a result of the erosion of the nearby islands and coastal areas (Ali et al., 2013;Emran et al., 2019;Kabir et al., 2020). Due to lack of adequate law enforcement and awareness, people still haphazardly migrate to one island to another in that zone, and also use multiple islands for grazing, agriculture, fishing etc., apart from the island they dwell. ...
Combining Geographical Information System (GIS) and machine learning to monitor and predict vegetation vulnerability: An Empirical Study on Nijhum Dwip, Bangladesh
Article
Vegetation loss has become a global concern as it is directly and indirectly harmful to all living beings, specifically to humans. By realizing the dimension of this issue, we have developed an Artificial Neural Network (ANN) based model by combining GIS and machine learning to investigate and predict the vegetation vulnerability with reliable accuracy. This model incorporates a sequence of geostatistical analyses, i.e., Normalized Difference Vegetation Index (NDVI), Hot Spot Analysis (Gi*) and Inverse distance weighted (IDW). 8 drivers, used in this study, were shuffled differently to obtain the highest accuracy possible and investigate their influence on land shift. However, the model was implemented on Nijhum Dwip island to quantify its credibility and evaluate the ecological stability and vulnerability status of this island. According to the findings, the island has undergone significant change between 2001 and 2021. The overall vegetative area has increased in this time as a result of the ecological reforestation projects undertaken after 2001. Then, our developed hybrid model was used to simulate the hot spot map of 2021 to quantify the accuracy of the model. Anyway, the kappa statistics was found more than 0.86 with 88.75% overall correctness, and the same weight values were utilized to predict the hotspot map of 2026 and 2031. The predicted maps showed a gradual increase in the vulnerable zones, which is the outcome of the uncontrolled extracting of natural resources. Eventually, the methodological knowledge of this study can help researchers as well as policymakers to estimate vegetation vulnerability and legislate new policies that support sustainable development, and the quantitative knowledge on Nijhum Dwip can facilitate future planning of this island.
... The monitoring of coastal land dynamics around the world through using GIS and remote sensing techniques is not new. In fact, there are numerous studies (Dolan et al.,1980;Saha and Singh, 1991;White and El-Asmar, 1999;Shifeng et al., 2002;Azab and Noor, 2003;Potdar et al., 2003;Wang, 2003;Zoran and Anderson, 2006;Jimmy, 2010;Prabaharan et al., 2010;Iqubal and Ali, 2011;Shibly and Takewaka, 2012;Alam and Uddin, 2013;Chowdhury and Tripathi, 2013;Islam et al., 2013;Sarwar and Woodroffe, 2013) conducted for different coastal areas using aerial photographs, GIS and remote sensing techniques. Depending on the behavior of the coasts, a number of approaches based on numerical models (Ferreira et al., 2006;Zoran and Anderson, 2006) have been used where dynamic stability, erosion, and accretion of the shores have been assessed. ...
Where is the coast? Monitoring coastal land dynamics in Bangladesh: An integrated management approach using GIS and remote sensing techniques
Article
This paper draws upon the application of GIS and remote sensing techniques to investigate the dynamic nature and management aspects of land in the coastal areas of Bangladesh. The geomorphological characteristic of the coastal areas is highly dynamic where land erosion and accretion with different rates remain a constant phenomenon. This study focuses on three coastal zones: western, central and eastern that comprise the entire coastal area of the country. At its core, this study uses the past 30 year Landsat satellite images. This research reveals that the rate of accretion in the study area is slightly higher than the rate of erosion. Overall land dynamics indicate a net gain of 237 km² (7.9 km² annual average) of land in the area for the whole period from 1985 to 2015. The results also demonstrate that the rates of both erosion and accretion are higher in the central zone compared to the western and the eastern zones of the coastal area. This is the first time that the entire coastal areas of Bangladesh have been considered for assessment. This study also recommends that coastal managers, planners and policymakers to consider the identified dynamic trends of coastal land before opting for any specific measure. Constant monitoring using the GIS and remote sensing techniques would be a viable management for this purpose. This study has identified some causes of land dynamics, particularly for the three coastal zones, that might be helpful for policymakers in identifying the nature of interventions needs to be taken for specific coastal zones.
Edaphic conditions of different islands under different hydrological regimes in the coastal zone of Bangladesh
Article
Full-text available
  • Nov 2011
Physical and chemical properties of soils from the southern coastal zone of Bangladesh were studied to understand the effect of inundation on different soil variables. Soil samples were collected from three different islands representing different hydrological regimes, viz. Char Motherbunia (Island I) is inundated twice daily, Char Taposhi (Island II) is inundated by high tide and Char Kashem (Island III) is totally raised, inundated only during storm surges. Three transects in each island perpendicular to the river Buragauranga were established. Five soil samples, each with a composite of five sub-samples, were collected from each transect, 15 variables were tested from total 15 samples of each island. To test the variations among the islands and within the island, ANOVA was used. Soils of the three islands were found to be rather similar in chemical properties, although there were some significant differences in pH and potassium concentration. The results indicated that broad-scale hydrology did not effect the variation found in the edaphic condition rather duration and amplitude may be responsible for some observed variation. A correlation matrix of the soil variables showed a strong correlation among chemical elements and that the majority of elements were significantly correlated with pH.
Use of remote sensing and GIS for sustainable land management
Article
Full-text available
  • Jan 1997
Remote sensing provides the basic data to undertake inventory of land, as well as the temporal information required to monitor sustainable land management practices. In this papaer, the current use of remote sensing for sustainable land managemnt is reviewed, and the potential of future (new) satellite systems to contribute to sustainable development is explored. Other elements for successful sustainable development (ie, good policy and participatory approaches) are then compared and contrasted with information requirements.
Tree diversity as affected by salinity in the Sundarban Mangrove Forests, Bangladesh
Article
Full-text available
  • Dec 2011
A botanical expedition to the Sundarban Mangrove Forests (SMF) in March, 2010 was made to study the tree diversity and their abundance as affected by salinity gradient. In six quadrats of 25m × 25m each, distributed in all four Ranges, a total of eight tree species were recorded. A maximum number of five species occurred in relatively low saline sites. Tree zonation dynamics of the forests along salinity gradient revealed an increase in the number of Ceriops decandra (goran), a salt tolerant plant in the north-eastern parts of the SMF which was dominated by Heritiera fomes (sundri), a freshwater loving plant in 1960's. Highest importance value index (IVI) was recorded for C. decandra, which was present in all sites, except Moroghodra, a freshwater zone in Nalianala (Khulna) Range. Comparison of the Landsat images of Nalianala and Chandpai Ranges during 1989, 2000 and 2010 revealed a decreased tendency of dominance of H. fomes in the two Ranges but increased tendency of Bruguiera sexangula (kankra), Excoecaria agallocha (gewa) and Sonneratia apetala (keora). Total tree cover in 2010 decreased by about 3% from that of 1989. The changes in the tree composition have been attributed to increased salinity. The changes in the physiography and tree composition of the two Ranges between 2000- 1989 were considerable.
Geographical Information Systems
Chapter
  • Jan 2015
A geographical information system (GIS) consists of a database of attributes, spatial information, geospatial operators that link the two, user interface, and analytical, statistical and modeling features. GISs have grown rapidly in this century in business, government, and mass consumption markets. Location has become pervasive with mobile devices. By industry, GIS is often applied in natural resources, transportation, utilities, supply chain, agriculture, real estate, newspapers, and banking/finance. The benefits of GIS beyond nonspatial IS are improved accuracy of decision making, recognition of geography in operations and management, improved problem solving through geographic analysis, and ability to geo-design future solutions.
Soil erosion assessment and mapping of the algar river watershed (uttar pradesh) using remote sensing technique
Article
  • Jun 1991
This study was undertaken to prepare an inventory on soil erosion of a hilly river watershed — the Aglar watershed, part of Tehri Garhwal and Dehradun districts (U.P.), using terrain physiography and soil survey data obtained from interpretation and analysis of Landsat TM FCC (1:62,500 scale) and limited ground investigations. The watershed is divided into four broad physiographic units viz. higher Himalayas (> 2000m elevation); lower Himalayas (< 2000m elevation); river terraces and flood plains. Each physiographic unit has been further divided into subunits on the basis of aspects and landuse. Three major orders of soils viz. Inceptisols, Mollisols and Entisols were found in different physiographic units. Soil, and land properties of soilscape units viz. soil depth, texture, structure, slope, landuse and soil temperature regime were evaluated for soil-erosion hazard. The results indicate that in the whole watershed 19.13%, 45.68%, 26.51% and 7.92% areas have been found to be under none to slight, moderate, severe and very severe soil erosion hazard categories, respectively.
Monitoring mangrove forest dynamics of the Sundarbans in Bangladesh and India using multi-temporal satellite data from 1973 to 2000
Article
  • Jun 2007
Mangrove forests in many parts of the world are declining at an alarming rate—possibly even more rapidly than inland tropical forests. The rate and causes of such changes are not known. The forests themselves are dynamic in nature and are undergoing constant changes due to both natural and anthropogenic forces. Our research objective was to monitor deforestation and degradation arising from both natural and anthropogenic forces. We analyzed multi-temporal satellite data from 1970s, 1990s, and 2000s using supervised classification approach. Our spatio-temporal analysis shows that despite having the highest population density in the world in its periphery, areal extent of the mangrove forest of the Sundarbans has not changed significantly (approximately 1.2%) in the last ∼25 years. The forest is however constantly changing due to erosion, aggradation, deforestation and mangrove rehabilitation programs. The net forest area increased by 1.4% from the 1970s to 1990 and decreased by 2.5% from 1990 to 2000. The change is insignificant in the context of classification errors and the dynamic nature of mangrove forests. This is an excellent example of the co-existence of humans with terrestrial and aquatic plant and animal life. The strong commitment of governments under various protection measures such as forest reserves, wildlife sanctuaries, national parks, and international designations, is believed to be responsible for keeping this forest relatively intact (at least in terms of area). While the measured net loss of mangrove forest is not that high, the change matrix shows that turnover due to erosion, aggradation, reforestation and deforestation was much greater than net change. The forest is under threat from natural and anthropogenic forces leading to forest degradation, primarily due to top-dying disease and over-exploitation of forest resources.
An improved decorrelation method for the efficient display of multispectral data
Article
A technique to enhance multispectral image displays and to improve their visual interpretations is proposed. The decorrelation approach is tested with a SPOT simulation and thematic mapper image. The technique is considered to be of great help for the interpretation of remotely sensed images. Furthermore, the choice between two-, three-, and N -dimensional decorrelation allows the user to adjust to specific cases. However, the main drawback of this technique is its strong link to the statistics of the image being displayed, which makes the analysis of the displayed image data (in terms of spectral properties of the surface, for example) more complex. For a specific application conducted with a given satellite, this inconvenience could be overcome by using a set of fixed linear combinations
Residual tidal and sediment volume, their circulation patterns and land cover changes in the Meghna estuary
  • Jan 1996
  • 61-83
  • A Saifuddin
Saifuddin A 1996. Residual tidal and sediment volume, their circulation patterns and land cover changes in the Meghna estuary. J. Civil Engineering 26(1): 61-83
Remote sensing of natural resource of Bangladesh through Earth Resource Technology Satellite Programm
  • Jan 1973
  • N V Choudhury
Choudhury NV 1973. Remote sensing of natural resource of Bangladesh through Earth Resource Technology Satellite Programm.
Morphological and mineralogical features of some soils from Manpura island in Bangladesh
  • Jan 2004
  • 17-24
  • A Begum
  • S M Hussain
  • F Ullah
  • Ottner
Begum A, MS Hussain, SM Ullah and F Ottner 2004. Morphological and mineralogical features of some soils from Manpura island in Bangladesh. J. Asiat. Soc. Bangladesh, Sci. 30(1): 17-24.