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Mapping Trajectories of Coastal Land Reclamation in Nine Deltaic Megacities using Google Earth Engine


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Increasing demand for land resources at the coast has exerted immense pressure on vulnerable environments. Population and economic growth in coastal cities have combined to produce a scarcity of suitable space for development, the response to which has frequently been the reclamation of land from the sea, most prominently in China. Urbanization is a key driver of such changes and a detailed investigation of coastal land reclamation at the city scale is required. This study analyzed remote sensing imagery for the period 1990 to 2018 to explore the trajectories of coastal land reclamation in nine major urban agglomerations across the three largest deltas in China using the JRC Global Surface Water (Yearly Water Classification History, v1.1) (GSW) dataset on the Google Earth Engine platform. The results are considered in the context of major national policy reforms over the last three decades. The analysis reveals that total land reclaimed among nine selected cities had exceeded 2800 km2 since 1984, 82% of which occurred after 2000, a year following the enactment of China’s agricultural ‘red line’ policy. Shanghai exhibited the greatest overall area of land extension, followed by Ningbo and Tianjin, especially in the period following the privatization of property rights in 2004. In analyzing annual trends, we identified the developmental stages of a typical coastal reclamation project and how these vary between cities. Scrutiny of the results revealed voids in nighttime light satellite data (2014–2018) in some localities. Although these voids appeared to be characterized by construction, they were occupied by vacant buildings, and were therefore examples of so-called “ghost cities.” In China, as elsewhere, continual land reclamation needs to be considered in relation to, inter alia, sea level rise and land subsidence that pose significant challenges to the vision of sustainable urban development in these three deltaic megacities.
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remote sensing
Mapping Trajectories of Coastal Land Reclamation in
Nine Deltaic Megacities using Google Earth Engine
Dhritiraj Sengupta 1, Ruishan Chen 1, *, Michael E Meadows 1,2 , Young Rae Choi 3,
Abhishek Banerjee 1and Xia Zilong 1
1Key Laboratory of Geographic Information Science, Ministry of Education, and School of Geographical
Sciences, Institute of Eco-Chongming, East China Normal University, Shanghai 200241, China; (D.S.); (M.E.M.); (A.B.); (X.Z.)
2Department of Environmental and Geographical Science, University of Cape Town, Cape Town 7701,
South Africa
3Department of Global and Sociocultural Studies, Florida International University, Miami, FL 33139, USA;
*Correspondence:; Tel.: +86-130-3212-9658
Received: 8 October 2019; Accepted: 5 November 2019; Published: 8 November 2019
Increasing demand for land resources at the coast has exerted immense pressure on
vulnerable environments. Population and economic growth in coastal cities have combined to
produce a scarcity of suitable space for development, the response to which has frequently been
the reclamation of land from the sea, most prominently in China. Urbanization is a key driver of
such changes and a detailed investigation of coastal land reclamation at the city scale is required.
This study analyzed remote sensing imagery for the period 1990 to 2018 to explore the trajectories
of coastal land reclamation in nine major urban agglomerations across the three largest deltas in
China using the JRC Global Surface Water (Yearly Water Classification History, v1.1) (GSW) dataset
on the Google Earth Engine platform. The results are considered in the context of major national
policy reforms over the last three decades. The analysis reveals that total land reclaimed among nine
selected cities had exceeded 2800 km
since 1984, 82% of which occurred after 2000, a year following
the enactment of China’s agricultural ‘red line’ policy. Shanghai exhibited the greatest overall area of
land extension, followed by Ningbo and Tianjin, especially in the period following the privatization
of property rights in 2004. In analyzing annual trends, we identified the developmental stages of a
typical coastal reclamation project and how these vary between cities. Scrutiny of the results revealed
voids in nighttime light satellite data (2014–2018) in some localities. Although these voids appeared
to be characterized by construction, they were occupied by vacant buildings, and were therefore
examples of so-called “ghost cities.” In China, as elsewhere, continual land reclamation needs to be
considered in relation to, inter alia, sea level rise and land subsidence that pose significant challenges
to the vision of sustainable urban development in these three deltaic megacities.
reclaimed land; coastal urbanization; global surface water dataset; nighttime light dataset;
China; red line policy
1. Introduction
The low elevation coastal zone (LECZ) supports 40% of the world’s population, and its limited
land resource is subject to immense pressures that are exacerbated by sea level rise [
]. Recently, large
scale coastal land reclamation has become an important manifestation of the human urban footprint [
Mega reclamation projects represent a significant threat to marine ecosystems and deserve much closer
Remote Sens. 2019,11, 2621; doi:10.3390/rs11222621
Remote Sens. 2019,11, 2621 2 of 13
scrutiny. In addition, the United Nations’ recent report “The Ocean and the Sustainable Development
Goals under the 2030 Agenda for Sustainable Development” addresses the land reclamation of salt
marshes, intertidal flats, and mangroves as a primary threat to the sustainability of coastal and marine
ecosystems [
]. Recent examples of such mega structures at the coast include the Palm resorts of Dubai,
international airports in Hong Kong, Macau, and Singapore, mega smart city projects such as ‘Eko
Atlantic’ in Lagos, Nigeria, and Songdo smart city, South Korea. The scale of land reclamation taking
place on the world’s coasts today is unprecedented and a critical understanding of the spatial and
temporal characteristics of these high impact practices is overdue. While reclaiming land is a global
phenomenon, China’s hunger for land [
] has resulted in it clearly outstripping other nations in
land reclamation for development at the congested coastal frontier (Figure 1a,b). Understanding the
policy context, along with information about the nature, magnitude and impacts of such projects, is
clearly a requirement if the goal of sustainable coastal urbanization is to be achieved. The process is
deeply rooted in understanding the major policy reforms that China implemented to maximize coastal
benefits for its cities and, in turn, help to sustain its national economy.
In 2018, China celebrated 40 years of reform and development, during which rapid economic and
population growth were accompanied by high rates of coastal urbanization and an accelerated demand
for land. This demand resulted in noticeable land use transformation, initially characterized by a shift
from agriculture to urban development [
]. However, for cities at the coast, land reclamation has
become the dominant means by which they extend and develop their urban areas [
]. Since 1985,
more than 6000 km
of land has been reclaimed in China, principally within and around its shining
coastal cities; where coastal reclamation is especially concentrated in cities located in its three highly
vulnerable deltaic ecosystems [
]. Notwithstanding the associated deleterious environmental and
ecological impacts [
], coastal land reclamation has emerged in China as a key strategy to
address three issues, i.e., urban land scarcity, the promotion of a so-called ‘eco-civilization’, and as an
adaptive measure to combat sea level rise [7,13,14].
Until now, much of the studies on coastal land reclamation have been at a national scale [
however, this paper aims to analyze the changing spatial extent of coastal land reclamation in China at
the individual city scale, and in relation to evolving urbanization and associated planning policies. In
doing so, we address the following objectives for nine megacities located in the world’s three largest
urbanized deltas:
Using the GSW dataset to map the annual occurrence of coastal land reclamation, including
change in total area, spatial distribution, and statistical trends from 1990 to 2018;
Using normalized dierence indices (NDVI and NDBI), to identify the nature of seaward land
extension through a consideration of how the process evolves, from the initial reclamation phase
to the establishment of land use development.
To assess the relationship between the pattern of coastal land reclamation and annual GDP growth
rate against the background of China’s economic and policy reform;
To strengthen the analysis by validating results with ground-truth remotely sensed imagery to
capture the most recent patterns of land use over reclaimed land.
Although China has a very high rate of urbanization (2.9 percent per year between 2000–2013),
much of which is at the deltaic coast (Figure 1c), it houses less than 50% of the global per capita mean
of arable land, resulting in potential food insecurity [
]. Therefore, land has become a zone of
intense resource conflict between agriculture, urban construction, and ecology; the so-called ‘land use
trilemma’ [
]. In response to this tension, the state government established what is known as the
agricultural ‘red line’ policy [
], by which a total of 1.2 million km
of basic farmland was delimited
nationally under the New Land Administrative Law of 1999, and this established a strict spatial limit
for urban expansion [9,18].
With rising demand for suitable land, many tidal flats and coastal wetlands were drained
and converted to agricultural, residential, commercial, or industrial land. These high levels of
Remote Sens. 2019,11, 2621 3 of 13
construction and urbanization, especially in the major deltaic regions of China (Figure 1d–f), have
led to a massive loss of natural wetlands and their associated ecosystems, and needs eective policy
integration [
]. With growing concerns regarding such degradation, the government has begun
promoting ‘eco-civilization’ in major coastal cities [
]. Meanwhile, land extension as a ‘by-product’ of
coastal protection is a common feature of recent coastal dynamics, especially in the world’s coastal
megacities [
]. China’s coastal zone is predicted to face increased risks of flooding; Brown et al.
(2018) [
] suggest that almost 100 million people in China (SSP3 scenario) face potentially catastrophic
flooding and storm surges, largely consequent on future RSLR. While China and other countries
may currently have the means to geo-engineer their coastlines to mitigate flood risk from rising
sea levels, mostly by constructing sea-walls, escalating energy and material costs are likely to make
such interventions less feasible in the future [
]. Land reclamation is now a dominant feature
of China’s coastal urbanization heightening exposure to risk and vulnerability [
]. Therefore,
understanding the key policies behind seaward land expansion at the city scale is vital, as is a more
detailed consideration of the pattern and process of land use changes over recently reclaimed land.
Figure 1.
) Global map of land gain per 100 km of the coastline between 1984 and 2015 using GSW;
) illustrates, for each country, the total area of land gain; note China clearly has the highest value.
) Global human settlement layer (GHSL) Population grid (no. of people per cell) for coastal China
(2015) (JRC, CIESIN, 2015), Nighttime light linear regression over time using DMSP OLS (Nighttime
Lights Time Series Version 4, Defense Meteorological Program Operational Linescan System) showing
urban expansion 1992–2014 as indicated by nighttime light data for deltaic megacities: (
) Yangtze, (
Tianjin-Tangshan and (f) Pearl.
Remote Sens. 2019,11, 2621 4 of 13
2. Materials and Methods
The AWEI (automatic water extraction index) and Ostu’s thresholding method are used in the
Google Earth Engine (GEE) platform to extract coastlines from the atmospherically corrected surface
reflectance of the Landsat 5 TM sensor using the Landsat Ecosystem Disturbance Adaptive Processing
System (LEDAPS) [
]. Moreover, cloud, shadow, and water masks of the Landsat imagery used in
this study were obtained from ‘pixel_qa’ band generated using the CFMASK algorithm [
]. An annual
composite of 1990 was further processed to obtain a 20 km seaward buer to include o-shore
reclamation around islands (from the 1990 coastline) as the spatial extent in calculating the area of land
reclaimed for nine cities in China. Each city boundary was obtained from the OpenStreetMaps website
( The AWEI distinguishes between ‘water’ and ‘non-water’ pixels
by taking the dierence of spectral bands and using coecients to enhance the spectral separation
between the two distinct surfaces [
]. AWEInsh enables the eradication of non-water pixel areas
and it was used here in areas with an urban background; where greater accuracy was achieved through
the removal of shadow pixels not eectively eliminated by AWEInsh. AWEInsh was calculated as in
Equation (1) [28]. (GEE code 1, see Appendix A)
AWEInsh =4×(Green SWIR1) (0.25 ×NIR +2.75 ×SWIR2) (1)
The GSW water classification history v1.1 database [
], which describes the dynamics of water
presence over the 29-year period (1990–2018) on a pixel basis, was used as the primary source of data
to calculate the annual rate of land reclamation along the coastline of nine deltaic cities using GEE
(Figure 2). In this study, we followed the interpretation of this dataset as explained by Mentaschi et al.
(2018) [
], whereby each 30 m pixel was classified as (1) “land” in the absence of water pixels; or,
in the case of within-year fluctuations between water and land and (2) “seasonal water.” (GEE code
2 and 3, see Appendix A) For our study, we combined these two classification types to map and
tabulate annual change in coastal land reclamation (Figure S1 and GEE code 4, see Appendix A).
Furthermore, to delineate coastal land in calculating the reclamation area using GSW, the Advanced
Land Observing Satellite (ALOS) DSM 30m was used as a masking layer in the GEE platform [
(GEE code 4, see Appendix A). Additionally, the Landsat TM 5 and 8 OLI/TIRS images of the summer
composite (July to September) of NDVI and the NDBI annual composite were employed in the GEE to
map the stages of coastal land reclamation for the Dongjiang Bay Scenic Area in Tianjin. Mann–Kendall
and Sen’s slope estimator were applied using Matlab R2019a and ArcGIS 10.2, to tabulate and map
statistical trends and assess the magnitude of change, respectively. Subsequently, stratified random
ground GPS points were identified to enable visualization and linear regression over time of monthly
average radiance composite images from 2014 to 2018, using average Day Night Band radiance
values (avg_rad’-nanoWatts/cm
/sr) of nighttime data from the Visible Infrared Imaging Radiometer
Suite (VIIRS) in GEE code 5 (see Appendix A) editor API platform. Validation of the results was
performed using field investigation in Tianjin and Shanghai, as well as through visual interpretation of
high-resolution historical Google Earth Pro©imagery and Baidu©streel level maps.
Figure 2. Flowchart illustrating the methods and steps followed in this study.
Remote Sens. 2019,11, 2621 5 of 13
3. Results
Analysis of the GSW dataset facilitated the visualization and calculation of the spatial distribution
of coastal land reclaimed in each year since 1990, for the nine individual cities (Figures 3and 4a).
According to Supplementary Materials, the total land reclaimed across the nine cities exceeded 2800
over the duration, of which 82% was gained post 2000 (Figure 4b and Figure S1). The most
prominent overall increases occurred in Shanghai (Figure 3a) (1990: 325.54 km
, 2018: 717 km
followed by Ningbo (1990: 267.31 km
, 2018: 634.30 km
) (Figure 3e), and Tangshan (1990: 195.73 km
2018: 424 km
) (Figure 3b). Zhong et al. (2019) [
] commented on the extent of Shanghai’s urban
expansion, but did not consider reclaimed land in their analysis, thereby underestimating the scale of
change. Furthermore, Figure 5shows statistical trends in the temporal pattern of reclamation for eight
of the nine cities.
Figure 3.
Annual progression in coastal land reclaimed for nine major coastal cities across three deltaic
urban agglomerations, derived using the GSW dataset. (
) Tianjin, (
) Tangshan, (
) Qinhuangdao, (
Shanghai, (e) Ningbo, (f) Jiaxing, (g) Shenzhen, (h) Zhuhai, (i) Guangzhou.
Remote Sens. 2019,11, 2621 6 of 13
Figure 4.
) Annual increase of coastal land reclamation in nine major coastal megacities in China. (
Radar chart (1990–2018) illustrating the total annual gain in coastal land for the nine cities; note that
land extensions are predominantly post-2000; darker colors =greater areas of land reclaimed annually.
Figure 5.
Sen’s slope for temporal trends in coastal land reclamation for (
) Tianjin, (
) Tangshan, (
Shanghai, (
) Ningbo, (
) Jiaxing, (
) Shenzhen, (
) Zhuhai, and (
) Guangzhou. All the cities exhibit
a statistically significant increasing trend (Qinhuangdao is not shown as increase is not statistically
significant). Maps show that, statistically, the maximum degree of change is in Shanghai, followed by
Tianjin and Zhuhai (Sen’s slope value). In terms of annual coastal land reclamation (
) Yangtze River
delta-Ningbo =9.10 km
, Shanghai-15.53 km
, Jiaxing =3.81 km
, (
) Pearl River delta-Shenzhen =
2.10 km
, Zhuhai =1.19 km
, Guangzhou =5.88 km
, (
) Tianjin =10.01 km
, Tangshan =5.66 km
Qinhuangdao =0.12 km2(alpha = < 0.05).
The regression for Shanghai, Ningbo, and Shenzhen suggested that approximately the same
additional amount of land had been reclaimed every year during the period 1990 to 2018. However, in
other cities, in particular Tianjin and Tangshan, there were periods of rapid development associated
with large-scale projects (e.g., Caofeidian Eco-city, see Reference [
]), resulting in greater residual
values (Figure 5a–h). Additionally, cities generally exhibited a more regular linear regression after
2000. Spatial variability in the area of reclaimed land could be observed among the three urban
agglomerations; where more than 1800 km
of land extension occurred around the cities of the Yangtze
estuary, followed by Tianjin-Tangshan-Qinhuangdao (925 km
), and the Pearl River agglomeration
Remote Sens. 2019,11, 2621 7 of 13
(438 km
) (Figure 3). Besides individual city planning policies, this variation was also because some
cities, including Shenzhen, Zhuhai, and Guangzhou, had smaller administrative boundaries along the
actual coastline. Statistical analysis revealed a strongly positive increasing trend in the total annual
rate of coastal land reclamation over time (Figure 5j–i). Shanghai exhibited the maximum magnitude
of increase (15.53 km
/decade), followed by Tianjin (10.1 km
/decade), and Ningbo (9.10 km
at a 95% significance level. Assessment of coastal land reclamation using the GSW dataset in GEE
allowed for detailed interpretation of the dynamics of the construction process. According to the
Supplementary Materials, Fluctuations could be explained where reclamation of ‘land’ was followed
by construction of water bodies, such as o-shore artificial lakes or reservoirs, and in some cases, these
were again replaced by land use changes in the construction plan [7] (Figure S1).
4. Discussion
4.1. The Evolving Policy Context
Figure 6a summarizes the annual trend of coastal land reclamation in relation to the implementation
of key major policy reforms [
]. Following the incorporation of guaranteed private property rights
into the Chinese constitution in 2004, the nature of the relationship between annual GDP growth and
land reclamation appeared to shift. At this time the trend lines diverge, and the two parameters appear
to become decoupled (Figure 6a). The annual growth in GDP slows after 2005, although the area of
reclaimed land continues to rise, following the implementation of Marine Functional Zoning (MFZ;
2010–2020) [34] and the Ecological Red Line policy (ERP) (2015) [14].
Figure 6.
) Total annual land reclaimed across all nine cities plotted against annual growth in GDP;
the graph also indicates China’s major phases of policy reform over the period. (
) National land sales
revenue (billion RMB) (Source-Ministry of land and Resources (2004–2016) plotted against total annual
land reclaimed for nine megacities.)
The strong positive relationship between land sales revenue, urban sprawl, and China’s economic
growth rate is illustrated in Figure 6b [
]. The area of reclaimed land for the nine cities continued to
rise between 2003 and 2010 as the annual revenue from government land sales increased. However,
despite the decline in land sales during the past few years, the annual rate of land reclamation
has continued to grow. The decoupling of land reclamation from GDP and land sales suggests
that factors other than economic growth are at play, such as increasing housing rent values, the
declining contribution of labor to GDP in response to the shift from agriculture to industry, and the
fact that households are allocating more to savings than previously [
]. Indeed, local governments’
outstanding debt now exceeds 18,400 billion RMB [
]. However, in the context of the recently
implemented ERP, the rate of coastal land reclamation remains high.
Figure 7highlights the stages of rapid development for a typical major coastal land reclamation
project, the Dongjiang scenic area, an artificial beach in Tianjin (GEE code 6, see Appendix A).
Construction of dykes was completed within two years of the plan being initiated and, by 2010, 35 km
of land was reclaimed. Patterns in vegetation and built-up land highlight the evolution of a systematic
post-reclamation land use configuration. Higher values of built-up land in 2010 characterize the initial
Remote Sens. 2019,11, 2621 8 of 13
phase of land use development, although this diuses over time and the NDBI levels eventually decline,
probably due to urban green landscaping after land construction [
]. Note that, as construction on the
reclaimed land develops, the NDVI and NDBI also change in areas adjacent to the reclamation site.
Figure 7.
A model of the five phases of land reclamation illustrated by the changes in NDVI & NDBI
values in the Dongjiang Bay Scenic Area (artificial beach), Tianjin.
4.2. Recent Patterns of Land Use on Reclaimed Land
In considering what land uses characterize the reclaimed land, it is notable that, after 2000, most
reclaimed land has been used for urban development, ports, and manufacturing [
]. However, a
more nuanced picture of the changing land uses over time may be obtained using monthly average
night time radiance based on advanced infrared imaging technology [
]. Nighttime light data enables
the interpretation of earth surface characteristics that are not well captured by daytime imagery,
and both the nature and intensity of the human footprint may be more reliably assessed using this
data source [
]. Furthermore, to extract more accurate land use information on reclaimed land, we
Remote Sens. 2019,11, 2621 9 of 13
established several GPS-fixed ground observation points and used these points in combination with
VIIRS nighttime data to investigate the 2014–2018 trend in urban land use intensity in the nine cities
under consideration. Figure 8reveals that there has been a gradual increase in nighttime radiance for
GPS points (Figure 8e,g,h,i) corresponding to high resolution ground and street-level images acquired
through Baidu Inc. These reveal the urban intensity for three of these sites (Figure 8(1i,2ii,3iii)).
Figure 8.
Maps showing the combination of ground-truthed GPS points (
) and mean monthly
radiance composite imagery based on night time data from the VIIRS and Baidu street maps (i, ii, iii)
which showcases change in nighttime light data over four years (2014–2018) over reclaimed land (
Shanghai, (2) Tianjin, (3) Shenzhen. (Street view images-©Baidu Inc.)
Recently reclaimed land is typically associated with the development of major ports (e.g., the Bohai
and Shenzhen Bay regions). Notably, some localities in Tianjin are characterized by prominent voids in
nighttime radiance (Figure 8(2d) and Figure 8(2f)). This suggests that, while reclaimed land in Shanghai
and Shenzhen was developed immediately, there was delayed development in Tianjin, probably due
to financial constraints and mixed land use planning. [
] Comparisons with ground-truth images
suggest that, although some of these voids are indeed characterized by construction, the buildings
remain unoccupied, and are therefore examples of the so-called “ghost cities” [
]. Meanwhile, local
governments are investing more capital and engaging in ‘prestige construction’ to maximize land
revenue profits [
]. Ground observation points (b), (c), and (d) also exhibit decreased levels of night
time radiance; where in these cases, the land use change involves the establishment of plantations,
artificial wetlands, or wetland parks [20].
This study reveals that maximum seaward land extension has occurred in the megacities of
the major coastal deltas. Even with the implementation of ERP and MFZ, which aim to preserve a
quarter of China’s land [
] and plan eective marine resource utilization [
], preserving coastal
land for ecological and agricultural land uses in the era of excessive urbanization remains a major
challenge [
]. For instance, authorities in the Yangtze River delta region, which is home to 150
million people, have planned to set aside 28,995 km
of land for conservation [
]. However, recent
studies have highlighted ongoing serious land degradation at the coast, especially due to large scale
geoengineering activities. [
] Furthermore, with a growing population, rising sea levels, and the
frequent occurrence of extreme weather events, it becomes extremely important to critically evaluate
the role of reclaimed land at the coast. A more detailed understanding of the process of coastal
land reclamation at the individual city scale, as demonstrated in this paper, oers important insights.
In addition, we show that analysis of advanced remote sensing imagery, such as the nighttime light
dataset and Baidu
street view (Figure 8), enables details of the human footprint over congested
reclaimed land at the coast to be revealed. The combination of three key datasets provides for rapid
Remote Sens. 2019,11, 2621 10 of 13
visualization and calculation of the extent of coastal land reclamation, and this could be further used to
analyze, as well as monitor, reclaimed land at high spatial and temporal resolution. The method is
potentially applicable to the assessment and monitoring of the extent of coastal land reclamation at a
global scale using the GEE.
5. Conclusions
This study was undertaken to evaluate coastal land reclamation as a key instrument in China’s
evolving planning policies, especially with respect to urbanization. Such large-scale reclamation at
city scale highlights its impact over an interconnected land–ocean continuum, which also has global
implications with respect to recent climate change. To account for and highlight coastal modifications
at the city scale, we used a global dataset on surface water (JRC-GSW v1.1) to map the annual gain in
coastal land for nine megacities across the three largest deltas in China. The results of this investigation
illustrated the very rapid expansion of reclamation post-2000, following the implementation of the
agricultural red line policy. While much reclaimed land has been developed for ports, industry, and
housing, in some localities (Shanghai in particular), the construction of artificial wetland parks and
‘eco-cities’ indicates a move toward ‘restoration governance’ [
]. Such constructions also raise
questions regarding equal accessibility and mobility in cities with the emergence of privatization in
‘eco-urbanism’ [45].
In addition, this study also charted coastal land reclamation in relation to China’s major policy
reforms and it showed how reclaimed land has played a key role in revenue generation. The introduction
of guaranteed private property rights has also had an important eect in promoting construction of, and
over, reclaimed land [
]. High resolution nighttime light images and ground observations revealed
unique patterns of urbanization over recently reclaimed land (2014–2018); where much of the land
developed for housing had a low radiance value, whereas ports were accompanied by considerably
higher values. China’s modern vision of ecological conservation through the ERP (2015–2021) [
], as
well as MFZ (2010–2020) [
] needs to take reclaimed land into account and how these newly built
surfaces can contribute to its ‘eco-civilization’. In order to assess the impact of RSLR and plan for future
coastal flooding, future research needs to account for changes in coastal elevation that result from the
combined eects of seaward land extension and coastal land subsidence. Considering the current state
of knowledge on economic development, rapid urbanization, sea level rise, land subsidence, climate
change, and the increased frequency and magnitude of extreme events in coastal deltaic regions of
China [
], a detailed evaluation is overdue on how building new land systems at the coast aects
the levels of risk for people living or working in such localities is overdue. Google Earth Engine is a
powerful long-term analytical tool to this end.
Supplementary Materials:
The following are available online at,
Figure S1: Annual figures of coastal land reclaimed (km
) and rates of change for the nine cities (1990–2018); Color
gradations indicate annual rate of change for individual cities. Fluctuations can be explained where reclamation
of ‘land’ is followed by construction of water bodies, such as artificial lakes or reservoirs, in some cases these are
again replaced by vivid land use changes in the construction plan. [7].
Author Contributions:
D.S. and X.Z. processed the satellite GSW images; R.C., M.E.M. and Y.R.C. contributed to
the description and discussion of the policy and its relation to coastal land reclamation; A.B. contributed to the
statistical analysis and cartographic design; D.S. and M.E.M. led the writing of the paper; all authors analyzed the
results and contributed to the final version of paper.
This study has been conducted with the support from the National Key R&D Program of China
(2017YFC1503001), the National Natural Science Foundation of China [grant number 41771119], and the Research
Fund of the Laboratory of Marine Ecosystem and Biogeochemistry [grant number LMEB201713].
We are grateful for the insightful and constructive comments of Sally Brown, Jiayi Fang,
Indira Shridhar, Samantha Grusd and the anonymous reviewers. Authors would also like to acknowledge the
European Commission’s Joint Research Centre for building and maintaining Global Surface Water dataset.
Conflicts of Interest: The authors declare no conflict of interest.
Remote Sens. 2019,11, 2621 11 of 13
Appendix A
Google Earth Engine API codes:
Shoreline extraction using AWEI and OSTU thresholding method
GSW export image ‘No water’ class
GSW export image ‘seasonal water’ class
GSW calculate annual change in ‘No water’ and ‘seasonal’ bands
Linear Regression over time for Night time light data
Export NDVI and NDBI images
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... The seaward movement of defences should be appraised in terms of environmental impacts, especially impacts on ecosystems and biodiversity [6,7]. ATL is an extremely expensive approach that is rarely practised, but it has been increasingly used in 21st century mega-coastal land reclamation [13][14][15]. It requires expensive and specialized equipment, technology, and skilled human capital. ...
... This requires both continuous improvements and plans to adapt to future SLRs. Recent examples of ATL cited in the literature include the tree-shaped Palm Jumeirah Island in Dubai, international airports in Hong Kong, Macau, and Singapore, and mega smart city projects such as 'Eko Atlantic' in Lagos, Nigeria, and Songdo smart city, South Korea [13,15]. In recent global analysis of mega land reclamations, ATL is attributed to the rising demand for suitable land for agricultural, residential, commercial, or industrial developments in countries such as China, which led to the conversion of many tidal flats and coastal wetlands [13]. ...
... Recent examples of ATL cited in the literature include the tree-shaped Palm Jumeirah Island in Dubai, international airports in Hong Kong, Macau, and Singapore, and mega smart city projects such as 'Eko Atlantic' in Lagos, Nigeria, and Songdo smart city, South Korea [13,15]. In recent global analysis of mega land reclamations, ATL is attributed to the rising demand for suitable land for agricultural, residential, commercial, or industrial developments in countries such as China, which led to the conversion of many tidal flats and coastal wetlands [13]. ...
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Systematic literature reviews provide the foundation for evidence-based research in a particular field of study. In this regard, the systematic review of the relationship between coastal management strategies and coastal infrastructure typologies provides an opportunity to benchmark local coastal adaptation policies against contemporary global practices, technologies, and sustainability. However, systematic reviews of coastal infrastructure in Ghana and West Africa at large are limited. To close this research gap, we conducted a systematic literature review of the global implementation of coastal management strategies and coastal infrastructure and provided a synopsis of coastal management in Ghana. To achieve this, we searched the Scopus Database for literature on coastal management approaches and infrastructure typologies. Forty-eight peer-reviewed publications met the inclusion criteria for full-text analysis. The results indicate a significant global shift from purely grey infrastructure toward integrating green and grey infrastructure. However, despite contemporary global advances, coastal infrastructure in developing contexts—particularly in Ghana—remains mostly static, using reactive, hold the line strategies, and grey infrastructure. As sea-level rise continues to intensify coastal hazards globally, increasing the demand for coastal protection, researching coastal management policies and coastal infrastructure is essential to support the hybridization of grey and green infrastructure and encourage transitions to adaptive coastal management instead of continuous coastal hardening using grey infrastructure.
... The utilization of median compositing images by Xu and Gong (2018) failed to accurately delineate the seawater areas, leading to an underestimation of seaward land gains. Additionally, the limited robustness of threshold-based methods (e.g., Hu and Wang, 2022) and the constraints imposed by the accuracy of existing data (e.g., Sengupta et al., 2019) also resulted in a smaller area. While FADUS has been specifically optimized for coastal urban areas, it can also be applied to inland cities by excluding the tidal module. ...
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Accurate and timely monitoring of urban sprawl using remote sensing provides valuable insights for urban management and sustainable development. While existing studies have explored methods for large-scale monitoring of urban sprawl, most of them rely on the collection of manually labeled training samples for supervised classification. Additionally, previous studies generally focused on inland urban sprawl, neglecting the process of urban sprawl towards sea areas, known as seaward urban sprawl, which has profound ecological implications for coastal ecosystems. Here we develop a fully automatic algorithm for detecting urban sprawl, named Fully Automatic Detection of Urban Sprawl (FADUS), using the time-series Landsat imagery without manually collecting training samples or existing urban maps for reference. FADUS automatically generates initial samples through a sequential binary unsupervised clustering technique and then updates them by removing the spectral outliers to obtain a high-quality training set for subsequent supervised classification. A tidal module is included in FADUS to avoid pseudo-urban changes caused by tidal fluctuations so that both inland and seaward urban sprawl can be detected. By applying the algorithm to 75 coastal cities in China, the most rapidly urbanizing region in the world, we uncovered a neglected but dramatic seaward urban sprawl process that has converted sea areas to urban space since 1985. Our results indicate that 9904.36 km2 of coastal wetlands and nearshore seawater areas have been converted to land area, of which 44.83% is currently covered by built-up area. With our method, the fully automatic detection of urban dynamics is now possible for both coastal and inland cities worldwide. Our derived map of seaward urban sprawl in China provides valuable references for coastal land-cover change monitoring, wetland protection and restoration, and integrated coastal management.
... According to the United Nations report "World Urbanization Prospects" [6], urban areas grow by about 3 of 25 performed a pixel-based analysis in the GEE environment to monitor the urbanization processes in India. Sengupta et al. [39] proposed a study using the GEE and Landsat-5 satellite images to detect trajectories of coastal land reclamation in nine deltaic megacities. Zhang et al. [40] proposed a method that was based on Landsat-8 time series and vegetation indices in the GEE environment to map urban areas in three cities in China. ...
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This study analyzes, through remote sensing techniques and innovative clouding services, the recent land use dynamics in the North-Roman littoral zone, an area where the latest development has witnessed an important reconversion of purely rural areas to new residential and commercial services. The survey area includes five municipalities and encompasses important infrastructure, such as the “Leonardo Da Vinci” Airport and the harbor of Civitavecchia. The proximity to the metropolis, supported by an efficient network of connections, has modified the urban and peri-urban structure of these areas, which were formerly exclusively agricultural. Hereby, urban expansion has been quantified by classifying Landsat satellite images using the cloud computing platform “Google Earth Engine” (GEE). Landsat multispectral images from 1985 up to 2020 were used for the diachronic analysis, with a five-yearly interval. In order to achieve a high accuracy of the final result, work was carried out along the temporal dimension of the images, selecting specific time windows for the creation of datasets, which were adjusted by the information related to the NDVI index variation through time. This implementation showed interesting improvements in the model performance for each year, suggesting the importance of the NDVI standard deviation parameter. The results showed an increase in the overall accuracy, being from 90 to 97%, with improvements in distinguishing urban surfaces from impervious surfaces. The final results highlighted a significant increase in the study area of the “Urban” and “Woodland” classes over the 35-year time span that was considered, being 67.4 km2 and 70.4 km2, respectively. The accurate obtained results have allowed us to quantify and understand the landscape transformations in the area of interest, with particular reference to the dynamics of urban development.
... For this article, we assume that reclamation is a specific type of land intervention, which comes in different shapes and types, aims at different goals and relies on different kinds of justifications. For example, in Indonesia, the justification for reclamation is often coastal area protection and coastal zone management [23,24]. There are however historically, operationally and thematically additional motives for opting for reclamation projects. ...
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Whereas most contemporary frameworks evaluating land management aspects focus on institutional settings at a national level, the 8R framework of responsible land management aims at evaluating individual land management projects or interventions. This 8R framework is, however, still under development and needs testing, validation and further detailing, such that specific operational characteristics and internal and external effects can be included in the evaluation. This article addresses this need by demonstrating how the 8R framework could improve when knowing both the operational details and external effects of a land management intervention. By reviewing the documented implementation strategies and effects of eight different types of land reclamation cases in Indonesia, the article derives adaptations and extensions of the 8R framework assessment, such that the framework can better detect whether a specific project is sufficiently responsible in any of the 8R aspects. The induction shows that the number of types of systematic prompts needs to be extended and further detailed if it aims to capture and detect specific problems of structures, processes and impacts. Zooming in to documented reclamation projects in Indonesia shows that there are various types of such projects, which are oftentimes contested, yet each requires integrated land management and development strategies. Furthermore, they draw on dissimilar, mostly contextual, justifications and legal frameworks, which makes it difficult to compare the generic relevancy and sustainability of reclamation as a land management intervention tool. Nevertheless, testing the 8R framework for reclamation cases in Indonesia can improve its methodology and extent or specify the use of the systematic prompts designed to qualify and quantify the respective aspects.
... Various kinds of satellite image data are utilized to determine the morphodynamics of the coast [45,46]. Additionally, Sen Gupta [47] used the Google Earth Engine (GGE) platform, remote sensing images, and the Joint Research Center Global Surface Water dataset to assess the trend of coastal land reclamation in China's three main deltaic regions. Fung created a map illustrating the growth of Hong Kong from 1979 to 1987 using data from Landsat MSS and SPOT High Resolution Visible (HRV) [48]. ...
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The United Arab Emirate's rapid population growth is coupled with an increase in the consumption of natural resources such as fresh air, sunlight, land, and water. In the past two decades, the demand for land has augmented both away from the coast and significantly near the coast. Within coastal zones, artificial reclamation of land in the sea is the most desirable way to meet the demand for land necessary for the development of the most modern urban areas. Seaward reclamation (land in the water) necessitates the construction of artificially reclaimed areas that are extended into the sea using innovative modern construction techniques. The majority of these building requirements are necessitated by a number of key factors and have diverse outcomes. Even though this type of urban expansion is not new, the scale and motivations of land reclamation have been drastically altered due to geological and human-induced factors. The purpose of this paper is to assess the increase in seaward land expansion, particularly in the seven UAE coastal emirates. Using satellite data, particularly from 1990 to 2021, the total increase in land due to newly developed reclaimed areas in all UAE coastal emirates is calculated. Satellite images from the Landsat series are used to analyze the tremendous growth since the early 2000s. In addition, the study of shoreline maps of 1990, 2000, 2010, and 2021 for the seven emirates revealed that the 22 km long Ajman and UAQ front coast experienced a notable shoreline retreat with a net erosion area of 300 m 2 and an annual rate of 30 my −1 over the past 21 years (2000-2021). Depending on the type of construction design used to describe the process, methodical sorting is also recommended. The impacts of the Dubai offshore reclaimed islands on the adjacent coastlines in Ajman and Umm Al Quwain (UAQ), as well as the potential impact of earthquake tremors along the Zagros fold belt region, are the subjects of this study. In this study, all seven coastal emirates are considered, and the largest reclamation projects are located in Dubai, Abu Dhabi, Ras-Al Khaimah (RAK), and Fujairah, with Dubai leading the way; it has expanded its coastal areas by more than 68 km 2 at present, and another 35 km 2 will be reclaimed soon to finish Palm Deira. Citation: Subraelu, P.; Ebraheem, A.A.; Sherif, M.; Sefelnasr, A.; Yagoub, M.M.; Nageswara, K. Land in Water: The Study of Land Reclamation and Artificial Islands Formation in the UAE Coastal Zone: A Remote Sensing and GIS Perspective. Land 2022, 11, 2024.
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The superimposed effects of sea level rise caused by global warming and land subsidence seriously threaten the sustainable development of coastal cities. In recent years, an important coastal city in China, Zhuhai, has been suffering from severe and widespread land subsidence; however, the characteristics, triggers, and vulnerability assessment of ground subsidence in Zhuhai are still unclear. Therefore, we used the SBAS-InSAR technique to process 51 Sentinel-1A images to monitor the land subsidence in Zhuhai during the period from August 2016 to June 2019. The results showed that there was extensive land subsidence in the study area, with a maximum rate of −109.75 mm/yr. The surface had sequentially undergone a process of minor uplift and decline fluctuation, sharp settlement, and stable subsidence. The distribution and evolution of land subsidence were controlled by tectonic fractures and triggered by the thickness of soft soil, the intensity of groundwater development, and the seasonal changes of atmospheric precipitation. The comprehensive index method and the analytic hierarchy process were applied to derive extremely high subsidence vulnerability in several village communities and some traffic arteries in Zhuhai. Our research provides a theoretical basis for urban disaster prevention in Zhuhai and the construction planning of coastal cities around the world.
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Hefei’s gross domestic product (GDP) growth rate ranks first among all cities in China, and it was the fastest-growing city in China from 2000 to 2020. The high-speed economic development inevitably led to rapid changes in land cover types, e.g., an increment in artificial features (built-up) and decrement in natural features (vegetation). However, (1) many previous studies focus on the land cover change in metropolis or at the global scale, yet few focus on underdeveloped but fast-growing cities; (2) land cover studies mainly focus on global variations, yet seldom on local characteristics. Thus, it is of great significance to monitor the land cover change for the city with the fastest economic growth in China based on the long time-series satellite images from both global and local perspectives. In this study, with support from huge amounts of data (including 719 Landsat TM/ETM+/OLI satellite images, land surface temperature, nighttime satellite images, DEM, multiple land cover products, and various auxiliary data), processing and parallel computing abilities of the GEE platform, classification maps of land cover in Hefei from 2000 to 2020 are produced based on a random forest machine learning method, and the spatio-temporal variations and driving factors are analyzed from both global and local viewpoints. The results show that: (1) the classification accuracy is excellent; the average overall accuracy is 93% and the Kappa coefficient is 0.88; (2) the general spatio-temporal variations in land cover in Hefei from 2000 to 2020 are obvious; the built-up area expanded from 419.72 km2 to 1530.20 km2, with a total growth rate of 264.58%. With the expansion of the built-up area, the vegetation coverage decreased by 16.61% (1652.56 km2); (3) the land surface temperature shows an increment trend in the new town yet a decrement trend in the old town due to the change in vegetation coverage and the decentration of administration centers; further analysis shows that the population and the social economy are two driving factors for land cover changes. It is worth noting that both the area and coverage of vegetation in the old town and water body area in Hefei increased significantly, although the fast urbanization inevitably caused a decrement in vegetation and water area in the whole city, indicating both the high-speed economic development and improvement in green surfaces simultaneously experienced in Hefei from 2000 to 2020.
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Nighttime Light (NTL) data provides a measure of socio-economic development and is publicly available on the Google Earth Engine (GEE) cloud-based platform. The use of GEE to analyze NTL has expanded, but the trends remain unknown. In response, we provide a systematic overview of GEE-based NTL studies from its inception. We searched the Google Scholar database, which returned 359 articles, 73 of which were eligible. Results indicated NTL-GEE research has evolved into studies of urbanization, environmental, and socio-economic areas worldwide. Studies grew steadily since 2014 and peaked in 2021. VIIRS-DNB is the widely used product due to its superior properties to DMSP-OLS that followed, and the Luojia01-1 data is increasing, although not currently available on GEE. Almost two-thirds of NTL was used as the primary dataset and the remaining as auxiliary; along with daytime sensors. Overall, the NTL-GEE research has been a success and supported by many governments and institutions.
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The ability to repeatedly observe and quantify the changing position of the shoreline is key to present-day coastal management and future coastal planning. This study evaluates the capability of satellite remote sensing to resolve at differing temporal scales the variability and trends in shoreline position along sandy coastlines. Shorelines are extracted from 30 + years of publicly available satellite imagery and compared to long-term in-situ measurements at 5 diverse test sites in Europe, Australia, the USA and New Zealand. These sites span a range of different beach characteristics including wave energy and tide range as well as timescales of observed shoreline variability, from strongly seasonal (e.g., Truc Vert, France), to storm-dominated (e.g., Narrabeen-Collaroy, Australia), to only minor annual to multi-annual signals (e.g., Duck, USA). For the 5 sites, the observed typical horizontal errors varied between a root-mean-squared error (RMSE) of 7.3 m and 12.7 m. An analysis of the typical magnitudes of shoreline variability at temporal scales ranging from a single month up to 10 years indicates that, by the implementation of targeted image pre-processing then the application of a robust sub-pixel shoreline extraction technique, the resulting satellite-derived shorelines are generally able to resolve (signal-to-noise ratio > 1) the observed shoreline variance at timescales of 6 months and longer. The only exception to this is along coastlines where minimal annual to multi-annual shoreline variability occurs (e.g. Duck, USA); at these sites decadal-scale variations are successfully captured. The results of this analysis demonstrate that satellite-derived shorelines spanning the past 30 years as well as into the future can be used to explore and quantify intra- and inter-annual shoreline behaviour at a wide range of beaches around the world. Moreover, it is demonstrated that present-day satellite observations are also capable of capturing event-scale shoreline changes (e.g. individual storms) that occur at timescales shorter than 6 months, where this rapid response exceeds the typical magnitude of shoreline variability. Finally, several practical coastal engineering applications are presented, demonstrating the use of freely-available satellite imagery to monitor inter-annual embayed beach rotation, rapid storm-induced shoreline retreat and a major sand nourishment.
Conference Paper
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Coastline extraction is a fundamental work for coastal resource management and coastal environmental protection. Today, by using digital image processing techniques, coastline extraction can be done with remote sensing imagery systems. In this study, Landsat 8 Operational Land Imagery (OLI) data have been the main data source due to free access and sufficient spatial resolution for coast line extraction. This research is focused on determining the coastline length and measuring land area by using Landsat 8 OLI satellite image for Bodrum Peninsula, Turkey. Three commonly used methods have been applied in order to determine sea-land boundary line and its length, and area of the study area. The Automatic Water Extraction Index (AWEI), Iterative Self-Organizing Data Analysis Technique (ISODATA) unsupervised classification technique and on screen digitizing method was chosen for identification of coastal boundaries. Results of coastline length and land areas of Bodrum by using AWEI, ISODATA and on-screen digitizing are compared with each other. This study shows that with using optimal threshold value, AWEI can be used for coast line extraction method with coherently for Landsat 8 OLI satellite imagery. The overall results show that coastline extraction from satellite imagery can be done with sufficient accuracy using spectral water indices instead of time consuming on-screen digitizing.
As one of the first countries to implement marine spatial planning, known in China as marine functional zoning (MFZ), China has developed MFZ into an integral part in its territorial spatial planning. Today, MFZ has become an important basis for the development, regulation and integrated management of marine space as well as an important tool for the management of its sea area, the protection of the marine environment, and development of its marine economy. This paper reviews China's MFZ system from a perspective of institutions, technologies and management requirements, and studies the resultant effects of MFZ in applications for sea-use projects, marine environmental monitoring and marine ecosystem protection by means of quantitative and comparative analysis. It is concluded that China's MFZ promotes the rational allocation of marine resources and the coordination of marine spaces for social and economic development based on its important role in sea-use project approval, marine environmental monitoring, and marine environmental protection. After three generations of evolution, it has formed a relatively mature classification system, technical system and institutional arrangement for China's MFZ with targets specified at three administrative levels and management requirements defined for different marine functional zones, which in turn facilitate the implementation of MFZ. China now is aiming to build the next generation of MFZ into a land and sea integrated zoning plan guided by the principles of ecosystem-based management. The well-established institutional arrangement and technical systems of MFZ, and the experiences accumulated in practice are available for reference by other countries.
Aquaculture is one of the fastest growing animal food production sectors mainly developed in fertile coastal areas. Monitoring and mapping of aquaculture ponds are of utmost importance for the sustainable management of coastal ecosystems. In this study, an integrated updating and object-based classification approach was developed to generate maps of coastal aquaculture ponds in China from 1984 to 2016 at 30-m spatial resolution. The current extent and change of coastal aquaculture ponds in China were analyzed over the course of 32 years. In addition, spatial-temporal dynamics of coastal aquaculture ponds were examined by buffer and overlay analyses. The results showed that the total area of coastal aquaculture ponds in China expanded by 10,463 km 2 , with the largest gain occurring from 1990 to 2000 (4,207 km 2). The coastal provinces of Guangdong, Shandong, Jiangsu, Liaoning, and Hebei had significant increases of aquaculture ponds areas, accounting for 83% of totally expanded ponds in the coastal zone of China. Rapid expansion of coastal aquaculture ponds was observed in the 0-10 km inshore buffer and the loss of wetlands and arable land contributed more than 50% to the expansion. Socioeconomic factors helped drive the continual increase of coastal aquaculture ponds in China. Scientific environmental regulations and planning and management strategies at the national and international policy levels should be enhanced to consider the ecological impacts of aquaculture expansion.
Little information is available on the impacts of coastal reclamation on wetland loss in large-river deltas at a regional scale. Using remote sensing data of coastal wetland and reclamation in four deltas in China from 1978 to 2014, we tracked their continuous area changes in four periods: 1978–1990, 1990–2000, 2000–2008, and 2008–2014. The areal relation between wetland loss and reclamation was quantified and used to identify coastal reclamation mode intensity coupled with another three indicators: reclamation rate, accretion rate and land-use intensity of coastal reclamation. The results showed that coastal reclamation driven by economic development reduced, or even reverse the original growth of delta which was determined by the offset between wetland acceleration rate and wetland loss rate. Generally, the area of reclamation showed a positive linear correlation with the area of wetland loss. The findings imply that human activities should control reclamation rate and intensity to alleviate total wetland loss and maintain wetland ‘net gain’. Inappropriate coastal reclamation modes can magnify total wetland loss; therefore, coastal reclamation with a slow increment rate and low impervious surface percent is of great importance for sustainable development in future coastal management.
Other nations could learn from China’s red-line initiative to preserve nature, biodiversity and ecosystem services in the country, says Jixi Gao. Other nations could learn from China’s red-line initiative to preserve nature, biodiversity and ecosystem services in the country, says Jixi Gao. “Locals want a better life and cleaner land more than an increase in GDP.”
Deltas are the most productive and economically important global ecosystems, associated with some of the largest coastal marine fisheries and the majority of global coastal wetlands. They are often regions of intense economic activity. Because of their ecological richness, deltas support the highest values of ecosystem goods and services in the world. We synthesize information presented on deltas in this book and elsewhere and discuss how individual deltas will fare given the given global megatrends of the 21st century. Deltas formed over the past several thousand years after sea level stabilization following the end of the last glacial epoch during a period of relatively stable sea level, predictable and regular input from drainage basins, and a high degree of interaction within its hinterland, drainage basins, river channels, the deltaic plain, and the coastal ocean. The functioning and sustainability of deltas depend on regular and episodic, external and internal, inputs of energy and materials that produce benefits over different spatial and temporal scales. Deltas are among the most threatened coastal ecosystems because human impacts have fundamentally changed the environmental setting of deltas. Deltaic sustainability can be considered from geomorphic, ecological, and economic perspectives. Here we build on earlier work to examine the sustainability of a subset of deltas presented in this book. Roughly running from less to more sustainable are deltas in arid environments, deltas with highly energy-intensive management and flood defense systems, deltas with significant areas below sea level, arctic deltas, tropical and subtropical deltas with growing human impact, deltas with relatively low energy management, and tropical deltas with relatively low human impact and high freshwater input. Using the database and approach of Giosan and colleagues, we consider the sustainability trajectory of individual delta given their ability to survive sea level with changing sediment input and environmental setting. Deltas with increasing aridity will likely cease to function as deltaic systems. Large deltas with sufficient freshwater input will lose wetlands and become dominated by large expanses of shallow water in a process of estuarization.
Decisions about future land use are complex and involve a wide range of factors. The perceptions, intentions, and interests of the stakeholders involved are usually unpredictable. Different stakeholders manage land by choosing different future options and revealing different expectations. Greater proximity to built-up areas confronts farmers with challenges about future land use and land cover change (LUCC). This study aims to identify how external drivers can affect farmers’ future LUCC intentions focusing on conversion of agricultural land to urban development. We explore two scenarios projected for the time horizon of 2025 based on farmers’ LUCC intentions: A0 – current social and economic trend; and B0 – increasing demand for urban development. We selected the Torres Vedras municipality (Portugal) as case study, an area predominantly agricultural but with a progressively urban intensification in the past two decades. We conducted interviews to capture the farmers’ LUCC intentions and modelled an artificial neural network – a multilayered perception to allocate the potential areas for urban development. Parishes with the highest urban pressure were identified using a cluster analysis. These were compared with areas expected to be urbanized (defined in the master plan). Results suggest an increasing farming intensity in the A0 scenario, and an urban growth increase of more than 40% in the B0 scenario, with negative impacts on farming expansion. The outcomes can be applied to spatial planning instruments in order to assist planners to define land transformation priorities and adjust them to spatial trends.