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Unplanned urban growth, particularly in developing countries has led to changes in land use/land cover (LULC). Numerous Indian cities face problems of unplanned LULC change due to nominal or non-existent planning efforts compounded by rapid urban population growth. The Guwahati Metropolitan Area (GMA) is one such urban centre. The present study assesses the trajectories of LULC change using Landsat imageries acquired in 1976, 1989, 2002 and 2015. Natural and semi natural vegetated area and artificial and natural water bodies decreased while built-up areas, cultivated and managed areas, and natural and semi natural non-vegetated areas increased. The built-up area increased from 23.9 in 1976 to 115.1 km² in 2015 becoming the dominant land cover class accounting for 41.8% of the total geographical area. During this period, natural and semi natural vegetated land were reduced by 88.9 km² at an annual rate of 2.2 km². Over the years there was an increasing trend of built-up land and cultivated and managed areas in the peripheral areas of the city while natural and semi natural vegetated land diminished. Consequently, as in many other developing countries, there is an urgent need for the governmental authorities and other stakeholders to implement effective urban planning policies.
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Geografisk Tidsskrift-Danish Journal of Geography
ISSN: 0016-7223 (Print) 1903-2471 (Online) Journal homepage:
Unplanned urban growth: land use/land cover
change in the Guwahati Metropolitan Area, India
Chandra Kant Pawe & Anup Saikia
To cite this article: Chandra Kant Pawe & Anup Saikia (2018) Unplanned urban growth: land use/
land cover change in the Guwahati Metropolitan Area, India, Geografisk Tidsskrift-Danish Journal of
Geography, 118:1, 88-100, DOI: 10.1080/00167223.2017.1405357
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Published online: 26 Nov 2017.
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VOL. 118, NO. 1, 88100
Unplanned urban growth: land use/land cover change in the Guwahati
Metropolitan Area, India
Chandra KantPawe and AnupSaikia
Department of Geography, Gauhati University, Guwahati, India
Unplanned urban growth, particularly in developing countries has led to changes in land use/land
cover (LULC). Numerous Indian cities face problems of unplanned LULC change due to nominal
or non-existent planning eorts compounded by rapid urban population growth. The Guwahati
Metropolitan Area (GMA) is one such urban centre. The present study assesses the trajectories of
LULC change using Landsat imageries acquired in 1976, 1989, 2002 and 2015. Natural and semi
natural vegetated area and articial and natural water bodies decreased while built-up areas,
cultivated and managed areas, and natural and semi natural non-vegetated areas increased. The
built-up area increased from 23.9 in 1976 to 115.1km2 in 2015 becoming the dominant land cover
class accounting for 41.8% of the total geographical area. During this period, natural and semi
natural vegetated land were reduced by 88.9km2 at an annual rate of 2.2km2. Over the years there
was an increasing trend of built-up land and cultivated and managed areas in the peripheral areas
of the city while natural and semi natural vegetated land diminished. Consequently, as in many
other developing countries, there is an urgent need for the governmental authorities and other
stakeholders to implement eective urban planning policies.
1. Introduction
Within a mere quarter of a century, the world population
has increased at a rapid rate from 5 billion in 1987 to 6 bil-
lion in 1999 and to 7 billion in 2011 (Haub & Gribble, 2011).
As part of this development, cities in the developing world
have undergone rapid urban expansion (Singh, 2013) and
this has generated tremendous pressure on land from both
unplanned and uncontrolled changes in land use/land
cover (LULC) (Seto et al., 2002). Additionally, urban sprawl
in most metropolitan areas, whether planned or not, put
pressure on ecosystems in peri-urban areas (Colantoni,
Grigoriadis, Sateriano, Venanzoni, & Salvati, 2016) contrib-
uting to LULC being one of the most important causes
of global environmental change (Chase, Pielke, Kittel,
Nemani, & Running, 1999; Houghton, Hackler, & Lawrence,
1999; Sala et al., 2000; Wu, Liu, Sohl, & Young, 2013).
Substantial LULC change is thus occurring in and around
cities, and small and medium-sized cities with populations
between 500,000 and 5million are the ones growing fast-
est. Population here is projected to rise by more than 32%
between 2015 and 2030 compared to 26% in large and
megacities (Birkmann, Welle, Solecki, Lwasa, & Garschagen,
2016). The secondary cities perform vital governance,
logistic and production functions at a sub-national or
sub-metropolitan region level within a system of cities in a
country (Roberts & Hohmann, 2014). Nearly half of the 100
million new urban residents expected in India by 2030 will
be living in secondary or mid-sized cities such as Agartala,
Imphal, Tiruppur and Tirupati, whereas one-quarter will
add to the population of the nation’s four megacities: Delhi,
Mumbai, Kolkata and Bangalore (Birkmann et al., 2016).
Urban policy research has traditionally focused on large
metropolitan cities and tended to pay less attention to
secondary (Andreasen, Agergaard, Kiunsi, & Namangaya,
2017), mid-sized (Tossonyi, 2017) or small cities (Bell &
Jayne, 2006, 2009). This is in spite of growing evidence
of the importance of mid-sized cities in contributing to
national economies (Bolton & Hildreth, 2013) and second
ary cities are projected to have a greater inuence upon
the future economic development of nations and larger
geographic regions (Roberts & Hohmann, 2014).
The Guwahati Metropolitan Area (GMA), the largest city
in north-east India, is one such example of a secondary
city and like numerous Indian cities it faces problems of
unplanned LULC change due to nominal or non-existent
planning eorts compounded by rapid urban population
growth. Ever since the capital of the state of Assam, India,
was shifted to Dispur, a locality within Guwahati, in 1972,
© 2017 The Royal Danish Geographical Society
Remote sensing; GIS; land
use/land cover change;
urban expansion; Guwahati
Metropolitan Area (GMA)
Received 20 June 2017
Accepted12 November 2017
CONTACT Anup Saikia
make up the GMA. The city is built on a landscape featuring
three broad geomorphic units: residual hills, alluvial plains
and marshy lands including water bodies. Nearly 60% of
the city’s total area is less than 60m amsl with the rest vary-
ing between 60–410m amsl (Phukan, Chetia, & Das, 2012).
Granitic gneisses, quartzites and granites are the dominant
rock types in the highlands, while Pleistocene-Holocene
sediments dominate the intermontane valleys (Das, Ray, &
Nain, 2014; Maswood,1982; Phukan et al.,2012).
The GMA consists of the Guwahati Municipal
Corporation (GMC) area, the North Guwahati Town
Committee (NGTC) area, the Amingaon Census Town
(ACT) and 21 revenue villages encompassing a total area of
275.0km2. Although this area accounts for only 1% of the
total area of north-east India, it is regarded as the gateway
to NER India because of its strategic location and economic
importance (Figure 1).
3. Methodology
3.1. Data
Due to the establishment of Guwahati as the capital of
Assam in 1972 and the availability of satellite data shortly,
thereafter, the time frame of the study spans from 1976 to
2015 over a period of 39years. Landsat MSS, Landsat 5 TM,
Landsat 7 ETM and Landsat 8 OLI TIRS satellite imagery at
13 year intervals were used in this study. These images
were obtained during the dry season (October to March)
since the study area tended to remain cloudy during the
monsoon season (April to September). Other reference
materials used in the study were a classied LULC map
of Guwahati in 1990 prepared by the Assam Remote
Sensing Application Centre (ASTEC), topographical maps
of Guwahati city (1967–1968 and 2003–2004) collected
from the Survey of India Oce, Guwahati and the GMDA
boundary map gathered from the Oce of the GMDA,
Guwahati and Google Earth images (Table 1).
3.2. Data pre-processing
Using ArcGIS 9.3 software (, the study area
boundary map was scanned and converted into a digital
raster image. It was geometrically rectied, using the near-
est neighbour resampling algorithm, and geo-referenced
to UTM Zone 46 North and WGS 84 datum. Consequently,
through on-screen digitization, the GMDA boundary vec-
tor layer was created which was used to subset the Landsat
imageries corresponding to the study area. In order to
match all the datasets to same pixel size, the 60×60m
Landsat MSS data was resampled to 30×30m pixel and
the snap raster function was used to resolve the problem
of pixel mismatch.
the city began receiving a large inow of people from
nearby areas. Between 1971 and 1991, the population of
Guwahati increased from 293,219 to 646,169 at a com-
pound annual growth rate of 4.0%. By 2011, when the last
decadal census was held, its population reached 968,549
and currently the city probably has well in excess of a mil-
lion people. Guwahati is recognized as the most important
city in north-east India (Anon, 2006) and plays a key role in
India in terms of geographical and strategic signicance.
Recently, under the Smart City Mission of Ministry of Urban
Development (MoUD), Government of India, the city was
among the top 20 cities of India to be developed as “smart
cities” (Anon, 2016). It is being touted as the lynch pin to
India’s Act East Policy and the gateway to South-East Asia
(Anon, 2017; Choudhury & Barua, 2001; Sarma, 2007). This
has increased the need for proper urban planning and e-
cient environmental management of the city.
Against this background, the objective of this study is
to quantitatively characterize the trajectories of land use/
land cover change in Guwahati city as an example of how
mid-sized cities cope with unplanned urban expansion.
The study integrates remote sensing (RS) and geographic
information system (GIS) technologies to quantify and
assess LULC dynamics in the GMA as these are widely rec-
ognized as eective tools for identifying and mapping land
use change in dierent areas such as metropolitan areas
(Sharma & Joshi, 2013; Xie, Fang, Lin, Gong, & Qiao, 2007;
Yang & Lo, 2002).
2. Study area
The GMA is situated on the banks of the Brahmaputra
River in north-east India. It is under the jurisdiction of the
Guwahati Metropolitan Development Authority (GMDA)
the boundary of which extends between 26°2 N to 26°16
N latitude and 91°33 E to 91°52 E longitude. The city has
an undulating topography, with an elevation varying from
49.5 to 55.5 m.a.s.l. Interspersed with a large number of
hills which are mostly covered with forests and some
exposed rocky surfaces (Yadav & Barua, 2016), the GMA
has a number of wetlands, locally known as “beels”. Some
prominent wetlands are Deepor beel, Silsako beel, Bosrsola
beel and Rangagra beel, of which the rst is a Ramsar wet-
land. The city is characterized by a warm humid climate
with precipitation (200–350mm/year) concentrated dur-
ing the summer monsoon months from July to October.
The temperature varies between 12 and 14°C in winter
to 30–37°C during a wet summer season, with humidity
remaining high throughout the year barring a brief two-
month spell of winter during December and January. Low
Precambrian residual hills and inselbergs interspersed with
elongated low lying valley lls, marshes and wetlands
3.3. Image classication and accuracy assessment
Based on eld work and visual interpretation of each sub-
set-image, a supervised classication was performed using
a maximum likelihood classier for the Landsat data-sets
to extract the land use/land cover characteristics of the
region. The number of observations per cluster was kept to
Figure 1.Location of the study area. Source: Authors.
4. Results and discussion
4.1. Land use/land cover change
The LULC classication results are summarized for the
years 1976, 1989, 2002 and 2015 in Table 3. It is evident
that natural and semi-natural vegetated area was the pre-
dominant land cover class in 1976. However, these areas
have been placed under increasing pressure from built-up
areas and cultivated and managed areas. This reduced the
percentage of natural and semi natural vegetated areas
from 61.0% in 1976 to 28.7% in 2015. This land cover class
decreased at a rate of 2.2km2 per year. On the other hand,
built-up areas have increased from 23.9km2 in 1976 to
in 2015 at a rate of 2.3km
per year. Incidentally,
the rate of gain in built-up areas and the rate of loss in
natural and semi-natural vegetated areas were approxi-
mately the same. Thus, over the years much of the increase
in built-up areas occurred at the expense of natural and
semi-natural vegetated areas. Additionally, over the years
small patches of built-up land emerged in areas inside the
notied reserved forests (RFs) and demarcated hills areas
within the city limits. Protected areas in India are classied
into National Parks, Wildlife Sanctuaries and RFs of which
the latter are not well protected and hence frequently
encroached upon. In RFs within the GMA encroachments
are made predominantly by the urban poor. In 2001, it was
found that a population of around 170,000 was residing in
the city hills (Borah & Gogoi, 2012). However, in addition
to the urban poor, unauthorized encroachment of some
pockets of land by commercial entities, such as high-end
hotels or wealthy urbanites had also occurred (Borthakur,
2017). Due to the concentrated human population, nearly
everything people do in urban areas has ecological impli-
cations (Forman, 2014). Urban expansion alters a city’s “big
seven”: natural vegetation; agricultural land; clean water;
jobs; housing; transport; and communities (Forman & Wu,
2016) albeit unequally by residents disaggregated on the
basis of economic strata. Among the urban poor, living
in informal settlements, soil erosion is often a problem in
partly because their houses are situated on steep slopes
(Forman, 2014). In the hill slopes of Guwahati, where
the informal settlements are located, mudslides are not
uncommon following periods of incessant precipitation.
Often lives are lost as poorly built structures and makeshift
a minimum of 30 per band (Janssen & Huurneman, 2001)
and it was ensured that clusters in the data did not overlap
(Saikia, Hazarika, & Sahariah, 2013). In adopting this classi-
cation system emphasis has been on increasing exibility
while maintaining mapability. Flexibility was identied as
the ability of the classication system to able to illustrate
enough classes to cope with the real world with a clear
and strict class boundary denition. Mapability is the abil-
ity of the classication system to dene a clear boundary
between two classes. Given the multi-functional land use
pattern of the Guwahati city (Borah & Bhagabati, 2015) and
the spatial resolution of the remote sensing data used, ve
LULC classes were identied to comprehensively record
the physical and cultural fabric of the study area. The pro-
posed LULC classes were based on the land cover classi-
cation scheme designed by the Food and Agricultural
Organization (Di Gregorio & Jansen, 2000; Latham, He,
Alinovi, DiGregorio, & Kalensky, 2002) (Table 2).
It was observed that some of the landscape features
were misclassied as they exhibited similar spectral sig-
natures. Such issues were resolved through a recoding
process with the help of reference images considered in
the study along with ground truth verication. An accu-
racy assessment was performed with a set of 40 random
ground points for each LULC class and for each year con-
sidered (1976, 1989, 2002, 2015). Overall accuracies of
85.25% (κ=0.75), 85.71% (κ=0.77), 87.72% (κ=0.83) and
89.83% (κ=0.86) for the 1976, 1989, 2002 and 2015 images
respectively were achieved. For a remotely sensed data-set
an overall accuracy of 85% is generally deemed satisfac-
tory (Anderson, Hardy, Roach, & Witmer, 1976). Finally, the
Land Change Modeler (LCM) module of TerrSet (https:// was employed, following previous
studies (Evans, 2017; Sudhakar Reddy et al., 2017; Zhang,
Estoque, & Murayama,2017), to analyse the dierent
aspects of land cover change in the study area.
Table 1.Satellite data used in the study.
Satellite Resolution (m) Path/row Observation date
Landsat 2 MSS 60 147/042 December 16,
Landsat 5 TM 30 137/042 March 9, 1989
Landsat 7 ETM 30 137/042 February 17, 2002
Landsat 8 OLI TIRS 30 137/042 March 17, 2015
Table 2.The land cover classification scheme.
Land cover classes
Artificial and natural water bodies Areas covered with water such as rivers, lakes, streams, reservoirs, canals, tanks, etc.
Built-up areas Areas covered with impervious surfaces like residential, commercial, industrial, transportation &
Natural and semi-natural vegetated Areas covered with vegetation such as forest, shrub land areas.
Cultivated and managed areas Areas covered with vegetation of anthropogenic origin which requires human activities to maintain it
such as croplands, orchards, plantation, fallow lands, etc.
Natural and semi-natural non-bare vegetated areas Areas that do not have vegetation cover such as sandy areas, bare vegetated areas.
population for the specic years viz. 1976, 1989, 2002 and
2015 were extrapolated on the basis of the compound
annual growth rate of the preceding year (Figure 2).
The cultivated and managed areas as well as the nat-
ural and semi-natural non-vegetated areas increased,
while articial and natural water bodies were reduced
from 11.9% in 1976 to 8.1% in 2015. Between 1976 and
2002 cultivated and managed areas increased by 15.2km
between 1976 and 2002, before subsequently falling by
9.3km2. This decline can be attributed to the increasing
pressure from the expansion of built-up areas.
Thus, over a period of 39years, a landscape dominated
by natural and semi-natural vegetated areas was steadily
transformed into a landscape with an extensive built-up
area. A vertical growth of the city also occurs, however, this
was not within the ambit of the present analysis (Figure 3).
As in Arusha, Tanzania, where migration is a central
dynamic that shapes urban transformation processes
(Andreasen et al., 2017), pull factors encourage migration
of the low income population from neighbouring areas
into the city of Guwahati. The relative lack of develop-
ment and income opportunities outside of agriculture
houses at tenuous hillside locations get buried by mud-
slides. 60 people lost their lives following landslides in
the hills of Guwahati during 2000–2007 (Das et al., 2014).
These informal settlements often lack access to basic
amenities such as drivable or all weather roads, piped
water supply and electricity. Guwahati is hardly unique in
these respects. Elsewhere too, the urban poor are forced
to occupy land illegally. They build their homes in infor-
mal human settlements (Aguilar & Guerrero, 2013) since
their housing requirements are rarely addressed eectively
(McGranahan, Mitlin, & Satterthwaite, 2008). A strong asso-
ciation between the expansion of illegal urban settlements
and socioeconomic factors, such as unemployment, has
been noted (Aguilar & Guerrero, 2013; Lopez, Heider, &
Scheran, 2017) and this is true for the urban poor of
Guwahati as well.
Between 1976 and 1989 the population grew by 67.1%
while the area of built-up land grew by 84.9%, indicating
a higher rate of land development in terms of population
growth. Subsequently, during 2002–2015, the rate of land
development further accelerated as the growth rate of
built-up land exceeded population growth fourfold. The
Table 3.LUCC classification in the GMA, for various years.
categories 1976 1989 2002 2015 % cover 1976 % cover 1989 % cover 2002 % cover 2015
Rate of gain/loss
Artificial and natural
water bodies
32.7 27.8 22.2 22.3 11.9 10.1 8.0 8.1 −03.0
Built-up 23.9 44.2 67.0 115.1 8.7 16.1 24.3 41.8 +2.3
Natural and semi-
natural vegetated
167.9 142.0 118.2 78.9 61.0 51.6 42.9 28.7 −2.2
Cultivated and
managed areas
47.8 57.6 63.1 53.8 17.4 20.9 22.9 19.5 +0.1
Natural and semi-
natural non-vegetated
areas (area in km2)
2.4 3.2 4.4 4.7 0.8 1.1 1.6 1.7 +0.1
Figure 2.Proportion of various LULC categories. Source: Authors.
managed areas registered a net loss of 39.2 and 9.2km2,
respectively, amounting to a total loss of 48.5km2.
It is evident that in recent years the built-up area has
expanded into areas which were previously either natural
vegetated or human induced vegetation managed land.
Most importantly, the cultivated and managed areas which
showed a steady rise between 1976 and 2002 experienced
a decline of 17.2% in their areal extension during 2002–
2015. In the last decade or so, a considerable number of
cultivated and managed areas have been transformed to
built-up area (Figure 4).
4.3. Contribution to net change in land use/land
cover classes
The contribution of land use/land cover classes to net
change in a particular class have been summarized in
Table 5. Here, the analysis has been performed for only
three land cover classes: built-up, natural and semi-nat-
ural vegetated areas and cultivated and managed areas.
The reason for this is that the remaining land cover classes
showed insignicant variations. The growth in built-up
area was compensated for by the decrease in natural and
semi-natural vegetated area and cultivated and managed
area (Table 5). Between 1976 and 2015, an area of 51.2km2
in neighbouring rural areas serve as push factors to the
largest city in north-east India. In the state of Assam, 45%
of rural households are still without electricity (Palit &
Bandyopadhyay, 2017). Moving to the only large city is a
way out of darkness.
With land rent and housing being high towards the
city centre, such migrants have no choice but to set-up
informal housing near the outer limits of the city. Despite
this, there is a “lack of political will to mitigate this problem
... and to attack the structural causes of illegality, social
insecurity, and the environmental degradation (Aguilar
& Guerrero, 2013) associated with informal human settle-
ments (IHS).
4.2. Net change in land use/land cover classes
The net change experienced by each land use/land cover
category during the time periods considered (1976–1989,
1989–2002 and 2002–2015) are presented in Table 4.
Throughout the study period, built-up areas experienced
the highest net gain compared to all other land cover
classes. The period 2002–2015 recorded a net gain in this
category of 48.1km2 which was more than double that of
the previous period (22.7km2). During this time, natural
and semi-natural vegetated areas as well as cultivated and
Figure 3.The classified images for 1976, 1989, 2002 and 2015. Source: Authors.
was due to the development of natural and semi- natural
vegetated areas while the losses in the same category can
be attributed to the increase in built-up area. Between
1976 and 2002, the cultivated and managed land gained
more land from natural and semi-natural vegetated areas
(28.6km2) than it lost to built-up area (15.1km2). However,
during 2002–2015 a greater proportion of cultivated and
managed areas were developed to built-up area while con-
siderably less was added from natural and semi-natural
vegetated areas. This indicated that between 1976 and
2002, the natural and semi-natural vegetated land was
being transformed to cultivated and managed areas that
were later converted to built-up land. However, in recent
years the land transformation process has intensied as
of natural and vegetated areas was converted to built-up
area. In comparison, 38.4km2 of cultivated and managed
areas were developed into built-up area, but the transfor-
mation rate showed an increasing trend over the years
indicating that the former would be under serious pressure
from built-up area in the years ahead.
Of all the land cover classes, the natural and semi-natu-
ral vegetated area class has suered maximum deteriora-
tion. The pre-dominant natural and semi-natural vegetated
area was reduced by 94.1km2 by 2015, of which 42.8km2
was transformed to cultivated and managed areas. The
changes in cultivated and managed areas provide an
insight into the land transformation process occurring in
the study area. The gain in cultivated and managed areas
Table 4.Changes in LULC in the GMA.
categories 1976–1989 1989–2002 2002–2015 % change 1976–1989 % change 1989–2002 % change 2002–2015
Artificial and natural water
−4.9 −5.6 +0.1 −17.5 −25.3 +0.4
Built-up +20.3 +22.7 +48.1 +45.8 +33.9 +41.7
Natural and semi-natural
vegetated areas
−25.9 −23.7 −39.2 −18.2 −20.1 −49.7
Cultivated and managed
+9.7 +5.5 −9.2 +16.9 +8.7 −17.2
Natural and semi-natural
non-vegetated areas (area
in km2)
+0.7 +1.1 +0.3 +23.4 +27.1 +6.6
Figure 4.LULC based on percentage of change for the three time periods. Source: Authors.
Table 5.Contribution to net change in the LULC categories for different periods.
Landuse/landcover categories
Built-up Natural and semi-natural vegetated areas Cultivated and managed areas
76–89 89–02 02–15 76–89 89–02 02–15 76–89 89–02 02–15
Artificial and natural water bodies +0.34 +0.44 +0.53 +3.41 +2.73 +0.03 +0.92 +0.83 −0.35
Built-up 0 −14.45 −12.59 −24.25 −5.45 −9.68 −23.29
Natural and semi-natural vegetated areas +14.45 +12.5 +24.25 0 +14.34 +14.29+14.21
Cultivated and managed areas +5.45 +9.68 +23.29 −14.34 −14.29 −14.21 0
Natural and semi natural non-vegetated areas
(area in km2)
+0.09 +0.04 +0.05 −0.54 +0.36 −0.82 −0.05 +0.05 +0.14
Figure 5.(a) Important landmarks and (b) concentric circles from the city centre within GMA. Source: Authors.
Figure 6.LULC change and distance from the city core for (a) Built-up (b) Natural and semi natural vegetated area and (c) Cultivated and
managed area categories. Source: Authors.
Silsako beel, Jalukabari, Amingaon and North Guwahati
were aected by this.
Much of the vegetated area was concentrated between
a 2500 and 12,000m zone of RFs and hills (Figure 6(b)).
During 1976–2015 these vegetated areas were reduced
considerably as a result of encroachment of low income
residential pockets in the hills and RFs grew. In the sum-
mers that follow a period of torrential or sustained precip-
itation, mudslides in these hills are not uncommon; often
leading to loss of human lives. Towards the city periphery,
the vegetation cover was drastically aected due to con-
version to built-up and cultivated and managed areas for
various commercial or educational purposes.
The cultivated and managed area curves were nar-
rowly juxtaposed indicating that over the years this land
cover class has been comparatively less aected. However,
between 2002 and 2015, signicant amounts of cultivated
and managed areas were lost in the 4000–9500m zone
while a large area was gained from 13,000m and outwards
till the GMA boundary limits. This would seem to indicate
that the pressure on cultivated and managed areas tends
to decline away from the city centre.
How do the residential areas get subsumed by the
urban expansion? Do such areas get developed prior to
or following the settlement of residents? The new residen-
tial areas are not “developed” per se, but rather illegally
settled upon. These settlements tend to be located on the
hill slopes of the city, lightly wooded areas, the fringes of
protected areas or vacant government land. They remain
undeveloped and over time minimal facilities are extended
to these areas. In sample areas surveyed, a single water
pipeline served a handful of informal homes with water
being pumped illegally from nearby for an undisclosed
petty bribe, almost as a form of monthly rent. Likewise,
a considerable amount of both natural and semi natural
vegetated land and cultivated and managed land has been
directly converted to built-up area (Table 5).
4.4. Land use/land cover change with distance
In this section, the distribution of land use land cover
classes in terms of distance from the city centre is exam-
ined. The Fancy Bazar area (Figure 5(a)), which is one of
the oldest business areas of Guwahati city was considered
as the city core. In the analysis 40 concentric circles with
widths of 500m each were created emanating from the
city core (Figure 5(b)). The distance between city core and
up to 8000m out included the major urban centres within
the city, the area between 8000 and 13,000m out con-
tained the municipal boundary areas and areas further out
than 13,000m represented the city’s outermost limits. The
analysis was conned to built-up, natural and semi natural
vegetative area and cultivated and managed area only, as
the other classes exhibited insignicant variations.
The built-up curves of each year showed similar pat-
terns over the study area with increasing distance from the
city centre. A high built-up concentration was observed
within 8000m as most of the urban centres are situated
inside this belt. The area between 8000–13000m con-
tained the city hills and major waterbodies, and with that
the area of built-up land in this zone declined signicantly.
Beyond 13000m and out to city limit the distribution of
built-up area was mainly connected tothe city airport and
a number of defence establishments. During 2002–2015
the expansion of built-up land had accentuated in the
area between 4000 and 10000m from the city core most
likely due to a large extent of built-up area cropping up in
some previously unoccupied tracts. Fringe areas like the
Figure 7.Low income informal settlements in the peripheral areas of the GMA. Most tin-roofed houses lack electricity, piped water
supply, sanitation facilities and metalled all-weather roads. Source: Authors.
Cowan, & Sheppard, 2017) and the fact that a sharp loss of
vegetated areas occurred in the GMA is a matter of concern
and one that requires attention and monitoring.
Although the GMDA has a city Master Plan-2025
(GMDA, 2009), its lack of implementation has seen a rise
in illegal settlements inside the notied reserved forests
and hills within the study area. Rapid population growth
has pushed the expansion of the urban areas in south-
ern Guwahati into the suburban areas and most of these
expansions are unplanned (Borbora & Das, 2014). With
incremental reductions in green cover stemming from
urbanization, the phenomenon of a summer urban heat
island (UHI) eect of over 2o C has occurred in the GMA
(Borbora & Das, 2014).
The LULC change analysis seen in relation to distance
from the city centre explored key information on the issue
of urban sprawl in the GMA. It was observed that towards
the city periphery the built-up as well as the cultivated and
managed areas increased over the years while natural and
semi-natural vegetation recorded signicant losses. These
unplanned built-up establishments have emerged along
the national highways 31 and 27 which pass through the
south and south-west ends of the city, respectively. There
is an urgent need for an action plan focusing on identi-
cation of illegal settlements and built-up establishments
to nd solutions for both illegal settlers and conservation
of the city’s natural resources including the hills, RFs and
Urban vegetation helps keep cities cool, acts as a natural
lter and noise absorber, improves microclimates as well
as the physical and aesthetic quality of natural resources
(Patarkalashvili, 2017). Urban forests help maintain the
quality of life of urban residents by providing various eco-
system services, improving the urban environment and
supporting physical, mental and social health (Nesbitt et
al., 2017). Despite such benets, little has been done to
protect the hills and RFs of the GMA. LULC change moni-
toring for cities is especially needed in developing coun-
tries (Zhao, Jensen, & Zhan, 2017) and the GMA is a case in
point, wherein the urban land use has acted as a predator
(Colantoni et al., 2016) on the natural non-urban area. This
trend is expected to exacerbate over time without planned
intervention. If Guwahati is to full the goals of a smart
city that the Indian government has recently envisioned
(Varghese, 2016), this trend of unplanned, haphazard
and illegal development of built-up land at the expense
of natural vegetation must be checked and strict imple-
mentation of the Master Plan-2025 has to be initiated by
the authorities and its stakeholders.
Our examination of the GMA reveals some elements
of urban expansion and IHS that are common to urban
centres in other developing countries that are often char-
acterized by urban sprawl (Hegazy & Kaloop, 2015). Urban
an electricity connection or two would be acquired by
greasing the palms of an unscrupulous ocial. In India,
consumers often draw electricity by hooking a wire to the
nearby utility poles and up to 20% electricity generated is
lost to theft (Gaur & Gupta, 2016). Residents in the GMA’s
outer limits are prepared to acquire electricity illegally,
reecting a situation hardly uncommon to urban poor in
similar contexts in India or other developing countries.
As such, without any substantial resources at their dis-
posal, low cost housing dots the outer limits of Guwahati
(Figure 7). Houses are covered with a tin roof and walls
made of split bamboo; the latter ubiquitously available
nearly everywhere. As incomes rise, split bamboo walls
are slowly converted to more permanent walls made of
bricks or cement. In a country where various identica-
tion documents like birth certicates, voter identication
cards or ration cards can be inexpensively and fraudulently
acquired or forged (Sadiq, 2009), these marginal residents
and their housing structures are over time often given a
degree of legitimacy by local ocials and politicians on
deferred promises of votes during elections.
5. Conclusion
This paper analysed the LULC dynamics of the GMA from
1976 to 2015 using RS and GIS along with other reference
data. It monitored the urban expansion and vegetation
loss experienced in the GMA and explored the relation-
ship between LULC changes and distance from the city
centre. Signicant changes occurred during 1976–2015.
A trend of extensive replacement of natural and semi-
natural vegetated land and cultivated and managed land
with built-up land occurred. During this 39-year period,
the built-up area increased nearly fourfold by 380% from
23.9km2 in 1976 to 115.1km2 in 2015. This proliferation of
built-up area was characterized by unplanned and haphaz-
ard growth. The unplanned growth in Guwahati ts into a
trend discernible in numerous Third World urban centres
(Ameen & Mourshed, 2017; Ding, Zhong, Shearmur, Zhang,
& Huisingh, 2015).
The natural and semi-natural vegetated area which was
the dominant land cover class in 1976 declined by more
than 50% to account for only 28.7% of the total geograph-
ical area in 2015. An increase of 91.2km2 of built-up area
occurred along with a concomitant decrease in 88.9km
natural and semi natural vegetated areas. A similar result
was found in a study on urban heat islands in the GMA
(Borthakur, 2017). This is in accordance with earlier studies
noting that the green belt zone and eco-sensitive areas
in Guwahati were under continuous pressure from urban
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... Urbanisation refers to the development of urban/built-up areas for the provision of houses, industries, and other infrastructure, such as transportation networks and other social amenities that support the existence of humans [12][13][14]. Urbanisation is a common phenomenon globally, but its intensity and dynamism in developing countries because of rapid population growth and economic growth need thorough investigation [15,16]. Several studies have revealed the escalation in the world's urban population [17,18]. ...
... Urbanisation refers to the development of urban/built-up areas for the provision of houses, industries, and other infrastructure, such as transportation networks and other social amenities that support the existence of humans [12][13][14]. Urbanisation is a common phenomenon globally, but its intensity and dynamism in developing countries because of rapid population growth and economic growth need thorough investigation [15,16]. Several studies have revealed the escalation in the world's urban population [17,18]. ...
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Understanding urban growth in rapidly changing cities is critical to city planners and administrators. Urban growth is a wide-ranging concept defined in many ways by different scholars. The existing literature on urban growth and urban sprawl is voluminous. The concept of sprawl suffers from difficulty in definition and is ‘lost in a semantic wilderness.’ In this present chapter, an attempt has been made to briefly document the important aspects of urban growth and urban sprawl pertaining to nature and dimensions of the studies on urban growth, issues associated with rapid built-up growth, particularly in developing countries like India, the role of remote sensing (RS) and geographic information system (GIS) in urban growth studies, preprocessing, classification, and accuracy assessment of the used satellite images, techniques of measuring and monitoring urban growth, especially the entropy approach, change detection analysis, landscape metrics, the goodness of urban growth, and other quantitative and qualitative indices employed by global researchers highlighting their merits and demerits, modeling urban growth dynamics and its recent trends. It also highlights similar studies conducted in the Indian context. The bibliometric analysis finds that USA tops urban growth research as per Scopus database followed by China, while India ranks 49th position in the ladder. Modeling approaches, like Markov chain, cellular automata, and SLEUTH, are frequently deployed modeling approaches often integrated with RS-GIS. Furthermore, very recently, some machine learning approaches (e.g., multi-layer perceptron) are reportedly used for this purpose. However, model parameterization and calibration remain challenging and critical.
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The homogenous nature of the urban environment rapidly alters community dynamics of extant flora and fauna due to short-term spatial and temporal factors. However, such impacts of urbanization are mostly investigated in terms of taxonomic diversity, while its impact on functional diversity remains poorly understood. Whereas taxonomic information is limited to the identity of species, functional traits determine the relationship between species identity and ecosystem functioning. Studies investigating the role of urbanization in altering these ecological parameters have mostly focused on avian communities or plant species, while arthropods such as spiders which are integral components of urban households have largely been overlooked. This study aims to understand the impact of urbanization on both taxonomic diversity and functional diversity of spider assemblages across an urban-semi-urban-forest gradient in Guwahati, a rapidly growing city in northeast India. We surveyed spiders at 13 sites representing four habitat types (urban, urban parks, semi-urban, and forests) using belt transects, and also recorded functional traits relating to key life history processes. Spider species composition differed significantly between various habitats. The taxonomic diversity of spiders was highest in forests and lowest in urban parks. The turnover component was the major contributor to changing the beta diversity of spiders. Reduced diversity in urban regions was likely due to the dominance of a few synanthropic species. Generalised linear mixed-effects model analysis indicated that the habitat types significantly impacted spider abundance. Functional richness was maximum in forests (Fric = 23.43) and minimum in urban habitats (Fric = 12.98), while functional divergence was maximum in urban sites (Fdiv = 0.79). Our study demonstrates that urban land-use change can alter the structure and functioning of the spider community.
Forest loss and fragmentation are critical issues that confront urban landscapes. The urban forests in the hills of the Guwahati Metropolitan Area (GMA) in India have experienced significant transformations. This study assesses the temporal changes of forests in protected and non-protected hills of the GMA. Landsat imageries between 1976 and 2018 were used to understand changes in forest composition and fragmentation using landscape metrics namely, percentage of landscape, number of patches, mean patch size, patch density and largest patch index. The results revealed that the forests of GMA were experiencing intense losses and fragmentation due to increasing non-forest anthropogenic developments. The dense and moderately dense forests declined by 44 and 43%, respectively, as non-forest area increased by 1475 ha between 1976 and 2018. Dense forest demonstrated increasing fragmentation due to the rising number of small patches from 568 to 780. Today, dense forest patches are limited to only three of the eight reserved forests within GMA. The non-protected hills reported a significant 1309% increase of non-forest landuse. Thus, both protected and non-protected forests sustained substantial losses and fragmentation. The analysis could enable policymakers to prioritize urban forest conservation efforts in the GMA.
Rapid population growth and urbanization in and around Guwahati city, the state capital of Assam have resulted in tremendous pressure on its limited land and civic infrastructures. Due to severe congestion and shortage of space, people are exploring peri-urban plain and hilly areas around the city and gradually expanding towards adjoining districts for settlement. Earlier studies focused mainly on Guwahati city only and neighboring districts, small and medium towns around the city, and adjacent Meghalaya state have received scant attention in urban policy research. This study evaluates land use land cover changes (LULC) from 1991 to 2021 within the GMDA area and encircling a 50 km buffer from the GMDA boundary. Landsat time series data were used to analyze land use and land cover changes. The result indicates the expansion in built-up areas with a net change of 2.27% from 1991 to 2021 within the 50 km buffer study area. The result indicates the loss of forest class and cultivated land with a net change percentage of 2.12 and 0.84% within the period of 30 years. Apart from the above, the study also reveals an increase in the built-up of 33.25% within the GMDA core area from 1991 to 2021. The impact of these LULC changes shows the expansion of the built-up area beyond the GMDA boundary in the eastern, western, and northwest direction and needs to be regulated for ensuring the planned growth of its outskirts and the surrounding region. Hence through adequate decentralized regional planning, the fast-expanding Guwahati city and its surrounding region can be managed.
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Urban growth is a significant trend in Africa. Scholarly attention and urban planning efforts have focused disproportionately on the challenges of big cities, while small and medium-sized urban settlements are growing most rapidly and house the majority of urban residents. Small towns have received some attention, but very few studies have focused on secondary cities. This paper offers a study of urban transformations, migration and residential mobility patterns in Arusha, a rapidly growing secondary city of Tanzania. Arusha functions as a major attraction for migrants and in-migration is a central dynamic shaping transformation processes in central areas characterized by high population turnovers, vibrant rental markets and widespread landlordism. There is also a considerable degree of intra-urban residential mobility within and between central areas. Intra- urban residential mobility is the most important dynamic shaping transformation processes in peripheral areas characterized by long-term urban residents moving from central parts of the city as part of a process of establishing themselves as homeowners. Overall, the paper provides crucial insights on how migration and residential mobility patterns influence processes of urban growth and transformation in the context of large secondary city, and thereby contributes to fill a significant knowledge gap on secondary cities in Africa.
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The increase in urbanization is the most dramatic factor in today’s world and it did not passed round Tbilisi, the capital of Georgia, too. Since the sixties of the 20th century the population of the city nearly doubled and today is about 1.3-1.4 million. Many problems that may not have been so evident in the past, became obvious and dramatic today. These problems concern urban forests and green spaces of the city because they shrank considerably and as the result, deteriorated ecological situation. Today, their role in improvement of city climate is little. In the Soviet period the main polluters of the air considered factories and plants, but today, after breaking of the Soviet Union and closing or destruction of all factories an plants, the increasing number of light vehicles, especially outdated once, manufactured before 1999(67%) are the main source of pollution(80%). The article highlights the historical development of Tbilisi urban forests and green spaces and outlines some challenges and prospects of ecological condition of the city.
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Developing countries face significant urban environmental challenges due to rapid urbanization, population growth, inability to effectively tackle climate and environmental risks, inefficient governance and environmental management, the prevalence of corruption and a chronic shortage of investment. Environmental degradation is often acute in politically unstable countries such as Iraq. Several postwar urban development and regeneration projects are currently underway in Iraq, but without evident participation from the wider public in decision-making. This study investigated stakeholders' perception of urban environmental challenges—their level of importance and priority in the Iraqi context. A nationwide survey (n=643) was conducted using a 25-item structured questionnaire where respondents' views were gathered on a 5-point Likert-type scale, in addition to demographic information. Principal component analysis (PCA) and statistical tests were applied to investigate the relationship between the perceptions of urban environmental challenges and demographic factors. Five principal components were identified, namely: water, waste, and materials; environmental impact; natural hazard; personal mobility; and transport. The results showed that about 70% of the respondents considered 'water conservation' as the most important urban environmental challenge, followed by 'increase choice of transport modes'. 67.2% of the respondents rated 'efficient infrastructure and utilities' as a very important factor, and was ranked the third. All demographic characteristics except location showed statistically significant differences in perception. The relatively high importance placed by the respondents on infrastructure related 2 items such as water, transport and utilities demonstrate a possible link between the perceptions and: (a) the citizens' day to day experience and hardship, and (b) the lack of adequate infrastructure and service provisions in Iraq, due to political instability in the recent decades.
Linking People, Place, and Policy: A GIScience Approach describes a breadth of research associated with the study of human-environment interactions, with particular emphasis on land use and land cover dynamics. This book examines the social, biophysical, and geographical drivers of land use and land cover patterns and their dynamics, which are interpreted within a policy-relevant context. Concepts, tools, and techniques within Geographic Information Science serve as the unifying methodological framework in which landscapes in Thailand, Ecuador, Kenya, Cambodia, China, Brazil, Nepal, and the United States are examined through analyses conducted using quantitative, qualitative, and image-based techniques. Linking People, Place, and Policy: A GIScience Approach addresses a need for a comprehensive and rigorous treatment of GIScience for research and study within the context of human-environment interactions. The human dimensions research community, land use and land cover change programs, and human and landscape ecology communities, among others, are collectively viewing the landscape within a spatially-explicit perspective, where people are viewed as agents of landscape change that shape and are shaped by the landscape, and where landscape form and function are assessed within a space-time context. This book articulates some of these challenges and opportunities.
With little known and explored urban morphology in the fastest growing countries like Bangladesh in South Asia, this study aims at exploring urban spatial signature and explaining spatiotemporal land use and land cover patterns in the five cities (Rajshahi, Rangpur, Sylhet, Khulna, and Barisal) in Bangladesh. Using time series Landsat imagery, socioeconomic data and, other geospatial information with ecological analysis tools, this study quantifies and characterize the spatial-temporal landscape patterns and urban growth trajectory across the five selected sites. The spatial representation of these five sites demonstrates a continuous increase in urban/built-up areas replacing arable agricultural land, waterbodies, vegetation cover and wetlands, which thereby substantially altering the structure and function of the ecosystem surrounding the cities. Built up areas, representing impervious surface as observed from land cover maps in these five cities, are expanding quickly. The total built-up cover within the five cities grew from 2,356 ha in 1973 to 13,435 ha in 2014 with a net increase of approximately 468%, while vegetation cover and crops field within same time period declined at 27.77% and 61.91%, respectively. This dramatic urban/built-up expansion has resulted in an increasingly faster alteration in the landscape composition causing to structural complexity at both class level and landscape level. Such rapid and unplanned urban expansion further has brought an overwhelming challenge to planners and policy makers, and has put a strain on local authorities to properly manage and utilize its limited land-based resources due to lack of time series geospatial information. The resulting thematic map and spatial information from this study is, therefore, to facilitate an understanding of urban growth dynamics and land cover change pattern in the five cities in Bangladesh. The result further can aid planners, stakeholders, and other interested groups to make the best possible choices regarding limited land-based resources to achieve an economically prosperous and environmentally sustainable future.
Despite the large-scale efforts towards electrification in India since the time of independence, approximately45 million households still continue to be without electricity access. This paper critically analyses the evolution of the process of rural electrification in India, the factors that potentially determine the household electricity access and juxtaposed that with the policies adopted over three distinct time periods: the pre-independence period; the period of state ownership and the post-reforms period. The paper then builds on the key insights that could be drawn from the evolution in retrospect and attempts to highlight key historical challenges that the electricity sector has been constantly grappling with. The paper observes that during the early period of Five Year Plans, electricity was mainly used for productive input in agro-industries and for irrigation. Household access was only given priority when it was started to be considered as a basic input in the 1980s. With the enactment of the Electricity Act in 2003, the importance of electricity as an infrastructure for changing the rural landscape was felt. Based on the insights gained from the critical analysis of process of rural electrification in retrospect, the paper provides specific inputs for policy making for rural electrification in India.
With the majority of the world’s human population now living in cities, urban forests provide an increasingly important range of ecosystem services, from improved air quality and climate change adaptation to better public health outcomes and increased tourism revenues. The importance of these ecosystem services in urban environments, and the central role that cities play in the lives of people around the world, have motivated various attempts to quantify the value of ecosystem services provided by urban forests. This paper reviews existing research in the fields of urban forestry, economics, sociology, and health on the value of urban ecosystem services, with a focus on cultural services, a category of ecosystem services that is of key importance to human well-being but that has suffered from a lack of empirical research. The review identified 38 studies that examined the value of mixed vegetation, 31 studies that examined the value of trees, and 43 studies that examined the value of green spaces. Psychological health is the most-studied ecosystem service category, with most research in this area focusing on the services of mixed vegetation. Social health, community economic development, and tourism are the least-studied, with most research in these areas focusing on mixed vegetation and trees. Multiple metrics were used to quantify the value of urban greenery within each ecosystem service category but only 11 metrics were assigned a monetary value. Gaps in the literature that present strong opportunities for future research include: the value of urban forests for improving social health, equitable access to ecosystem services, the impact of urban forests on community economic development, and economic valuation and green exposure metrics. We hope that this review stimulates future research in the areas highlighted and that municipalities consider including evaluations of a broad range of ecosystem services during land use planning and budgeting processes.
This article examines the spatial and temporal patterns of land surface temperature (LST) in Nanchang City, China in the last decade (2000-2013) in the context of the urban heat island (UHI) phenomenon. It also investigates the relationship of LST with six social-ecological variables, namely land use/land cover (LULC), vegetation index, impervious surface index, water index, population density, and fossil-fuel CO2 emission. Landsat data captured in 2000 and 2013 and geographic information systems techniques were used to facilitate the analysis. The results show that the overall mean LST in the study area increased by 1.64 °C between 2000 and 2013. This temporal variation in LST might have been influenced by the given environmental conditions at the time when the source satellite images were captured. That said, there have been indications that the detected increase in the overall mean LST has been influenced by the rapid urbanization of the area, resulting in the rapid expansion of impervious surfaces and loss of green spaces. In both time points, the urban LULC class (impervious surfaces) had a consistent high LST and all the other social-ecological variables examined had statistically significant relationships with LST. We recommended that these variables be taken into consideration in the landscape and urban planning process for the future development of the city. This study also emphasizes on the importance of urban green spaces because of their ability to mitigate UHI effects and the valuable ecosystem services they generate for and provide to people. Urban green spaces can help improve the overall livability and environmental sustainability of cities.
The challenges that urbanisation pose is multi-faceted. Land allocation priorities to urban green cover are usually neglected or readily negotiated in the countries that are in transition. Urbanisation devoid of urban green can cause many social and physical impacts on its residents. Hence, locally suitable Green Index should be devised and incorporated in the urban planning of cities, in spite of the size of the city. This analysis is to showcase the green index for the planning of smart cities. The devised green index is verified in the real-world context of Gulbarga city, India, thereby understanding the practicality of this index. The results show scope for alternative green cover, where ever the green index is low. This technique presents intra-city green cover pattern analysis. Such analysis emphasises to reserve the space for green in urban planning for well-being in totality. The aspect of Land Surface Temperature (LST) analysis and correlating the same with the amount of green cover further enhances the process of promoting green cities. The assessment of per capita green space with the standards of World Health Organisation (WHO) identified the scope of greenery initiatives in various parts of the city.
Determining changes in land use/land cover (LULCC) can be used to assess and monitor habitat loss as one of the five global priority causes of biodiversity loss. In South Africa, two national land-cover (NLC) datasets have been developed from satellite imagery obtained in circa 1990 and 2013/2014. The Vhembe Biosphere Reserve (VBR), designated in 2009, is located in the north of the Limpopo Province in South Africa and has a surface area of 30,457 km2. The aim of biosphere reserves is to provide a landscape-scale framework for conservation and sustainable development of an area. The area within a biosphere reserve is prioritised by designating it into one of three zones 1) Core, 2) Buffer, and 3) Transitional Zones. Two national parks and six provincial reserves (PAs) are the current and form part of the proposed updated core areas (pCAs) of the VBR. Intensity analyses was used to assess LULCC in the VBR. The pCAs cover 39.7% of the surface area of the VBR. The PAs cover 39.7% and only 15.8% of the surface area of the pCAs and VBR respectively. Based on the NLC 2013/2014 a majority of the VBR, pCAs and PAs consisted of indigenous vegetation dominated by Woodland/Open bush, Grassland, and Thicket/Dense bush. The extent of transformed land in the VBR declined from 1990 to 2013 by 1697.7 km2. The total amount of change and mean annual change in the VBR was 53.1% and 2.31% respectively. The overexploitation of fuel wood by rural communities in rural areas of the VBR, was partly responsible for the targeted loss of Woodland/Open bush to Thicket/Dense bush and Grasslands. The unquantified presence of novel vegetation and alien invasive plants means that the NLC 1990 and 2013/2014 overestimates the quantity and distribution of the remaining indigenous vegetation in the VBR. In order to address this the distribution of alien and indigenous invasive plant species in the VBR needs to be determined and used to update future NLCs. Assuming a worse-case-scenario of all the coal deposits in the VBR, including the Kruger National Park, being mined it would amount to 24.7% of the surface area of the VBR. Only 6.8% of the area of all the coal deposits in the VBR was transformed with 93.2% currently remaining untransformed. It is recommended that transformation of indigenous vegetation to one of the seven transformed land cover categories and more specifically from coal mining should be restricted to the VBR's Transition Zones.