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Characterisation and mapping of land subsidence based on geodetic
observations in Lagos, Nigeria
Article in Geodesy and Geodynamics · March 2020
DOI: 10.1016/j.geog.2019.12.006
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Geodesy and Geodynamics 11 (2020) 151e162
Contents lists available at ScienceDirect
Geodesy and Geodynamics
journal homepage: http://www.keaipublishing.com/geog
Characterisation and mapping of land subsidence based on geodetic
observations in Lagos, Nigeria
Femi Emmanuel Ikuemonisan*, Vitalis Chidi Ozebo
Department of Physics, Faculty of Science, University of Lagos, Akoka, Lagos, Nigeria
a r t i c l e i n f o
a b s t r a c t
Article history:
Received 22 July 2019
Accepted 3 December 2019
Available online 25 March 2020
The pervasive seasonal flooding, aquifer contamination, and saline water intrusion in parts of Lagos are
some of the long-term effects of land subsidence caused by the excessive groundwater exploitation and
land reclamation that has been taking place in the city. Efforts to monitor the extent and pattern of land
deformation will help in many ways to mitigate the effects of flooding and other geohazards associated
with land subsidence. In this study, we characterised and mapped the land subsidence in the Lagos city
based on the analyses of geodetic data, which included Global Positioning Satellite (GPS), Envisat,
Sentinel-1, and GRACE data. We applied the SBAS technique to the Envisat and Sentinel-1 datasets acquired from 2004e2011 and 2015e2019, respectively, and to perform multi-temporal analyses and
produce corresponding subsidence maps over the Lagos city. The GRACE data were used to infer the
extent and trend of groundwater changes at the GPS location. The results indicate that the subsidence is a
widespread phenomenon in Lagos city, with subsidence rates varying between 2 mm/year and
87 mm/year. The highest subsidence rate was observed around the coastal zones and areas where
heavy structures are built on landfills. With the highest rate at present, subsidence has gradually
increased in the last 15 years. With the development of indiscriminate groundwater exploitation, urbanization, and rapid population growth, the subsidence rate in Lagos city is likely to rise significantly in
the coming years, which, in turn, may further escalate the flood rate and other associated geohazards.
© 2020 Institute of Seismology, China Earthquake Administration, etc. Production and hosting by Elsevier
B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY-NC-ND
license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords:
InSAR
P-SBAS
Deformation time series
Land subsidence
Lagos
1. Introduction
Land subsidence is a form of land deformation that may result
from many natural and anthropogenic processes, and involves
the relative sinking of the Earth's surface. For example, excessive
withdrawal of groundwater from an aquifer system [1],
compaction of unconsolidated sediments [2], reduction of pore
pressure within an aquifer system [3,4], and excessive injection
of wastewater into underground reservoirs [5] are some of these
processes. Other factors that can cause land subsidence include
* Corresponding author.
E-mail address: femi.ik@yahoo.com (F.E. Ikuemonisan).
Peer review under responsibility of Institute of Seismology, China Earthquake
Administration.
Production and Hosting by Elsevier on behalf of KeAi
poor drainage system, decomposition of organic soil, underground mining, oil and gas extraction [6] and impoundment of
large underground reservoirs [7]. Coastal cities are mostly
vulnerable to land subsidence because the dense population in
those areas often takes advantage of the existing natural resources and modifies the elevation [1]. Recent studies concerning land deformation have shown that many worldwide coastal
cities are undergoing rapid land subsidence with an increase in
the global mean sea level at a rate of about 2 mme3 mm
annually [8,9]. Although the high concentration of people in
coastal cities brings many economic advantages, such as
enhanced transportation networks, industrial and urban development, and improved income bases from tourism, fishing, and
lumbering, the combined effects of the rapid population growth
and urbanization also have negative impacts on the ecological
systems that provide such economic advantages [10]. For many
years, like many other coastal cities around the world, Lagos has
been subjected to the widespread land subsidence of both natural and anthropogenic origins [11,12]. And it has been suffering
https://doi.org/10.1016/j.geog.2019.12.006
1674-9847/© 2020 Institute of Seismology, China Earthquake Administration, etc. Production and hosting by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is
an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
152
F.E. Ikuemonisan, V.C. Ozebo / Geodesy and Geodynamics 11 (2020) 151e162
drastic losses of its natural coastal barriers, deltaic wetlands and
barrier islands, with increasing flood risk across the city [13,14].
Land subsidence induced by over-extraction of groundwater in
Lagos has significantly increased since the early 1990s, when the
population of the city began to grow rapidly, increasing percentages of the population relying on groundwater for both
domestic and industrial uses [15,16]. The population growth of
Lagos is exceeding the ability of urban planning agencies to
enforce necessary regulations on groundwater exploitation [17],
with the current water demand-supply gap put at 2418.9 ml/day
[17,18]. Land subsidence poses many environmental hazards to
the affected areas. It worsens the local relative sea-level rise and
exposes the affected population to terrific environmental problems like permanent inundation, flooding, shoreline erosion and
saltwater intrusion, as well as damages to buildings, roads, train
tracks, pipelines and well casings [2,6,19e22]. Structural failures
in Nigeria's coastal cities are consequences of over-extraction of
underground fluids [13], and land reclamation and sand filling
for real estate development [12]. Given the current population
growth rate and the pace of urbanisation, demand for groundwater in Lagos will continue to rise.
Establishing the degree to which land subsidence is compounded by human impacts requires enhanced quantification and
monitoring [9] to quantify seismic geohazard and manage geohazard risk [19,23]. Enhanced approaches can also be used to
analyse the sediment records and understand the development
trend of regional disasters. Until now, no comprehensive land
subsidence analysis has been conducted to monitor the extent and
pattern of land subsidence in the city of Lagos. Consequently, little
is known about the full spatial variability of land subsidence in the
city. The few existing studies in this area have been mostly
restricted to a single-technique approach [11], and no study has
compared the results of different techniques over the study area.
Cian, F. et al. [12] did recently implement the Stanford Method for
Persistent Scatterer Interferometry (StaMPS PSI) technique to
study subsidence in some African coastal cities, including some
selected locations in Lagos. However, only a few synthetic aperture radar (SAR) data were considered in the study, limiting the
spatial coverage. In our study, we used a large number of SAR
images to obtain improved time series analysis results covering
most parts of Lagos. This paper presents the investigation of land
subsidence analysis across the city of Lagos at a high spatial resolution based on analysis of Global Positioning Satellite (GPS),
Interferometric SAR (InSAR), and Gravity Recovery and Climate
Experiment (GRACE) data. We investigated the trend in mass
change and the associated land displacements. In addition, we
determined the parts of Lagos that are characterised by critical
land subsidence and discussed the possible causes of the high
subsidence rate in the affected areas.
The deployment of space geodetic techniques, particularly the
GPS and InSAR, for high-accuracy geodetic monitoring has
increased significantly over the years [24]. And various studies have
demonstrated the effectiveness of these techniques to study
different forms of land deformation at a large scale in major cities
across the world. Subsidence [1,19,25e28], earthquake and volcanic
eruption [29e32] and flood and snowmelt monitoring have been
studied in depth [33,34]. Although GRACE has a low spatial resolution in monitoring variability in groundwater level for a wide
area, it can be successfully applied to monitor groundwater change
in smaller areas, particularly where high signal-to-noise ratio of
mass change resulting from a large-amplitude groundwater storage
change is concentrated [35]. Several studies have also established
the capability of GRACE and InSAR analyses to jointly monitor the
relationship and correlation between land subsidence and changes
in groundwater storage [35e42].
2. Study area
Lagos is one of the major Nigerian commercial cities, with an
estimated population of 25 million. The city has about 180 km of
Atlantic coastline in the southern part, and its topography is
comparatively flat in most parts, varying from 0 m above sea level
in the south to 79 m above sea level in the north. In terms of geology, Lagos is composed predominantly of sedimentary Tertiary
and Quaternary sediments. The Tertiary sediments are unconsolidated sandstones, grits with mudstone, and sand with clay layers,
while the Quaternary sediments are recent deltaic sands, mangrove
swamps, and coastal alluvium. Juvenile, organic-hydromorphic,
and ferralitic soils are the main soil group. Lagos is underlain by
the Dahomey Basin, which consists mainly of sands, shales, and
limestone. The limestone is thickened towards the west and along
the Atlantic coast [43]. Detailed stratigraphic descriptions of the
Dahomey Basin sediments have been provided by references
[44e48]. The Abeokuta Formation consists of a deep aquifer in the
northern parts of Lagos, and the water aquifer is approximately
750 m deep. The Coastal Plains Sands is the main aquifer in Lagos,
and it consists of a multi-aquifer system with three aquifer horizons
separated by silty or clayey layers [49,50]. The aquifer thickens from
its outcrop in the north of the city down towards the coast in the
south, and the sand percentage also changes from north to south
[49]. The generalized geology map of Lagos is shown in Fig. 1.
Lagos has a total area of about 3577 km2, of which about
787 km2 are occupied by water, wetlands, or mangrove swamps
[51]. Flooding in Lagos is generally prevalent between May and
October every year, with over 12% of the total land area of Lagos
subjected to pervasive seasonal flooding [52], which is likely to
increase significantly as climate change is expected to increase
annual precipitation [12]. Eze, U. et al. [14] noted that sand mining,
river damming, drainage obstruction, and destruction of vegetation
are major causes of Lagos' eroding shores, which have subjected
Lagos to the danger of tidal flooding. Mahmud, U. et al. [11] and
Balogun, I. et al. [17] reported that Lagos is one of the cities on the
Nigerian coast geosyncline that is subsiding as a result of continued
indiscriminate groundwater exploitation occasioned by the
persistent shortfall in public water supply and the consequent
compaction of rapidly deposited sediments.
2.1. Methodology and datasets
A comparative approach that included GPS data, Environmental
Satellite Advanced Synthetic Aperture Radar (Envisat-ASAR) data,
Sentinel-1 data, and GRACE data were used in this study. The satellite SAR data coverage over the study area is shown in Fig. 2. To
achieve improved spatial resolution of subsidence information, we
used InSAR datasets (Envisat and Sentinel-1) provided by the European Space Agency (ESA) to determine the line-of-sight (LOS)
mean land subsidence velocity and vertical deformation time series. The two InSAR datasets provided the spatial resolution over
the entire city, except for vegetative areas. To further enhance the
reliability of our results, we retrieved through the monthly GRACE
data corresponding vertical displacement caused by groundwater
changes at the GPS station (code: ULAG) located at the University of
Lagos campus. Finally, we compared the results obtained from each
of the techniques.
F.E. Ikuemonisan, V.C. Ozebo / Geodesy and Geodynamics 11 (2020) 151e162
153
Fig. 1. Generalized geology map of Lagos (modified after Ref. [53]).
Fig. 2. The SAR data coverage over the study area. The rectangles labelled with sensors' names and respective track numbers show the spatial coverage of various SAR images over
Lagos (The red, purple, yellow, blue rectangles are coverage of Sentinel-1 Track 95, Envisat Track 351, Sentinel-1 Track 1, and Envisat Track 122, respectively). Only Envisat Track 122
and Sentinel-1 Track 1 are used in the present study. The study area is bounded within the green rectangle. Features are superimposed on shaded topography provided by 30 m
elevation Shuttle Radar Topography Mission (SRTM).
2.1.1. GPS data
In geophysical studies, the GPS system is used primarily to
evaluate variations in a continent's position and velocity field in a
well-defined frame of reference [54]. To achieve high accuracy,
Bock, Y. et al. [55] proposed that observing GPS arrays operate
continuously for land deformation related to tectonic activity and
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F.E. Ikuemonisan, V.C. Ozebo / Geodesy and Geodynamics 11 (2020) 151e162
ground fluid withdrawal. In order to determine the trend, pattern,
and area with a high rate of land subsidence in Nigeria, we analysed
GPS data obtained from 15 GPS stations in continuous operation in
Nigeria and one in the neighbouring the Republic of Benin. The
stations, which provide a partial tie to a global reference frame and
temporal resolution in certain locations in Nigeria, have between
2.5 and 5 years of observations and some stations have operated
continuously up to 2015. We included the BJCO station in the Republic of Benin because it is close to Lagos and has a longer temporal length. The location coordinates of the GPS stations are
shown in Table 1. The GPS raw data was processed using Global
Navigation and Satellite Systems (GNSS)-Inferred Positioning System and Orbit Simulation Software version 6.1.1 (GIPSY/OASIS II v.
6.1.1) which was developed at the Jet Propulsion Laboratory (JPL)
[56]. A precise point positioning (PPP) technique implemented in
GIPSY was used to process the GPS phase and pseudo range measurement in Receiver Independent Exchange (RINEX) format [57].
With the aid of GIPSY/OASIS software, we calculated position coordinates within International GNSS Service 2008 (IGS08) in a time
series kinematic mode with receiver clock state as white noise with
updates on every measurement epoch and zenith wet delay as a
random walk with a variance of 3 mm2 per hour. The wet delay
gradient was treated as a random walk with a variance of 0.3 mm2
per hour and phase ambiguities as real numbers. Then, we constructed the sites' rate of motion from the time series plot obtained
from daily position and determined the stations' velocity vector.
2.1.2. InSAR data
The InSAR is a space geodetic technique developed to detect the
temporal evolution of crustal surface deformation and geomorphological characteristics of the lithosphere. It has ability to
generate high spatial resolution images regardless of the weather
condition in the area of interest at the time of measurement [26].
InSAR technology can monitor a wide area of land deformation and
provide highly accurate surface displacements over time in a
reasonable duration and with the minimal effort [23,58e60]. We
considered Envisat and Sentinel-1 data in this study.
2.1.2.1. Envisat data. The data provided by Envisat ASAR was the
only suitable one covering Lagos for an adequate period before
launching the Sentinel-1A satellite in 2014. Lagos city is covered by
two descending orbit tracks, numbers 122 and 351. However, only
Track 122 provided a full spatial coverage over Lagos. We processed
a total number of 139 images from Track 122 to determine subsidence rates and produce a surface velocity map for our study area.
Given that temporal and spatial baselines can strongly affect multi-
Table 1
GPS continuous operating reference station (CORS) location coordinates (IGS08
frame).
Station code
Latitude (degree)
Longitude (degree)
Ellipsoidal height (m)
ULAG
CLBR
FUTY
FUTA
UNEC
MDGR
OSGF
RUST
CGGT
FPNO
ABUZ
GEMB
BJCO
BKFP
HUKP
6.517
4.950
9.350
7.299
6.425
11.838
9.028
4.802
10.123
5.435
11.152
6.917
6.385
12.469
12.921
3.397
8.352
12.498
5.136
7.505
13.131
7.486
6.979
9.118
7.033
7.649
11.184
2.450
4.229
7.591
44.6
57.2
247.4
410.6
254.4
348.2
532.7
45.6
916.4
88.3
705.1
1795.6
30.7
250.0
559.6
temporal analysis if not well-defined. If their values are too small,
the number of available SAR datasets will be reduced and if they are
too large, temporal decorrelation will be created, which typically
decreases coherence magnitude and increases phase noise [61,62].
In this study, we used 1500 days and 400 m for the temporal and
spatial baselines, respectively, to reduce the effects of phase noise
and enhance the temporal and spatial coherence characteristics of
the interferograms. Table 2 details the processing parameters and
the satellite information of the Envisat data used in the study.
2.1.2.2. Sentinel-1 data. At the launch of the Copernicus Sentinel1A and Sentinel-1B satellites on April 8, 2014 and April 26, 2016,
respectively, a new era evolved of the continuous monitoring of
earth deformation using a space geodetic technique. The two
Sentinel-1 satellites constituted a significant advance from previous satellites such as the European Remote Sensing (ERS) satellite
and the Envisat satellite. They carried 12-m-long advanced SAR
antennas, which operate on C band with a wavelength of 5.6 cm.
With the two satellites, the temporal revisit time has reduced from
36 days to 6 days. A comprehensive description of the Sentinel-1
algorithm can be found in reference [63]. In this study, we performed SBAS analysis on 83 Sentinel-1A datasets acquired between
November 17, 2015 and June 23, 2019 to monitor the spatial distribution of subsidence in Lagos city. Table 3 shows the Sentinel-1
satellite information used in this study.
2.1.2.3. Envisat and Sentinel-1 data processing. Several methods
have been developed to further the use of InSAR data, widely used
among them are Persistent Scatterer Interferometry (PSI) and the
Small Baseline Subset (SBAS) method. The SBAS-InSAR is an
advanced Multi-Temporal InSAR (MT-InSAR) technique used to
accurately detect gradual deformations accurate up to a millimetre
using a stack of SAR interferograms to generate a displacement
time series [26,64]. In principle, the algorithm creates several small
space and time baseline interferometric pairs to form interferograms that reduce the impacts of decorrelation and topography.
The atmospheric phase is separated by low-pass and high-pass
filtering in space and time, respectively. This allows the multisensor SAR data collected using different radar sensors with the
same illumination geometry to be jointly processed to obtain the
long-term ground displacement [65]. Once the processing steps are
completed, the land deformation component between the two
observations via the LOS between the ground and the satellite is
given by the differential interferogram. Detailed descriptions of the
SBAS algorithm and the procedure to generate interferograms can
be found in reference [66].
Table 2
Satellite information of Envisat ASAR data used in this study.
Parameters
Values
Track number
Number of image used
Azimuth (m)
Range (m)
Heading angle (degree)
Incidence angle (degree)
Date of earliest image used
Date of latest images used
Maximum temporal baseline (days)
Max perpendicular baseline (m)
Maximum allowed doppler centroid (Hz)
Coherence threshold
Ground pixel dimension (m)
Goldstein weight
122
139
950
1250
76
21
October 7, 2004
August 22, 2011
1500
400
1000
0.7
80
0.5
F.E. Ikuemonisan, V.C. Ozebo / Geodesy and Geodynamics 11 (2020) 151e162
Table 3
Satellite information of Sentinel-1 data used in this study.
Parameters
Description
Orbit direction
Number of images used
Mission
Product type
Swath mode
Sub-Swath
Burst
Track
Central incidence angle
Polarization
Acquisition time
Ascending
83
Sentinel-1A
Single look complex (SLC)
IW TOPS
All swaths
2e7
1
38
VV
November 2015eJune 2019
Because the processing of SBAS-InSAR data is computationally
expensive to produce, we adopted the Geohazard Exploitation
Platform (GEP) cloud computing service to process the InSAR
datasets. The web-based GEP of the European Space Agency (ESA) is
designed to access Earth Observation (EO) data, to identify and
monitor geohazards such as earthquakes, subsidence, volcanos, and
landslides. The platform offers a reliable and user-friendly interface
that enables users to perform a parallel SBAS (P-SBAS) service, such
as analyses of spatial and temporal variability of surface displacements and generation of land deformation maps [30,61e64,67]. In
addition, the platform allows fast remote processing of a large
number of data without downloading them into the local machine.
The selection for the master image was based on low perpendicular
baseline dispersion at the centre of the time series. To reduce the
effects of phase noise and enhance the temporal and spatial
coherence characteristics of the interferograms, we set the
perpendicular baseline and temporal baseline at 400 m and 1500
days, respectively. All interferograms were obtained by using a
complex multi-look operation with four looks in range and azimuth. The differential interferograms were produced based on
temporal and spatial baseline thresholds and followed by the
multi-looking and Goldstein filtering to improve the interferograms' signal-noise-ratio. In this study, we used the P-SBAS Envisat
processing service and P-SBAS Sentinel-1 processing services to
process Envisat data and Sentinel-1 data, respectively.
2.1.3. GRACE data
In March 2002, the National Aeronautics and Space Administration (NASA) and German Aerospace Centre (DLR) jointly
launched the GRACE mission, comprising two satellites separated
by approximately 200 km into near-polar orbits at about 500 km
altitude, as part of the NASA Earth System Science Pathfinder
Programme. The project was designed to provide high-resolution
models of the Earth's gravity field at high accuracy. Numerous
studies have shown that the change in terrestrial water storage
based on the Earth's mass change and the same mass concentrated over a small area can be determined through the timevarying Earth gravity field provided by the GRACE [35,68,69].
Thus, high variability in storage can be monitored, such as the
aquifer recharge zone [20]. GRACE has been used to detect variations in the traditional field and surface deformation caused by
hydrologic loading. It has been considerably applied to model
hydrological loading both at regional and global scales [70]. In this
study, we used the monthly Level-2 gravity field products from
Release-5 (RL05) up to degree 60 in the form of spherical harmonic coefficient provided at the centre for space research at the
University of Texas, between April 2002 and January 2017 to
deduce land subsidence resulting from the impact of groundwater
155
depletion. We calculated the change in groundwater storage
(DGW) from the residual of GRACE terrestrial water storage (TWS)
anomalies. The components of TWS were computed using the
Global Land Data Assimilation System (GLDAS). GLDAS-based soil
moisture (SM) was also computed. Surface water, soil moisture
storage, snow water equivalent, and canopy monthly anomalies
were computed by removing the mean value over the period from
the monthly soil moisture values. The relationship between the
anomalies can be expressed as follows:
DTWS ¼ DSW þ DSM þ DGW þ DCPY þ DSWE
(1)
where DSW is change in surface water, DSM is change in soil
moisture, DGW is change in groundwater, DCPY is change in canopy
water, and DSWE is change in snow water equivalent. Thus, we
retrieved groundwater storage changes by subtracting SM changes
from GRACE TWS changes [37]. Hence, the possibility for land
subsidence is determined based on declining groundwater trends
deduced from linear fitting in the time series of groundwater
storage anomalies. The GRACE data can be accessed via http://
podaac.jpl.nasa.gov/GRACE.
3. Results and discussions
Analyses of GPS, GRACE, Envisat, and Sentinel-1 datasets
enable us to specifically monitor land subsidence in the Lagos city.
In this section, we present the results of each method and compare
them.
3.1. GPS result
We obtained cumulative vertical and horizontal deformation
time series for the ULAG station using the processed position coordinate. The calculated velocity field was based on the GPS data
collected between 2011 and 2014. We determined both the vertical
velocity (subsidence rate) and horizontal velocity. The horizontal
velocity is the vector component of the east and north components.
The values of GPS deformation rate for the east, north, and vertical
components were found to be 22.9 mm/year, 18.0 mm/year and
3.3 mm/year, respectively. The values of vertical velocity revealed
at the ULAG station indicates that the station is gradually subsiding.
The resultant horizontal velocity for the ULAG station was found to
be 29.1 mm/year in the direction of north-east (51.8 ). The steady
horizontal movement shown by the resultant horizontal component in the north-east direction indicates that the area of Lagos
where the station is located is not only subsiding but also gradually
drifting north-eastward. In other words, the calculated relative
horizontal velocity vector indicates existence of local movement
irregularities in and around the station. Moreover, velocity field
analyses confirm the unstable position of ULAG, BJCO, RUST, FUTA,
CLBR and HUKP stations, with ULAG being one of the stations with
the highest subsidence rate. The velocity vector component for all
the processed stations is shown in Fig. 3. In the ULAG station area,
the subsidence rate is gradually increasing but may be substantial
over time, posing a possible long-term threat to the safety of
structures and facilities. Fig. 4 shows the level of agreement in the
measured east, north, and vertical components in terms of correlation coefficients and standard deviations. The correlation coefficients show that the strength and direction of the linear
relationships between pairs of components (north-east, eastvertical, and north-vertical) are strong. Table 4 summarizes the
GPS results (Fig. 5).
156
F.E. Ikuemonisan, V.C. Ozebo / Geodesy and Geodynamics 11 (2020) 151e162
Fig. 3. Locations of the GPS stations used in the study. The vectors blue and red
represent the horizontal velocity vector and vertical vector respectively for the IGS08
reference frame, and overlain on a 30 m Shuttle Radar Topography Mission (SRTM)
digital elevation model.
Fig. 4. Relationships between the measured components (east, north, and vertical) for
ULAG continuous GPS station: (a) correlation coefficient; (b) variance.
3.2. InSAR result
In this section, we present the results of the SBAS-InSAR analyses performed on the Envisat and Sentinel-1 datasets.
3.2.1. Envisat result
The mean LOS velocity field, measured in millimetres-per-year,
was determined by the P-SBAS-InSAR technique applied to Envisat
data acquired between 2004 and 2011, as shown in Fig. 6. In Fig. 6,
negative values indicate that the surface is moving away from the
satellite, representing subsidence in the direction of LOS. The positive values show that the surface is moving towards the satellite,
indicating uplift. The inspection of Fig. 6 shows that subsidence is a
widespread phenomenon in Lagos. The P-SBAS result reveals significant land subsidence in the Lagos city in seven critical areas:
Ikoyi, Ketu-Alapere, Idimota, Victoria-Island, Apapa, Ijora-Olopa
and Orile-Iganmu.
These critical areas are close to either the Atlantic Ocean or
Lagos lagoon, as shown in Fig. 6. Vertical deformation time series
for areas where critical subsidence was observed are shown in
Fig. 7. The mean subsidence rate measured by the interferograms
for the critical areas from 2004 to 2011 is about 15 mm/year. In
addition, findings showed that mean subsidence for the critical
areas increased from 55 mm to 84 mm between 2009 and 2011. The
results also indicate that other areas of the city are undergoing land
subsidence but the subsidence rates are relatively low compared to
these seven areas of critical land subsidence mentioned above.
Fig. 8 is the plot of subsidence rates obtained from the Envisat PSBAS result against distance along an approximate northesouth
trending profile towards the Atlantic Ocean. The sinusoidal pattern
of subsidence distribution shown in the plot indicates that subsidence rates decrease with distance away from the Atlantic Ocean
coastline but increase towards the bank of Lagos lagoon. The uneven nature of the subsurface geology in the study area, which
resulted in the differential sediments compaction along the profile,
is considered as the major mechanism behind the sinusoidal
pattern.
3.2.2. Sentinel-1 result
Fig. 9 is a map depicting the mean LOS velocity of the study area,
which we obtained from the P-SBAS-InSAR time series analyses.
The map also reveals the rates of land subsidence distribution over
the study area. The result indicates that Ikoyi, Ijora-Olopa, Idumota,
Orile-Iganmu, Victoria Island, Lekki, Apapa, Ebute-Meta, and KetuAlapere are areas of critical subsidence. It shows that the mean
subsidence rate for areas of critical subsidence were about
63 mm/year from 2015 to 2017 and 87 mm/year from 2017 to
2019. Moreover, our results indicate that mean subsidence for these
critical areas was about 44 mm between 2015 and 2017. Then,
between 2017 and 2019, the mean subsidence was about 114 mm,
which indicates a significant increase in subsidence.
In the present study, critical subsidence rates were primarily
noted in areas located along the Atlantic Ocean coastline and in
the Lagos Lagoon, as well as in areas where extensive construction
projects have been taking place. The soil along the Atlantic Ocean
coast and near the bank of Lagos Lagoon comprises of alluvium
deposits formed as a result of loading and compaction of high
vertical sediments [71]. Subsidence rates ranging from 64 mm/
year to 4.9 mm/year were measured around Satellite Town,
Festac Town and the Ojo Local Government Area, where soils also
primarily comprise of alluvial sediments. Our results further
indicate that, while Agege, Ifako/Ijaye and some parts of the Ikeja
Local Government Areas appeared to be relatively stable, other
parts of Lagos city are is subsiding at a rate of 4.5 mm/year.
Moreover, the magnitude of subsidence rate measured for Ikoyi,
Idumota, Ketu-Alapere, Ijora-Olopa, Victoria-Island, and Apapa
suggests that these areas may be prone to other geohazards, such
as flooding, coastal erosion, and aquifer contamination, if
adequate mitigation measures are not implemented. Vertical
deformation time series for areas characterised by critical subsidence are shown in Fig. 10. Inspection of Fig. 9 shows that land
subsidence is a widespread phenomenon in Lagos.
F.E. Ikuemonisan, V.C. Ozebo / Geodesy and Geodynamics 11 (2020) 151e162
157
Table 4
Summary of GPS results.
Station code
ULAG
CLBR
FUTY
FUTA
UNEC
MDGR
OSGF
RUST
CGGT
FPNO
ABUZ
GEMB
BJCO
BKFP
HUKP
Velocity (mm/year)
Horizontal direction (degrees)
East
North
Resultant horizontal
Vertical
22.9
21.8
21.9
22.6
21.7
22.1
21.7
19.2
24.4
20.4
21.7
22.0
22.1
21.8
21.7
18.0
19.2
18.9
18.6
18.6
21.3
19.3
17.3
12.7
18.3
19.3
19.3
18.7
19.3
19.0
29.1
29.0
28.9
29.3
28.6
30.7
29.0
25.8
27.5
27.4
29.0
29.3
28.9
29.1
28.8
3.3
2.5
1.3
6.0
0.2
1.6
0.9
3.1
3.9
6.7
0.7
0.7
1.2
0.1
2.7
51.8
48.6
49.2
50.5
49.4
46.1
48.4
48.0
62.5
48.1
48.4
48.7
49.8
48.5
48.8
Fig. 5. Deformation time series plot derived from the continuous GPS data (station code: ULAG).
3.3. GRACE result
3.4. Discussions
The groundwater changes recorded between 2002 and early
2017 at the ULAG station are shown in Fig. 11. To obtain the correlation between groundwater change and land subsidence, we
estimated the groundwater changes as the difference between the
GRACE-based TWS changes and the GLDAS-based soil moisture
changes. This process revealed presence of a non-linear upward
trend during the period spanning from mid-2002 to mid-2011,
followed by a downward trend characterizing the period from
mid-2011 to 2017. Accordingly, the linear fitting also shows two
different trends for these periods (2002e2011 and 2011e2017). The
linear fitting method was adopted to determine the trend in land
subsidence caused by groundwater withdrawal, as proposed by
reference [42]. Specifically, the regression results indicate that land
subsidence induced by change in groundwater levels increased by
9.2 mm/year from 2002 to 2011, after which they declined by
11 mm/year until 2017. The results for the 2011e2017 period
further reveal a long-term trend in groundwater depletion. The
mean subsidence inferred from the linear fitting aligned with the
time series related to the groundwater level changes. The inferred
subsidence can be seen in Fig. 12.
In the present study, we examined the correlation between
the subsidence measured by the Envisat, Sentinel-1, GRACE, and
GPS techniques across different temporal coverages. To ensure
full alignment with the temporal resolution of the GRACE,
Envisat and Sentinel-1 datasets, the daily GPS displacement-time
series were detrended. Using a deformation-time series for the
2011e2014 period, the subsidence rates were calculated based on
the GPS data obtained from ULAG station. Similarly, we determined the subsidence rates by dividing the magnitude of the
land subsidence for each interferogram near the ULAG station by
the number of days the interferogram covered, as proposed by
reference [72]. Moreover, we computed the GRACE-based subsidence, and retrieved the Envisat and Sentinel-1 data points
corresponding to the location of the ULAG station. Due to the
differences in the spatial and temporal coverage in the GRACE,
Envisat, Sentinel-1, and GPS datasets, the magnitude of subsidence measured by these techniques could not be directly
compared or integrated. For example, to implement InSAR and
GPS integration, the GPS velocities need to be interpolated and
resampled to the InSAR grid points, but the numbers of GPS
158
F.E. Ikuemonisan, V.C. Ozebo / Geodesy and Geodynamics 11 (2020) 151e162
Fig. 6. Mean LOS velocity map generated through the P-SBAS processing for Envisat data acquired from 2004 to 2011.Negative and positive values represent subsidence and uplift,
respectively. Features are superimposed on a 30 m Shuttle Radar Topography Mission (SRTM) digital elevation model. The line AeB is an approximate northesouth trending profile
line.
Fig. 7. Vertical deformation time series for areas characterised by critical subsidence as
revealed by Envisat Track 122 over Lagos metropolis.
Fig. 8. XeY plot for distance against vertical deformation rates retrieved from the
Envisat P-SBAS InSAR analysis along the approximate northesouth trending profile,
showing subsidence pattern.
stations located in Lagos are not sufficient to provide the
required GPS velocities for interpolation. Consequently, we only
compared the subsidence rates and magnitudes where the
measurements overlapped.
Fig. 12 shows the pattern of vertical deformation time series
measured by the Envisat, Sentinel-1, GPS, and GRACE techniques
near the ULAG station. The GRACE-based derived groundwater
changes at the ULAG location show a continuous declining trend
between 2011 and 2017, as shown in Fig. 11. The GPS result and the
GRACE-based subsidence respectively reveal a subsidence rate of
3 mm/year and 11 mm/year. The mass change (subsidence) at
the ULAG GPS station may be attributed to the groundwater
depletion. The InSAR derived land subsidence rate revealed
9.7 mm/year for Envisat data acquired between 2004 and 2011,
and 58 mm/year for Sentinel-1 data acquired between 2017 and
2019, which indicates a significant variation. The subsidence rates
between 2011 and mid-2014 for GPS and GRACE are 3.3 mm/
year and 5.2 mm/year, respectively. Between 2015 and 2017, the
subsidence rates revealed by GRACE and Sentinel-1 are 18 mm/
year and 61 mm/year, respectively. In 2011, the average
F.E. Ikuemonisan, V.C. Ozebo / Geodesy and Geodynamics 11 (2020) 151e162
159
Fig. 9. Mean LOS velocity map generated through the P-SBAS processing for Sentinel-1 data acquired between 2015 and 2019. Negative and positive values respectively represent
subsidence and uplift rates. Features are superimposed on a 30 m Shuttle Radar Topography Mission (SRTM) digital elevation model.
subsidence measured by Envisat is about 23 mm and 12 mm for
GRACE. In mid-2017, the average subsidence revealed by Sentinel1 and GRACE is 64 mm 33 mm, respectively. The average subsidence measured by Sentinel-1 in 2019 is about 74 mm. The results
obtained from the continuous GPS data and the three satellites'
data (Envisat, GRACE, and Sentinel-1) agreed that Lagos is undergoing a rapid land subsidence.
The declining trend in the groundwater changes detected by
GRACE and the subsidence measured by InSAR provide a general
pattern of land subsidence over the study area. The cyclical
seasonal peak amplitude revealed by GRACE suggests a strong
seasonal hydrological fluctuation at the ULAG station. There is a
good correspondence between the Envisat and Sentinel-1 results
in terms of subsidence pattern in Lagos, which means that they
both reveal the area of the city with critical subsidence. However, the deformation magnitude revealed by Sentinel-1 is
comparably larger, indicating the highest subsidence rate at
present, than the deformation magnitudes determined by the
Envisat. Since the Sentinel-1 datasets contained recent measurements, it suggests that the subsidence rate in Lagos has
significantly increased in the last 15 years. The significant variations in the Envisat and Sentinel-1 results may be connected
with some of the following contributions: (a) the relatively short
acquisition interval between Sentinel-1 images, (b) different
incident angles with which the satellites operate, (c) different
temporal coverage, (d) sediments loading caused by a long-time
decay of soil compaction rate, and (e) error associated with
InSAR processing [73].
Fig. 10. Vertical deformation time series for areas of critical subsidence as observed by
Sentinel-1 (Track 1) across the Lagos city area. (a) Vertical deformation time series
between 2015 and early 2017 (with 64 mm/year maximum subsidence rate); (b)
Vertical deformation time series for the 2017e2019 period (characterised by 87 mm/
year maximum subsidence rate).
160
F.E. Ikuemonisan, V.C. Ozebo / Geodesy and Geodynamics 11 (2020) 151e162
Fig. 11. Time series of groundwater changes derived from the GRACE data. The yellow line and purple line represent the linear fitting for measurement between 2011 e 2017 and
2002e2011, respectively.
This study focused mainly on the extent and pattern of land
subsidence and not its driving mechanism as this would have
required long-term measurements of surface displacement and
formulation of a firm geophysical theory for each part of the
process. However, it is important to highlight possible causes
of land subsidence in the study area because it will help to
accurately model subsidence and other associated geohazards.
Previous studies [12,13] reported that excessive groundwater
extraction can be a major cause of land subsidence and
structural failure in Lagos city. Because large volumes of
groundwater are being pumped from the Lagos aquifer [17], it
is expected that the aquifer's poroelastic response to the
groundwater redistribution will be high, which may be
responsible for land subsidence. Another explanation is offered
by Aslan, G. et al. [74] who reported that natural forces like
isostatic adjustment and natural settling of Holocene sediments (which depend on the age of the sediments), as well as
the thickness of the compressible deposits, the hydrological
condition and the stratum lithology may be the primary causes
of land subsidence in coastal cities like Lagos. Furthermore, the
pattern of subsidence may also be connected to the flexural
isostatic deformation resulted from the passive continental
margin of an Africa plate that subsided during the Jurassic
period [75].
4. Conclusions
In this study, we monitored and mapped the extent and pattern
of land subsidence in the coastal city of Lagos through comparative
analyses of GPS, Envisat, Sentinel-1, and GRACE datasets. The analyses enabled us to comprehensively map the land subsidence in
Lagos between 2004 and early 2019, which is helpful for understanding the regional development of disastrous trend within the
study area. Particularly, this study helped in identifying the parts of
Lagos that are highly prone to geohazards associated with land
subsidence. The study revealed clear variability in spatial subsidence
over the study area, which reflects the hydrogeological units and
differential compaction of different stratigraphic units. Furthermore,
this study identified several areas along the coasts of the Atlantic
Ocean and Lagos lagoon, which are essentially alluvial deposits undergoing a rapid land subsidence. The spatial trend of land subsidence revealed by Envisat and Sentinel-1 measurements support
that land subsidence is a widespread occurrence in Lagos. If adequate
measures are not instituted to mitigate this issue, areas where critical
subsidence had been observed might become prone to other associated geohazards, such as flooding, aquifer contamination, and
saltwater intrusion. Because the rapid population growth of Lagos
city is a major determinant of groundwater exploitation, it is likely
that land subsidence in the city has been significantly modified
locally by the over-extraction of groundwater. We also highlighted
other possible causes of land subsidence in Lagos. Understanding the
driving force behind the land subsidence will help to accurately
model subsidence and other associated geohazards. Therefore, we
hope to study the driving mechanism of the land subsidence in Lagos
city in our subsequent study.
Funding information
The first author personally funded the project.
Author statement
Fig. 12. Vertical deformation time series measured at the ULAG GPS station by the
various techniques.
F.E. Ikuemonisan handled the research conceptualization, methods, investigation, formal analysis, while V.C. Ozebo provided the
oversight, mentorship, and leadership responsible for the research
activity planning and execution, including critical review.
F.E. Ikuemonisan, V.C. Ozebo / Geodesy and Geodynamics 11 (2020) 151e162
Conflict of interest
The authors declare that there is no conflicts of interest.
Acknowledgement
The authors would like to thank the following data providers for
making the data available: GRACE, GLDAS, JPL, and in particular the
European Space Agency (ESA) for providing Envisat, Sentinel-1
datasets, and the Geohazards Thematic Exploitation Platform
(Geohazard TEP). The authors also like to acknowledge four anonymous reviewers for their insightful comments. The authors
sincerely thank the editor for her contribution to this paper.
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Femi Emmanuel Ikuemonisan, is a Ph.D. student
in the Department of Physics (Geophysics research
group), University of Lagos, Nigeria. He obtained a
master's degree in Geophysics in 2015 from the
Federal University of Agricultural, Abeokuta. He has
been a visiting physics lecturer at the Lagos State
University and Crawford University since 2017 and
2018, respectively. His research interests include
geostatistics, crustal deformation, land subsidence,
geodesy and geodynamics.
Vitalis Chidi Ozebo, is an experienced associate professor
with a demonstrated history of working in the higher
education industry. Skilled in analytical skills, geophysics,
lecturing, curriculum development, and mathematical
modelling. Strong professional education with a M.Sc. and
a Ph.D. focused in Solid Earth Physics from University of
Ibadan, Nigeria.