GROUND DEFORMATION AND ITS CAUSES IN ABBOTTABAD CITY, PAKISTAN FROM SENTINEL-1A DATA AND MT-INSAR - MDPI
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remote sensing
Article
Ground Deformation and Its Causes in Abbottabad
City, Pakistan from Sentinel-1A Data and MT-InSAR
Naeem Shahzad * , Xiaoli Ding , Songbo Wu and Hongyu Liang
Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hong Kong,
China; xl.ding@polyu.edu.hk (X.D.); sabriwu@outlook.com (S.W.); allenhongyu.liang@connect.polyu.hk (H.L.)
* Correspondence: naeem.shahzad@connect.polyu.hk
Received: 24 September 2020; Accepted: 15 October 2020; Published: 20 October 2020
Abstract: Land subsidence, as one of the engineering geological problems in the world, is generally
caused by compression of unconsolidated strata due to natural or anthropogenic activities.
We employed interferometric point target analysis (IPTA) as a multi-temporal interferometric
synthetic aperture radar (MT-InSAR) technique on ascending and descending Sentinel-1A the terrain
observation with progressive scans SAR (TOPSAR) images acquired between January 2015 and
December 2018 to analyze the spatio-temporal distribution and cause of subsidence in Abbottabad City
of Pakistan. The line of sight (LOS) average deformation velocities along ascending and descending
orbits were decomposed into vertical velocity fields and compared with geological data, ground water
pumping schemes, and precipitation data. The decomposed and averaged vertical velocity results
showed significant subsidence in most of the urban areas in the city. The most severe subsidence
was observed close to old Karakorum highway, where the subsidence rate varied up to −6.5 cm/year.
The subsidence bowl profiles along W–E and S–N transects showed a relationship with the locations
of some water pumping stations. The monitored LOS time series histories along an ascending orbit
showed a close correlation with the rainfall during the investigation period. Comparative analysis of
this uneven prominent subsidence with geological and precipitation data reflected that the subsidence
in the Abbottabad city was mainly related to anthropogenic activities, overexploitation of water,
and consolidation of soil layer. The study represents the first ever evidence of land subsidence and its
causes in the region that will support the local government as well as decision and policy makers for
better planning to overcome problems of overflowing drains, sewage system, littered roads/streets,
and sinking land in the city.
Keywords: land subsidence; Sentinel-1A; multi-temporal InSAR; interferometric point target analysis
(IPTA); Pakistan
1. Introduction
Ground subsidence is a common geological hazard worldwide, which is mostly linked to natural
(e.g., earthquake, compression of soil, and change in aquifer) or anthropogenic (e.g., underground
construction activities, groundwater extraction) processes [1]. Subsidence at the local scale specifically
in urban areas can be a serious threat to the economy, such as damages to infrastructures (buildings,
roads, bridges, canals), and to viable and sustainable economic development [2]. Changes in geological
settings, mining, construction of subways, and ground water extraction are among the main causes of
land subsidence in most cities in the world [3,4]. Other than these causes, the subsidence showed high
correlation with changing geology in terms of strata lithology, formation, and structure [5]. The areas
with unconsolidated surficial deposits generally form the most prolific aquifers and subsidence in such
areas is mostly due to the extensive extraction of ground water [6]. This extensive use of underground
water resources and increase in the pumping stations due to increase in the population is causing
Remote Sens. 2020, 12, 3442; doi:10.3390/rs12203442 www.mdpi.com/journal/remotesensing
Remote Sens. 2020, 12, 3442 2 of 18
significant loss in small and large aquifers in most parts of the world, creating problems related to
drainage system, flooding during rainy seasons, and the functioning of structures such as canals [6–8].
Numerous events of localized land subsidence have been reported in the past couple of decades
in various parts of the world, especially due to extensive groundwater discharge [9]. Variation in
seasonal timings and change in precipitation patterns have disturbed the runoff and recharge in aquifer
systems. This change in runoff and recharge is also linked with increased demand of water in cities,
which is one of the hurdles in achieving the sustainable goals of any country. Therefore, the demand
for spatio-temporal monitoring of this hazard has increased to take necessary measures and to achieve
sustainable goals.
A number of traditional studies describing different methodologies and effective solutions
are available in the literature to monitor and study the ground deformation/subsidence processes.
These traditional point-based monitoring studies include the following: global positioning system
(GPS), leveling, and geological monitoring methods [10,11]. These methods lack in providing enough
samples for ground-based subsidence monitoring and are very difficult to use in areas surrounded by
steep slopes. Interferometric synthetic aperture radar (InSAR) has been proven to be the most efficient
method, widely used to monitor land subsidence all over the world [1,12,13]. This technique is capable
of detecting small changes at an unprecedented level of spatial details (centimeter to millimeter) in
land surface elevation at low cast under ideal conditions [14–16]. So far, the problem incorporated in
InSAR approach due to change in scatterer with time is mainly due to atmospheric and ionospheric
disturbances, which lead to the introduction of decorrelation in the signal [17,18]. This is a common
problem associated with the repeat-pass InSAR technique as a result of discrepancies that arise between
two related SAR signals over the same location at different epochs [19]. Many advanced InSAR
techniques has been developed to overcome this limitation by using multi-temporal InSAR (MT-InSAR)
techniques [20]. MT-InSAR techniques work on the principal of simultaneously processing multi-SAR
images to accurately extract deformation information. Zhang et al. [21] and Crosetto et al. [22] presented
very good reviews of these techniques. These MT-InSAR techniques have been widely applied to
monitor ground subsidence on different SAR data sets, concluding that these techniques have the
ability to overcome (at least partially) the weaknesses of the conventional InSAR approach [23–25].
In this study, a step-wise and iterative technique, i.e., interferometric point target analysis (IPTA)
multi-baseline technique of persistent scatterer interferometry (PSI), is implemented on Sentinel -1
(4 season × 4 years) data acquired between January 2015 and December 2018 along ascending and
descending orbits in order to investigate, highlight, and understand the causes of subsidence and its
temporal evolution in response to increasing demand of ground water and changes in soil properties
in Abbottabad city of Pakistan (Figure 1). Based on iterative process for calculating high-precision
deformation on point scatterers (PSs), IPTA has been proven to hold strong power in monitoring
deformation using a large number of SAR images [26–29]. The study area has various types of natural
conditions surrounded by mountains and an attractive place thanks to its natural beauty. This is why
the city has experienced rapid urban growth in the past decade. In order to facilitate this increased
urban settlement in the area, the Government of Pakistan (GoP) has implemented various drinking
water supply schemes/projects [30]. As a result of contamination in the surface water and upper level of
groundwater, the need to drill deeper borewells has increased with the increased number of tubewells
in the area. This study is the first ever attempt to examine the spatio-temporal deformation patterns
and their causes in the region. The results obtained by implementing the advanced InSAR technique
will support the local government for better decision making and planning to overcome problems such
as overflowing drains, disturbed sewerage system, sinking land, and littered roads and streets.
Remote Sens. 2020, 12, 3442 3 of 18
Remote Sens. 2020, 12, x FOR PEER REVIEW 3 of 19
Figure
Figure 1. Location map
1. Location map of
of study
study area.
area.
2. Study Area and Datasets
2. Study Area and Datasets
2.1. Characteristics of the Study Area
2.1. Characteristics of the Study Area
Abbottabad, formerly known as “the city of the maple trees” and a famous hill station in the lower
Abbottabad,
Himalayas, formerly known
is the administrative as “the city
headquarters of the
of the maple
Hazara trees”ofand
division a famous
Khyber hill station
Pakhtunkhwa in the
province
lower Himalayas, is the administrative headquarters of the Hazara division of
of Pakistan (Figure 1). Geographically, the study area extends from 34◦ 140 47.0000 N, 73◦ 110 56.0000 EKhyber Pakhtunkhwa
province
to of Pakistan
34◦ 70 46.00 00 N, 73◦ 16(Figure
0 56.0000 1). Geographically,
E. Endowed the and
with scenic study areamountains
green extends from
located 34°14′47.00″
about 125 km N,
73°11′56.00″ E to 34° 7′46.00″ N, 73°16′56.00″ E. Endowed with scenic
north of Islamabad (Capital of Pakistan) through Karakoram Highway, the area is a very famous and green mountains located
about
hill 125 kilometers
resort in summer. north
With of Islamabad
an altitude(Capital
of 1260of mPakistan)
(4120 ft),through
the areaKarakoram
also serves Highway,
as a gatewaythe area
to
is a very famous hill resort in summer. With an altitude of 1260 m (4120 ft), the
Galliyat regions in west. Geologically, the central part of the study area consists of Quaternary Alluvialarea also serves as a
gateway to Galliyat
(unconsolidated regions
surficial in west.
deposits Geologically,
of sand and gravel) the surrounded
central part by of Hazara,
the study area consists
Tanawal, Lokhart, of
Quaternary
and Alluvial (unconsolidated
Hazira formation [31]. surficial deposits of sand and gravel) surrounded by Hazara,
Tanawal,
Being the part of Orash Valley, rainfall[31].
Lokhart, and Hazira formation occurs throughout the year with the highest rainfall during
Being the part of Orash
monsoon seasons, making the region prone toValley, rainfall occurs throughout
flashflood. the year
According withrecent
to the the highest
census rainfall
report,
during
the monsoon
population seasons,
of the city hasmaking the region
increased at a rateprone to flashflood.
of 3.61%/year According
from 1998 to 2017to the recent census
[32].
report, the population of the city has increased at a rate of 3.61%/year from 1998 to 2017 [32].
2.2. Datasets
2.2. Datasets
The selection of Sentinel-1 data was based on the fact that this mission provides long-term,
timelyThe
dataselection of Sentinel-1
with satisfactory data wasfree
resolution based on the
of cost. fact data
These that are
thisamission
reliable provides
source tolong-term,
study the
timely data with
deformation and itssatisfactory
evolution over resolution free ofcan
time, which cost. Thesetodata
be used arefuture
predict a reliable source
scenarios to Therefore,
[33]. study the
deformation and its evolution over time, which can be used to predict future
in this study, we used Sentinel -1A data along the ascending and descending orbits (incident angle scenarios [33]. Therefore,
in this study,
~33.81 and 33.15 we degrees,
used Sentinel -1A data along
respectively). the ascending
Interferometric wideand descending
swath (IW) singleorbits
look (incident
complexangle (SLC)~
33.81 and 33.15 degrees, respectively). Interferometric wide swath (IW)
the terrain observation with progressive scans SAR (TOPSAR) images, operating in C-band (~5.6 cm single look complex (SLC)
the terrain observation
wavelength), acquired from with progressive
European Space scansAgency
SAR (TOPSAR) images, operating
(ESA) distributed in C-bandprogram,
under Copernicus (~5.6 cm
wavelength),
were used to map acquired from distribution
the spatial European Space Agency
of ground (ESA) distributed
deformation and timeunderseries Copernicus
deformationprogram,
patterns.
were used to map the spatial distribution of ground deformation and
The 84 acquired ascending orbit images (track 100) were between 4 January 2015 and 2 December 2018, time series deformation
patterns. The 84 acquired ascending orbit images (track 100) were between 4 January 2015 and 2
December 2018, and the 82 descending orbit images (track 107) were between 17 January 2015 and 27
December 2018. All the acquired images were preprocessed for orbital refinement using precise orbit
Remote Sens. 2020, 12, 3442 4 of 18
and the 82 descending orbit images (track 107) were between 17 January 2015 and 27 December 2018.
All the acquired images were preprocessed for orbital refinement using precise orbit determination
(POD) files released by ESA. Moreover, 1 arc second (~30 m) shuttle radar topography mission (SRTM)
digital elevation model (DEM) was downloaded from United States geological survey (USGS) and used
to simulate and remove topographic phases. For processing and co-registration, the acquired images
on 8 August 2017 for ascending data and 13 December 2016 for descending data were selected as
master images. This selection of the master image was based on the joint correlation method presented
in [34].
Google Earth was used to interpret and analyze the data at different stages. Advanced InSAR
processing software, GAMMA-2017® , developed by GAMMA Remote Sensing AG, Switzerland,
was used to define and implement the IPTA processing chain for the mapping of ground subsidence in
the area.
3. Methodology
The use of the InSAR technique for ground deformation mapping and monitoring depends on
a number of factors, including operational band (C, X, or L), type of incident surface, topography
and geography of the area, number of acquisitions, and temporal intervals between repeated images.
These factors play an important role in achieving high efficiency of the InSAR technique [35]. To achieve
such efficiency of the results, the IPTA approach was employed to analyze and monitor the ground
subsidence in the area. Although the phase model used for point target analysis is the same as that
used in conventional interferometry, its step-wise iterative process is very helpful in refining the
parameters and to separate the deformation phase from all non-deformation phase components of
Equation (1) [36].
ϕki,unw = ϕki,de f o + ϕki,noise + ϕki,topo + ϕki,atm (1)
where ϕki,unw is the unwapped phase of the ith point target in the kth interferogram and is expressed as the
sum of ϕki,atm (atmospheric path delay phase), ϕki,noise (decorrelation phase noise), ϕki,topo (phase residues
due to the digital elevation model (DEM) inaccuracies), and actual ϕki,de f o deformation phase.
The term ϕki,topo is the phase attributed to the errors introduced by DEM as elaborated in Equation (2)
by [35],
k
k
4π Bi,perp
ϕi,topo = ∆ε (2)
λ RSinθ
where ∆ε is the height error (m) increment; Bki,perp is the perpendicular baseline; and λ, R, and θ are
the radar wavelength, slant range, and look angle, respectively.
The term ϕki,de f o is actual deformation phase that can be further divided into linear and non-linear
components [35]. The linear component of this deformation phase is presented in Equation (3).
4π k
ϕki,de f o−lin = t vi (3)
λ
where tk is the time difference of the kth interferogram and vi is the linear deformation velocity at
the ith point target. Moreover, the efficiency of the models and data storage capacities is one of the
main concerns of the researchers working with limited computer resources. The vector format data
structure used in this approach has provided a great benefit to generate results even with the limited
system resources. The overall processing sequence adopted for IPTA processing in this research study
is presented in Figure 2.
Remote
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Figure 2. Processing workflow for interferometric point target analysis (IPTA).
Figure
Figure 2.
2. Processing
Processing workflow
workflow for
for interferometric
interferometric point
point target
target analysis (IPTA).
analysis (IPTA).
3.1. Generation of Point List and Differential Interferograms
3.1. Generation of
3.1. Generation of Point
Point List
List and
and Differential
Differential Interferograms
Interferograms
In order to minimize the contribution of non-deformation phases elaborated in Equation (1),
In
In order
generationorderof to minimize
atogood
minimize
quality the
theof contribution
contribution of
of non-deformation
points is important. non-deformation
In this study, the phases
phases elaborated
elaborated
strategy used toin in Equationgood
Equation
determine (1),
(1),
generation
generation
quality point of a good
of atargets, quality
good quality of points
of points is
i.e., persistent is important.
important.
scatterers In
In this
(PS), this
wasstudy, study,
basedthe the strategy
onstrategy used to
used to determine
two approaches, determine
good
i.e., temporal
good
quality quality
variabilitypoint
andpoint targets,
targets,
spectral i.e., i.e., persistent
persistent
diversity scatterers
[36].scatterers
The ratio (PS), (PS),
of the was was
mean based
based onontwo
(temporal two approaches,
approaches,
average i.e., temporal
i.e., temporal
of backscattering) to
variability
variability
the standard and spectral
anddeviation diversity
spectral diversity [36].
(sigma) of[36]. The ratio
The ratiofrom
backscatter of the mean
of thethis
mean (temporal
(temporal
average average
average
was used of
for of backscattering)
backscattering)
temporal to
to
variability.
the
For standard
the standard deviation an
deviation
spectral diversity, (sigma)
(sigma)
averagedof backscatter
of backscatter
coherencefrom from this
fromthiseach average
average
SLC was wasused
was usedtofor
used for temporal
temporal
select variability.
the PSvariability.
with low
For
For spectral
spectral
spectral diversity,
diversity,
diversity. anan
In order averaged
to havecoherence
averaged coherence
enough from
PS, each
from
the SLC
each
point was used
SLC
targets was to select
used
of both the PS with
thetoapproaches
select the werelowwith
PS spectral
low
merged
diversity.
spectral In order
together.diversity. to have
For theseInpoints,
order theenough
to have PS,
SLC enoughthe
values arepoint targets
PS,extracted
the pointandof both
targets the approaches
of both
written thevector
in the were
approaches merged
data SLC were together.
merged
point data
For these
together.
stack. points,
For
Taking these the
advantage SLCofvalues
points, the
theSLC are extracted
values
long-term are and written
timeextracted
series andthe
data, in maximum
the vector
written data SLC
in thescene
vector datapoint
SLC of
difference data
point stack.
data
three (3)
Taking
stack. advantage
scenesTaking of the
advantagewith
was considered long-term
of the time series
long-term time
perpendicular data, the
series data,
baseline maximum
checkthe scene
of maximum
200 m andscenedifference of three
difference
temporal baseline (3) scenes
of three
check(3)of
was
100 considered
scenesdays with perpendicular
wastoconsidered
generate with perpendicular
interferometric baseline check
Basedofon
pairs.baseline 200
check
themofand 200temporal
baseline m chart baseline
and temporal check
(Figure 3),baseline
theseof 100
PS days
check of
were
to
100generate
days tointerferometric
translated togenerate
generate pairs. Based
interferometric
point-based on the
pairs.
DEM, baseline
Based
leading tochart
on the (Figure
baseline
calculating 3),the
chart these PS were
(Figure translated
3), these
point-based PS wereto
differential
generate
translated point-based
interferogram. DEM, leading to calculating the point-based differential
to generate point-based DEM, leading to calculating the point-based differential interferogram.
interferogram.
Figure 3. Baseline
Figure 3. Baseline vs.
vs. time plots (left) ascending orbit data
data (right)
(right) descending
descending orbit
orbit data.
data.
Figure 3. Baseline vs. time plots (left) ascending orbit data (right) descending orbit data.
3.2. Interferometric Point Target Processing
3.2. Interferometric Point Target Processing
IPTA is basedPoint
3.2. Interferometric on aTarget
2D linear regression model, in which the phase difference between point
Processing
IPTA is based on a 2D linear regression model, in which the phase difference between point
targets is analyzed in the temporal domain. This 2D regression is based on the linear dependency of
IPTA
targets is based in
is analyzed onthe
a 2D linear regression
temporal domain. Thismodel, in which is
2D regression the phase
based ondifference
the linear between
dependencypoint
of
the topographic phase with the perpendicular baseline (Equation (2)) and the linear dependency of
targets is analyzed
the topographic in the
phase temporal
with domain. Thisbaseline
the perpendicular 2D regression is based
(Equation on the linear dependency
(2)) and dependency ofof
the deformation phase with time (Equation (3)). This 2D linear regression was applied to generate
the
the topographic
deformationphasephasewith
withthe perpendicular
time baseline
(Equation (3)). This 2D(Equation (2)) and the
linear regression waslinear dependency
applied of
to generate
initial estimates of deformation phase, residual topography, and phase standard deviation. This phase
the deformation
initial estimates phase with time phase,
of deformation (Equation (3)). This
residual 2D linearand
topography, regression was applied
phase standard to generate
deviation. This
initial
phase estimates of deformation
standard deviation phase,a residual
represented topography,
quality check betweenand phase standard
the model deviation.phase.
fit and differential This
phase standard deviation represented a quality check between the model fit and differential phase.
Remote Sens. 2020, 12, 3442 6 of 18
standard deviation represented a quality check between the model fit and differential phase. In addition
to these terms, the phase model also generated the linear regression phase residual, which was comprised
of phase variations related to atmospheric artifacts as well as non-linear deformation phase component
with decorrelation noise (Equation (4)).
ϕki,res = ϕki,non−lin + ϕki,atm + ϕki,noise (4)
The residual phase at this stage exhibited phase jumps related to unwrapping errors that were
removed iteratively using the minimum cost flow (MCF) algorithm [37]. Because atmospheric phase
screen (APS) and non-linear deformation phases are spatial low-pass signals, we applied the linear least
square spatial filtering method to the unwrapped residual phase in order to calculate the phase attributes
related to APS. The estimated APS is then subtracted from the point-based differential interferogram
stack for all of the PS candidates. As presented in Figure 2, this process was iterated several times to
generate improved quality estimates of the height correction, APS, and refined unwrapped differential
phase. More technical details on processing strategies using the IPTA framework can be found
in [36,38].
3.3. Deformation Rate and Time Series Retrieval
The final deformation rate and deformation time series histories were retrieved for each point by
implementing the multi-baseline (mb) approach [39]. These final deformation histories and average
annual deformation rates corresponding to point information are converted to line of sight (LOS)
displacement and equiangular (EQA) projection for further analysis.
3.4. Decomposition of LOS Displacements into 2D Displacement Fields
The mean LOS velocity fields against each PS, extracted from two different orbits, i.e., ascending
and descending, were decomposed into vertical and east–west components. Assuming the negligible
north–south movement [40], the vertical (dv ) and east–west (dh ) components were computed using
Equation (5) [41,42].
dasc asc sinθasc
! ! !
los
cosθ cos∆α d v
= (5)
ddsc
los
cosθdsc sinθdsc dh
where θasc and θdsc represent the incident angles of ascending and descending orbits, respectively,
and ∆α is the difference between headings of ascending and descending orbits.
3.5. Causal Factors of Deformation
The cause of the subsidence is normally considered and interpreted as an individual/single factor,
but urban subsidence especially in areas surrounded by hills with variety of geological units may be
caused by the interaction of two or more factors together. This interaction between causal factors
is very clear and reported in many studies [43]. If changes in such casual factors are left unnoticed,
then the subsidence can lead to significant disaster in the area. Abbottabad, being one of the major
affected cities in the October 2005 earthquake, has attracted a number of researchers for several reasons.
One reason is its location in an intermountain basin with thick Quaternary deposits. Apart from the
number of causal factors of subsidence, we gathered data about natural and anthropogenic factors that
influence land subsidence. Geological layers (Figure 4) were extracted from the map of Geological
Survey of Pakistan (GSP) [44] and refined using the map published in [31].
Remote Sens. 2020, 12, 3442 7 of 18
Remote Sens. 2020, 12, x FOR PEER REVIEW 7 of 19
Figure 4. Geological
Geological map of the study area.
Precipitation data were gathered from Kakul Station of Pakistan Meteorological Department
4. Results
(PMD) from the year 2015 to 2018. Moreover, information related to the increase in drinking water
The criteria for the generation of interferometric pairs on the basis of multi-baseline can
supply schemes was collected from various reports [45–47] and compiled for the analysis. Because of
guarantee that all of the Sentinel 1A images are involved. These interferometric pairs were assessed
the unavailability of ground water discharge data at these water supply schemes, the analysis with
by applying a standard two-pass D-InSAR algorithm to generate differential interferograms. During
ground water discharge was done with the help of the implemented plans of water supply under such
D-InSAR processing, it was observed that the interferograms with relatively longer temporal
schemes. The pattern of subsidence and the locations of high subsidence zones were compared and
intervals showed the phase variations in some part of the study area. The phase variations could be
analyzed with these developments in the area.
related to topographic residuals and perpendicular baselines. Such phase variation cannot be
categorized
4. Results to a specific phase signal unless multiple D-InSAR products based on time series data are
analyzed. For this purpose, IPTA was employed in Abbottabad city and adjacent surrounding areas
The criteria
to extract for theinformation.
deformation generation of interferometric pairs on the basis of multi-baseline can guarantee
that all of the Sentinel 1A images are involved. These interferometric pairs were assessed by applying
a standard
4.1. Average two-pass
SubsidenceD-InSAR
Rate Mapalgorithm to generate differential interferograms. During D-InSAR
processing, it was observed that the interferograms with relatively longer temporal intervals showed
Figurevariations
the phase 5 shows the in average
some part velocities in cm per
of the study area.year
Thealong LOS
phase directionscould
variations of both
be ascending
related to
(left) and descending (right) data, derived by implementing the IPTA technique.
topographic residuals and perpendicular baselines. Such phase variation cannot be categorized These LOS resultsto
were geocoded in WGS 84 coordinate system and superimposed onto the shaded
a specific phase signal unless multiple D-InSAR products based on time series data are analyzed. relief map of the
study
For this area. Color IPTA
purpose, rampswasfrom blue to red
employed represent the
in Abbottabad movement
city of land
and adjacent along the areas
surrounding LOS direction.
to extract
The negative deformation
deformation information. values indicate the movement away from the sensor (i.e., subsidence) and
positive deformation values are related to movement towards the sensor (i.e., uplift). Owing to lower
positive values
4.1. Average (FigureRate
Subsidence 5), Map
it can be assumed that there is no movement towards the sensor (i.e.,
uplift); therefore, the term “deformation” is represented as “subsidence” in this research paper. It can
Figure 5 shows the average velocities in cm per year along LOS directions of both ascending (left)
be seen in Figure 5 that the results extracted from both orbits’ data exhibit similar spatial patterns.
and descending (right) data, derived by implementing the IPTA technique. These LOS results were
These similar patterns represent the presence of dominant vertical deformation and negligible
geocoded in WGS 84 coordinate system and superimposed onto the shaded relief map of the study area.
horizontal velocity [42].
Color ramps from blue to red represent the movement of land along the LOS direction. The negative
The results of average vertical velocity obtained after decomposing LOS velocities of both orbits
are shown in Figure 6. It was observed in Figure 6 that the averaged vertical deformation (subsidence)
rate varies up to −6.5 centimeter (cm) per year in the area. Figure 6 also represents a prominent, un-
Remote Sens. 2020, 12, 3442 8 of 18
deformation values indicate the movement away from the sensor (i.e., subsidence) and positive
deformation values are related to movement towards the sensor (i.e., uplift). Owing to lower positive
Remote Sens. 2020, 12, x FOR PEER REVIEW 8 of 19
values (Figure 5), it can be assumed that there is no movement towards the sensor (i.e., uplift); therefore,
the term “deformation” is represented as “subsidence” in this research paper. It can be seen in Figure 5
even subsidence pattern and the most prominent pattern with values from −6.5 to −2 cm/year was
that the results extracted from both orbits’ data exhibit similar spatial patterns. These similar patterns
identified along the old Karakoram highway (locally known as road Nowshera-Abbottabad road,
represent the presence of dominant vertical deformation and negligible horizontal velocity [42].
N35), which is settled in the foothills of the Himalayas, including the cantonment area of the city.
Figure
Figure 5.
5. Average
Average line
line of
of sight
sight (LOS)
(LOS) velocity
velocity maps:
maps: (a)
(a) ascending
ascending and
and (b)
(b) descending
descending orbits’
orbits’ data.
data.
Moreover,
The resultsFigure 6 also
of average represents
vertical three
velocity main subsidence
obtained regions, i.e.,
after decomposing LOSA,velocities
B, and C.ofAboth
andorbits
B are
the regions with high population density and exhibit higher subsidence rates, whereas
are shown in Figure 6. It was observed in Figure 6 that the averaged vertical deformation (subsidence)region C falls
into
rate the medium
varies up to to lowcentimeter
−6.5 subsidence(cm)
region
perwith
yearainrelatively
the area.scattered
Figure 6population. The subsidence
also represents a prominent,in
region A incorporates residential societies of Hassan town, Amir alam awan town.
un-even subsidence pattern and the most prominent pattern with values from −6.5 to −2 cm/year was The subsidence
varies from
identified −6.5the
along cm/year to −0.5 cm/year
old Karakoram highwayin this region.
(locally knownRegion B lies
as road in Mir Alam Town and
Nowshera-Abbottabad road,Jhangi
N35),
area
which with a higher
is settled centered
in the value
foothills of −6.5
of the cm/yearincluding
Himalayas, up to −1 cm/year at the outer
the cantonment edges
area of of the region.
the city.
Region C is the northern part of the main city, and lies in Kaghan and Sir Syed Colony with relatively
higher altitudes than regions A and B. The subsidence rate varies between −3.0 and −1 cm per year in
this region.
Remote Sens. 2020, 12, 3442 9 of 18
Remote Sens. 2020, 12, x FOR PEER REVIEW 9 of 19
Figure 6. Meanvertical
6. Mean verticalvelocity
velocity map
map in in cm/year.
cm/year. TheThe
red red color
color represents
represents downward
downward movement
movement (i.e.,
(i.e., subsidence).
subsidence).
Moreover,Time
4.2. Subsidence Figure 6 also represents three main subsidence regions, i.e., A, B, and C. A and B are
Series
the regions with high population density and exhibit higher subsidence rates, whereas region C falls
Themedium
into the spatio-temporal evolution region
to low subsidence in the deformation pattern
with a relatively using population.
scattered ascending orbit
The data at six (6)
subsidence in
different stages overlaid on averaged multi-looked intensity (MLI) image in RADAR
region A incorporates residential societies of Hassan town, Amir alam awan town. The subsidence geometry is
shown in Figure 7. Analyzing the increasing and expanding trend of the deformation
varies from −6.5 cm/year to −0.5 cm/year in this region. Region B lies in Mir Alam Town and Jhangi in the
eastward/westward and southward/westward
area with a higher centered directions,
value of −6.5 cm/year up to −1respectively, four
cm/year at the typical
outer edgesPSof(P1,
the P2, P3,
region.
and P4) were selected for detailed regional time series analysis (Figure 8a–e). Time series trends
Region C is the northern part of the main city, and lies in Kaghan and Sir Syed Colony with relatively show
the deformation
higher evaluation
altitudes than regionsextracted
A and B. using ascendingrate
The subsidence datavaries
and scattered at different
between −3.0 and −1 locations
cm per yearover
in
the
thisdeforming
region. area. The locations of these points are shown in Figure 8a.
4.2. Subsidence Time Series
The spatio-temporal evolution in the deformation pattern using ascending orbit data at six (6)
different stages overlaid on averaged multi-looked intensity (MLI) image in RADAR geometry is shown
in Figure 7. Analyzing the increasing and expanding trend of the deformation in the eastward/westward
and southward/westward directions, respectively, four typical PS (P1, P2, P3, and P4) were selected
for detailed regional time series analysis (Figure 8a–e). Time series trends show the deformation
Remote Sens. 2020, 12, 3442 10 of 18
evaluation extracted using ascending data and scattered at different locations over the deforming area.
The locations of these points are shown in Figure 8a.
Based on LOS deformation obtained using ascending data, the temporal variations in the
subsidence values of P1 vary from 0 to −25 cm, with an average rate of −6.63 cm/year. P2, which lies
in the upper part of subsidence zone A, exhibits an average rate of −5 cm/year and the trend varies
from 0 to −18 cm. P3, which lies in the upper part of subsidence zone B, varies from 0 to −16 cm,
with an average rate of −4.3 cm/year. P4, which lies in northern part of study area and in the center of
subsidence zone C, shows lower values varying from 0 to −12 cm, with an average rate of −3 cm/year.
The temporal variations of these points are shown altogether in Figure 8b–e. These variations show
a non-linear trend in the subsidence. The variations in time series patterns show that deformation
slows down and is sustained for a certain period of time. One of the possible reasons for this variation
could be the seasonal changes in the underground water levels, particularly after the monsoon season
every Sens.
Remote year.2020, 12, x FOR PEER REVIEW 10 of 19
Figure
Figure 7.
7. SixSix
different stages
different of of
stages cumulative landland
cumulative subsidence pattern
subsidence in RADAR
pattern in RADARgeometry. The
geometry.
background image is the averaged intensity image of the study area. One color cycle corresponds
The background image is the averaged intensity image of the study area. One color cycle corresponds to
10 cm/year
to 10 displacement.
cm/year displacement.
Based on LOS deformation obtained using ascending data, the temporal variations in the
subsidence values of P1 vary from 0 to −25 cm, with an average rate of −6.63 cm/year. P2, which lies
in the upper part of subsidence zone A, exhibits an average rate of −5 cm/year and the trend varies
from 0 to −18 cm. P3, which lies in the upper part of subsidence zone B, varies from 0 to −16 cm, with
an average rate of −4.3 cm/year. P4, which lies in northern part of study area and in the center of
subsidence zone C, shows lower values varying from 0 to −12 cm, with an average rate of −3 cm/year.
The temporal variations of these points are shown altogether in Figure 8b–e. These variations show
a non-linear trend in the subsidence. The variations in time series patterns show that deformation
slows down and is sustained for a certain period of time. One of the possible reasons for this variation
could be the seasonal changes in the underground water levels, particularly after the monsoon season
every year.Remote Sens. 2020, 12, 3442 11 of 18
Remote Sens. 2020, 12, x FOR PEER REVIEW 11 of 19
Figure8.8. Time
Figure Time series
seriesevaluation
evaluationofofaveraged
averagedLOS deformation
LOS presented
deformation using
presented ascending
using data:data:
ascending (a)
location of PSs, (b) P1, (c) P2, (d) P3, and (e) P4.
(a) location of PSs, (b) P1, (c) P2, (d) P3, and (e) P4.
5.5.Discussion
Discussionand
andAnalysis
Analysis
Beingpart
Being partofofthethe valley
valley andand foothills,
foothills, the exhibits
the city city exhibits
heavyheavy flash floods.
flash floods. SeveralSeveral
drainage drainage
systems
systems
were were introduced
introduced in the areaintothe
moveareathetoflooded
move the flooded
water fromwater
the cityfrom thenearby
to the city to river
the nearby
channels river
via
channels via Darkhan Katha into Dor River. With the passage of time, the situation
Darkhan Katha into Dor River. With the passage of time, the situation of flooded and standing water in of flooded and
standing
the water in the
city is becoming more city is becoming
severe, more severe,
which results which the
in paralysing results
city in paralysing
with theespecially
traffic jams, city with traffic
during
jams, especially
rainfall seasons [48]. during rainfall
To better seasons [48].
understand To betterthe
this scenario, understand
subsidence this scenario,
profiles alongthetwosubsidence
transects,
profiles
west along
to east (W–E)twoandtransects,
south towest to east
north (S–N),(W–E)
wereand south to
analyzed. northobserved
It was (S–N), werethat analyzed.
the magnitude It wasof
observed that the magnitude of LOS subsidence along these transects
LOS subsidence along these transects decreases in value while moving from W–E or S–N, keeping decreases in value while
the
moving from W–E or S–N, keeping the maximum values in the centers of the
maximum values in the centers of the transects and causing a bowl-shaped profile, particularly along transects and causing
a bowl-shaped
the W–E transect, profile, particularly
and some alonginthe
major dips theW–E transect,profile
subsidence and somealongmajor dips transect
the S–N in the subsidence
(Figure 9).
The comparison of these subsidence profiles with the actual ground elevation profileswith
profile along the S–N transect (Figure 9). The comparison of these subsidence profiles canthe actualin
be seen
ground
Figure 9. elevation profiles
It is clear from can 9bethat
Figure seen in Figure
these 9. It is regions
bowl-shaped clear from Figure 9 that
of subsidence these
zones bowl-shaped
in this part of the
regions of subsidence zones in this part of the city are basically responsible for the standing waterRemote Sens. 2020, 12, 3442 12 of 18
Remote Sens. 2020, 12, x FOR PEER REVIEW 12 of 19
city are basically responsible for the standing water during the rainfall season, limiting human activity;
navigation;
during the and severe
rainfall destruction
season, limitingtohuman
roads, streets,
activity;and buildings,and
navigation; making them
severe prone to to
destruction seepage
roads,
as well. and buildings, making them prone to seepage as well.
streets,
Figure9.
Figure 9. Subsidence
Subsidence profile
profile along
alongthe
theS–N
S–Nand
andW–E
W–Etransects.
transects.
In
Ingeneral,
general,most
most subsidence
subsidence areas
areas inin Abbottabad
Abbottabad belong
belong toto residential
residential area
area and commercial area.
The
The subsidence
subsidence inin these
these areas
areas isis of
of course
course due
due to
to some
some underground
underground activities
activities related
related toto various
various
anthropogenic (e.g., ground water withdrawal) and natural (e.g., soil consolidation)
anthropogenic (e.g., ground water withdrawal) and natural (e.g., soil consolidation) processes. processes. In most
In
cases, the land
most cases, thesubsidence patternpattern
land subsidence represents an integrated
represents effect of
an integrated bothofofboth
effect theseoffactors. In suchIncases,
these factors. such
the anthropogenic
cases, factors act
the anthropogenic as a speed
factors act as up tool forupthe
a speed naturally
tool for theoccurring
naturallyevents suchevents
occurring as subsidence
such as
and degradation. Because of the increase in population with time, this subsidence
subsidence and degradation. Because of the increase in population with time, this subsidence and and degradation
can be relatedcan
degradation to the increase
be related tointhethe demand
increase of the
in the underground
demand natural resources
of the underground natural (water discharge).
resources (water
The detailed relationships of land subsidence with the categorized factors are discussed
discharge). The detailed relationships of land subsidence with the categorized factors are discussed below.
below.
5.1. Soil Consolidation
5.1. Soil Consolidation soil is postulated as a primary driver of land subsidence in most of the major
Unconsolidated
cities Unconsolidated
and areas of the world
soil is[6]. Figure 4 as
postulated shows that most
a primary of the
driver of central part of the in
land subsidence study
mostarea
of is
thelocated
major
in alluvial sediments with grey brown shale and minor limestone in the west;
cities and areas of the world [6]. Figure 4 shows that most of the central part of the study areadolomite, dark grey
is
shale, light grey medium to thick bedded limestone in the south; and dolomite limestone
located in alluvial sediments with grey brown shale and minor limestone in the west; dolomite, dark comprised of
sandstone
grey shale, and shale
light in the
grey north [31].
medium Figure
to thick 10 shows
bedded the relationship
limestone between
in the south; andthese geological
dolomite units
limestone
and averageof
comprised vertical subsidence
sandstone rates.
and shale in It
thecan be observed
north in Figure
[31]. Figure 10 shows10 that
themost of the subsidence
relationship area
between these
belongs to unconsolidated deposits (alluvial surfaces).
geological units and average vertical subsidence rates. It can be observed in Figure 10 that most of
Keeping in area
the subsidence viewbelongs
the importance of unconsolidated
to unconsolidated depositsdeposits,
(alluvialwhich makes mattresses of aquifers,
surfaces).
the three-layered structure analysis as presented by [46] showed that the first layer is comprised of clay
and silt along the inter-beds of gravel, with a thickness of 30 to 40 m in the west and 70 to 80 m in the
central part of the subsidence area; the second layer majorly consists of gravel with a conspicuously
increased thickness of about 40 m in the center and southern part of the subsidence area; and the
third layer of the unconsolidated soil in the region is underlying bedrock, represented by shale in
the west and dolomite and limestone in the east. The thickness of the second layer increases while
moving in a westerly direction along the transect W–E, which follows exactly the western extent of
the subsidence region. This structural analysis showed a strong correlation with the overall extent
subsidence. Although most of the land subsidence occurred in alluvium deposits, the direct correlation
between this type of soil with subsidence may not be solely possible, but the direct correlation of this
type of geological unit with the existence of aquifer and its exploitation (changing the unconsolidatedRemote Sens. 2020, 12, 3442 13 of 18
surface to consolidated surface) could provide a better understanding of the land subsidence process
in this populated part of the city.
Remote Sens. 2020, 12, x FOR PEER REVIEW 13 of 19
Figure 10.
Figure 10. Relationship
Relationship between
between geological
geological units
units and
and average
average subsidence
subsidence rate.
rate.
5.2. Effect
Keepingof Ground
in view Water Withdrawal of unconsolidated deposits, which makes mattresses of aquifers,
the importance
the three-layered
Anthropogenic structure analysis
factors mostly as presented
include by [46]development,
infrastructure showed that the first activities,
mining layer is comprised
and ground of
clay and silt along the inter-beds of gravel, with a thickness of 30 to 40 m
water exploitation. Abbottabad city and the surrounding area are mostly dependent on surfacein the west and 70 to 80 m
in theand
water central
ground part of the
water. Thesubsidence
increase inarea; the second layer
the contamination majorly
of water due to consists
mixingof gravel with
of minerals froma
conspicuously
surrounded increased
hills thickness
was bringing of aboutdiseases
water-borne 40 m in into
the center and southern
the community part of themore
and becoming subsidence
severe
area; and the third layer of the unconsolidated soil in the region is underlying
with time [49]. In order to handle this situation, Government bodies implemented a number of safe bedrock, represented
by shale water
drinking in the schemes
west andindolomite
the area. and
Onelimestone
of the majorin the
andeast.
mostThe thickness
recent schemes of was
the aided
secondbylayer
the
increases while moving in a westerly direction along the transect
Japanese Government and implemented by Japan International Cooperation Agency (JICA) W–E, which follows exactlyafter
the
western extent of the subsidence region. This structural analysis showed a strong
conducting a survey in 2009 [46]. Under this project, combined use of surficial and underground water correlation with the
overall
was extent subsidence.
proposed by repairingAlthough most of the
the old tubewells andland subsidence
building occurred ininalluvium
new tubewells the areasdeposits,
with densethe
direct correlation between this type of soil with subsidence may not be solely
population. For this purpose, a network of water supply lines connecting surface water reservoirspossible, but the direct
correlation
and tubewells of this
wastype of geological
developed unit
(Figure with
11), the existenceand
implemented, of aquifer
handed and its to
over exploitation (changing
the Government in
the unconsolidated
October 2015 [50]. surface to consolidated surface) could provide a better understanding of the land
subsidence processthe
By comparing in this populated
subsidence part
of the of with
area the city.
the existing and implemented water supply scheme,
it can be seen in Figure 9 that the crests along profiles W–E and S–N belong to the locations of tubewells.
5.2. Effect of Ground Water Withdrawal
Similarly, it can be seen in Figure 11 that the extent and pattern of the subsidence zone follow the
Anthropogenic
distributed locations offactors mostly include The
tubewells/boreholes. infrastructure development,
edges of subsidizing zones mining activities,
are at relatively and
higher
ground water
altitudes than theexploitation.
central partAbbottabad
of the citycity
andand the the
follow surrounding
locations ofarea are tubewells
other mostly dependent on
in this area.
surface
As waterinand
elaborated ground
Section water.
5.1, the Theinincrease
aquifers the study inarea
the are
contamination of water
identified in the due
first and to mixing
second layers ofof
minerals
the from surrounded
underground hills wasinbringing
soil and groundwater water-borne
these aquifers moves withdiseases into
varying the level
water community
from 1190and to
becoming
1210 m mean more severe
sea level with therefore,
(M.S.L); time [49]. In order
it was to handle
emphasized by thethis
JICAsituation,
team duringGovernment
the handing bodies
over
implemented
of the project toa number
monitor of thesafe drinking
water water
discharge in schemes in the major
order to avoid area. One of issues,
future the major and
such as most recent
subsidence
schemes
in the area.was
The aided
increasebyof the Japanese
3.5 percent Government
population per year and implemented
since 1999 in 2017,by Japan an
including International
increase of
Cooperation
17 percent from Agency
2009 to(JICA)
2015 after conductingincreased
[47], ultimately a survey thein 2009 [46]. Under
drinking this project,
water demand combined
in the area. use
of surficial and underground water was proposed by repairing the old tubewells and building new
tubewells in the areas with dense population. For this purpose, a network of water supply lines
connecting surface water reservoirs and tubewells was developed (Figure 11), implemented, and
handed over to the Government in October 2015 [50].Remote Sens. 2020, 12, 3442 14 of 18
Remote Sens. 2020, 12, x FOR PEER REVIEW 14 of 19
Figure 11. Location
Figure of tubewells
11. Location and and
of tubewells supply lineslines
supply overlaid on average
overlaid vertical
on average velocity
vertical map.map.
velocity
By comparingthe
Nevertheless, thearea
subsidence
of higher of the area rates
subsidence withagrees
the existing
well withandthe implemented
tubewell in the water
study supply
area;
scheme,
the it can bemostly
deformation seen in Figure
started 9 that
with the crestsincrease
an excessive along profiles
of waterW–E and S–N
pumping from belong to thetubewells
developed locations
of tubewells.
during Similarly, itperiod.
the investigating can be seenOne in of Figure
the other11 possibilities
that the extent of and pattern of the
this subsidence subsidence
could zone
be the water
follow the distributed locations of tubewells/boreholes. The edges of
leakage problem in the underground pipes, as there have been more than 800 different cases reported subsidizing zones are at
relatively higher
regarding altitudes
water leakage than in
issues thethe
central
area. part of the city
Moreover, andconnections
illegal follow the locations of other tubewells
and uncontrolled pumping
in thiscould
hours area. Asalsoelaborated
be responsiblein Section
for the5.1, the aquifers
changing waterintable
the study
in the area
area.are identified in the first and
second layers to
In order of verify
the underground
the cause of soil and
this groundwater
change in these
in the area, aquifers moves
we analyzed with varying
the temporal water
correlation
level from
between 1190 to 1210
IPTA-InSAR m mean
derived time sea
serieslevel (M.S.L); at
subsidence therefore,
investigatedit was
PSs,emphasized by and
i.e., P1, P2, P3, the P4,
JICAandteam
the
during the handing
precipitation (Figureover12). ofThe
thecollected
project toprecipitation
monitor the water
data atdischarge
the nearby in order
Kakultostation
avoid (the
major future
location
issues,
of such asissubsidence
the station shown in Figure in the 11)
area. The increase
showed a strong of correlation
3.5 percentwith
population
time seriesper year
trendsince 199912).
(Figure in
2017,
The including
seasonal an increase
variation of 17 percent
in the ground from 2009 to
water particularly 2015
after [47], ultimately
monsoon rainfall (Juneincreased
throughthe drinking
September)
water demand
justifies the causein of
thethe
area.
subsidence in the area. The monsoon rainfall refills the aquifers, balancing the
Nevertheless,
underground waterthe area of higher
discharge subsidence
and stabilizing rates
the agrees
process ofwell with the This
subsidence. tubewell in the
clearly study area;
demonstrates
deformation
the process mostly
and cause of started
subsidence withinan theexcessive
study area.increase
Zhangofetwater
al. [51]pumping
and Gallowayfrom developed
et al. [52]
tubewells during the investigating period. One of the other possibilities of
showed a similar relationship and joint effect of natural and anthropogenic conditions with subsidence.this subsidence could be
the water leakage
Moreover, problem in
the identification of the
highunderground pipes, as there
subsidence particularly in thehave been more
peripheries than 800 locations
of tubewell different
cases reported
showed regarding
a good ability water1A
of Sentinel leakage
data and issues in the
the IPTA area. Moreover,
approach illegal connections
for land subsidence mapping in and this
uncontrolled
part pumping hours could also be responsible for the changing water table in the area.
of the region.
In order to verify the cause of this change in the area, we analyzed the temporal correlation
between IPTA-InSAR derived time series subsidence at investigated PSs, i.e., P1, P2, P3, and P4, and
the precipitation (Figure 12). The collected precipitation data at the nearby Kakul station (the locationbalancing the underground water discharge and stabilizing the process of subsidence. This clearly
demonstrates the process and cause of subsidence in the study area. Zhang et al. [51] and Galloway
et.al. [52] showed a similar relationship and joint effect of natural and anthropogenic conditions with
subsidence. Moreover, the identification of high subsidence particularly in the peripheries of
Remote Sens. 2020,
tubewell 12, 3442showed a good ability of Sentinel 1A data and the IPTA approach for
locations 15 land
of 18
subsidence mapping in this part of the region.
Figure 12.
Figure 12. Time
Time series
series LOS
LOS subsidence
subsidence of
of PS
PS points
points P1,
P1, P2,
P2, P3,
P3, and
and P4
P4 versus
versus daily
daily precipitation
precipitation at
at
Kakul Station.
Kakul Station.
6.
6. Conclusions andFuture
Conclusion and FutureWork
Work
In
In this
this study,
study,thethemulti-temporal
multi-temporalInSAR InSARapproach
approachof ofIPTA
IPTAwas wasemployed
employedon on multi-track
multi-track Sentinel
Sentinel
1A
1ATOPSAR
TOPSARimages images collected
collectedbetween
betweenJanuary 2015 2015
January and December
and December 2018 to2018
analyze the spatio-temporal
to analyze the spatio-
distribution and trendand
temporal distribution of subsidence in Abbottabad
trend of subsidence City and
in Abbottabad theand
City surrounding
the surroundingarea. Step area.by step
Step by
processing
step processing chainchain
of iterative IPTA IPTA
of iterative approach was employed
approach was employed and the andcauses of the of
the causes subsidence were
the subsidence
investigated
were investigated by analyzing the relationship
by analyzing between natural
the relationship between(soil consolidation) and anthropogenic
natural (soil consolidation) and
factors (ground factors
anthropogenic water extraction)
(ground water in detail. The average
extraction) subsidence
in detail. The average rate subsidence
map showed that
rate maptheshowed
central
part
that ofthethe subsiding
central part ofarea,
thewhich is close
subsiding to which
area, Karaokram highway
is close and cantonment,
to Karaokram highway and including major
cantonment,
localities such as Hassan town, Amir Alam Awan town, Mir alam town,
including major localities such as Hassan town, Amir Alam Awan town, Mir alam town, and Jhangi and Jhangi Area, is sinking
at a maximum
Area, is sinking rate
at of ~6.5 cm/year,
a maximum ratevarying
of ~6.5 from different
cm/year, varyingratesfrom
up todifferent
1 cm/year. ratesTimeup series history
to 1 cm/year.
graphs
Time seriesshowed a close
history correlation
graphs showed with the rainfall
a close during
correlation the investigation
with the rainfall during periodthe andinvestigation
subsidence
profiles
period and alongsubsidence
the W–E and S–N transects
profiles along theshowed
W–E and varying
S–N crests
transectsalong the transects
showed varying that are related
crests along theto
the locations
transects thatofare
tubewells.
related to Thetheoverall pattern
locations of the subsidence
of tubewells. The overallwas investigated,
pattern of theand it was found
subsidence was
that it follows the development made for providing safe drinking water
investigated, and it was found that it follows the development made for providing safe drinking to the community under a
recently
water tocompleted
the community projectunder
of JICA. The aquifer
a recently in this part
completed of the
project Abbottabad
of JICA. basin in
The aquifer is decreasing
this part ofasthe a
result of extensive
Abbottabad basinwater dischargeasina recent
is decreasing result years, resulting
of extensive in the
water consolidation
discharge of soil,
in recent further
years, leading
resulting in
to
thethe creation of several
consolidation local problems
of soil, further leading to in the
thecreation
area. Building
of several dikes/bowls
local problemsafter rainfall
in the area.or flood are
Building
ultimate
dikes/bowls responses
after to the subsidence
rainfall or flood processes
are ultimate and responses
the concerned to thedepartments
subsidence were unawareand
processes of this
the
phenomenon in the studywere
concerned departments area.unaware
This study of highlights the first ever
this phenomenon in the evidence
study area.of land
Thissubsidence and its
study highlights
causes
the firstinever
the region,
evidence and ofthe
land results obtained
subsidence andbyitsimplementing
causes in the the advanced
region, and the InSAR
results technique
obtainedcan by
provide support to the local government as well as decision and policy makers for better decision
making and planning to overcome problems such as availability of drinking water, overflowing drains,
sewage system, littered roads/streets, and sinking land in this part of the city.
Because in situ observations were not available, some decorrelation noises may be present in the
final deformation maps, but they have been greatly minimized during 2D regression quality checks
at each iteration. Therefore, the LOS deformation rates generated for each point target are basically
reliable for mapping the land subsidence in the area, and showed consistency in the results of ascendingYou can also read
