Abstract
This study maps and quantifies the changing settlement
character of Kerala’s villages between 2020 and 2025 using the European
Commission’s Global Human Settlement - Settlement Model (GHS-SMOD) dataset.
Rather than focusing only on cities, the analysis examines all 1,533
administrative villages of Kerala and classifies each of them according to
internationally standardised DEGURBA*(ref: footnote) categories ranging from rural to urban centre. A majority-class zonal
statistics method was used to translate global raster data into village-level
indicators, enabling direct comparison across the two time periods. The results
reveal that 910 villages (nearly 60 percent of Kerala) experienced a shift in
their dominant settlement classification within just five years, overwhelmingly
in an upward direction along the urban hierarchy. The findings confirm that
Kerala’s urbanisation is not concentrated only in major cities but is occurring
as a widespread, incremental transformation across ordinary villages. The study
demonstrates how global remote-sensing datasets can be converted into locally
meaningful insights for planners and researchers seeking to understand
distributed urban change.
Introduction
Urbanisation in India is usually described through the
growth of large cities; expanding metropolitan regions, rising skylines, and
new infrastructure corridors. Kerala, however, does not fit neatly into this
conventional narrative. Its settlement pattern has long been recognised as
dispersed and corridor-like, with a blurring of distinctions between “urban”
and “rural.” As a result, much of Kerala’s transformation happens not within
officially designated cities, but across hundreds of ordinary villages.
This study shifts the focus from cities to villages. Instead
of asking how fast Kochi or Kozhikode is growing, it asks a more grounded
question: how has the settlement character of Kerala’s villages changed
between 2020 and 2025? To answer this, the analysis uses global,
standardised spatial data rather than administrative labels, and applies them
consistently across the entire state.
The objective is to translate global settlement information
into a form that is directly relevant for local planning and governance. By
examining every administrative village in Kerala using the same dataset and
method, the study seeks to reveal patterns of change that remain invisible in
conventional city-centric analyses.
What Do We Mean by “Village”?
For this study, a village is defined strictly as an
official administrative village unit of Kerala, based on the Census 2001
spatial framework (with updated boundaries), used as the standard polygon layer
for analysis.
Kerala has 1,533 such villages, and every map and
statistic in this study refers to these same 1,533 administrative units.
This means the analysis is not about pixels, neighbourhoods,
wards, or towns.
It is about real, named villages as recognised in Kerala’s administrative
system.
Data Source
The analysis uses the Global Human Settlement –
Settlement Model (GHS-SMOD) dataset produced by the European Commission’s
Joint Research Centre.
This dataset classifies every 1 km grid cell of the world
into standardised settlement categories based on built-up density and
population thresholds:
- Unpopulated
- Very
Low Density Rural
- Low
Density Rural
- Rural
Cluster
- Suburban
/ Peri-urban
- Semi-dense
Urban Cluster
- Dense
Urban Cluster
- Urban
Centre
Two time slices of this dataset were used: (https://humansettlement.emergency.copernicus.eu/download.php?ds=smod)
- GHS-SMOD
2020
- GHS-SMOD
2025
Using the same global dataset for both years ensures
methodological consistency and allows meaningful comparison over time.
Method: From Global Raster to Kerala Villages
The challenge was to convert a global pixel-based dataset
into a format meaningful for local planning and governance.
The workflow followed was:
- SMOD
raster layers for 2020 and 2025 were clipped to the Kerala boundary
- Kerala
village polygons were overlaid on the raster layers
- Zonal
statistics were computed for each village
- For
every village, the majority SMOD class was extracted
- Each
village was assigned a single dominant class for 2020 and for 2025
- A
transition matrix was generated to track changes
This “majority class method” converts a complex raster
surface into a simple, interpretable question:
What kind of place is this village – mostly rural,
suburban, or urban?
(Initial exploratory maps were prepared by directly
overlaying Kerala village boundaries on the raw SMOD raster layers for 2020 and
2025. While these maps were useful for visual inspection, they did not provide
a systematic basis for comparison because each village contains multiple SMOD
classes. The final analysis therefore adopted the majority-class zonal
statistics method, which assigns a single dominant category to each village and
enables consistent year-to-year comparison.)
Kerala in 2020: The Baseline
The 2020 map shows the dominant settlement character of each
village at the start of the period.
Map 1: Kerala Village-Level DEGURBA Classification – 2020.
Source: GHS-SMOD (JRC, European Commission). Analysis & Mapping:
Ajith Vyas Venugopalan, 2026.
The map visually demonstrates that Kerala does not follow the conventional Indian pattern of isolated cities surrounded by rural hinterlands. Instead, it reflects a corridor-like, dispersed urbanisation pattern.
Several patterns are immediately visible:
- A
near-continuous belt of Urban Centres along the western coastal corridor
- Extensive
Suburban and Peri-urban zones spreading inland
- Clearly
rural clusters concentrated in the eastern highlands
- A
corridor-like urban structure rather than isolated, compact cities
Even in 2020, Kerala already appeared less like a typical
Indian state and more like a distributed urban region.
Kerala in 2025: Intensification of Urban Form
Map 2: Kerala Village-Level DEGURBA Classification – 2025
. Source: GHS-SMOD (JRC, European Commission). Analysis & Mapping:
Ajith Vyas Venugopalan, 2026
This map captures the accelerating urban diffusion
occurring beneath formal city boundaries.
By 2025, the spatial pattern shows clear intensification:
- Many
villages shift into Semi-dense and Dense Urban categories
- Suburban
zones push further eastward
- Urban
Centres expand around Kochi, Kozhikode, Thrissur, and Thiruvananthapuram
- Areas
previously classified as rural show visible upward movement in the urban
hierarchy
This is urbanisation not through a few mega-projects, but
through hundreds of small, incremental transformations.
How Many Villages Actually Changed?
To move beyond visual impressions, the dominant class of
each village in 2020 was directly compared with its class in 2025.
Map 3: Villages with DEGURBA Class Change (2020–2025) . Source:
GHS-SMOD (JRC, European Commission). Analysis & Mapping: Ajith Vyas
Venugopalan, 2026
A striking proportion of Kerala’s villages show change,
highlighting how rapidly settlement structures are evolving, even outside major
cities.
Out of 1,533 villages in Kerala:
|
Indicator |
Number |
|
Villages that changed class |
910 |
|
Villages with no change |
623 |
|
Percentage showing change |
59.4% |
|
Percentage unchanged |
40.6% |
In just five years:
Nearly three out of every five villages in Kerala altered
their dominant settlement character.
This is not a marginal adjustment.
It is evidence of widespread structural transformation.
What Kind of Change Took Place?
Not all changes are equal.
Some villages moved only one step up the hierarchy, while
others jumped multiple levels.
Map 4: Detailed Transition Map (2020 → 2025) . Source:
GHS-SMOD (JRC, European Commission). Analysis & Mapping: Ajith Vyas
Venugopalan, 2026
The village-level transition map shows where change
occurred; the transition chart explains how that change unfolded. When the 2020
and 2025 classifications are compared village by village, a clear structural
pattern emerges: most movement is upward along the urban hierarchy. The
dominant shifts are not dramatic leaps from rural to city, but steady
step-by-step transitions; from Very Low Rural to Suburban, from Suburban to
Dense Urban, and from Semi-dense Urban to full Urban Centre status. This
indicates that Kerala’s urbanisation is less about the sudden appearance of new
cities and more about the gradual thickening of existing settlements across the
state.
Transition Trends
Fig 01: Distribution of Village-Level Urban Transitions
in Kerala (2020–2025)
Number of villages undergoing specific DEGURBA class transitions between 2020
and 2025. The chart summarises the direction and magnitude of change, showing
that most transitions represent upward movement along the urban hierarchy –
particularly from rural and suburban categories into semi-dense and dense urban
classes. Analysis & Graph: Ajith Vyas Venugopalan, 2026
The numerical distribution of transitions reinforces this
interpretation. Out of 1,533 villages, 910 experienced an upward
reclassification between 2020 and 2025, while only a very small number showed
any downward movement. The largest share of transitions occurred from Very Low
Rural and Low Rural categories into Suburban and Semi-dense Urban classes,
confirming that peri-urban expansion is the primary mechanism of change. What
stands out is the breadth rather than the intensity of transformation: urbanisation
in Kerala is occurring simultaneously in hundreds of ordinary villages, not
just within established metropolitan cores. The evidence points to a process
that is incremental, distributed, and remarkably consistent across the state.
Key Findings
The comparison of village-level classifications between 2020
and 2025 reveals a remarkably rapid transformation of Kerala’s settlement
structure. Out of 1,533 administrative villages analysed, 910 villages (nearly
60 percent) changed their dominant DEGURBA class within just five years, while
only 623 villages retained the same category. This scale of change confirms
that Kerala is experiencing not isolated pockets of growth but a broad,
system-wide shift in settlement character. The dominant direction of movement
is clearly upward along the urban hierarchy: very low rural areas becoming
suburban, suburban areas intensifying into dense urban clusters, and several
already-urban locations transitioning into full urban centres.
The transitions also show that Kerala’s urbanisation is
fundamentally diffused rather than city-centric. Change is not restricted to
Kochi, Kozhikode, or Thiruvananthapuram alone; it is visible across almost
every district, including Malappuram, Thrissur, Palakkad, Kannur, and
Alappuzha. What emerges is a pattern of incremental but widespread
intensification, where villages gradually acquire urban characteristics without
necessarily being reclassified administratively. In effect, the analysis
highlights a growing mismatch between official labels and on-ground reality:
many places still called “villages” now function as suburbs, commuter
settlements, or small towns within an increasingly continuous urban region.
Limitations
The analysis presented here has several important
limitations that must be recognised. The GHS-SMOD classification relies on
global population-density thresholds rather than definitions tailored
specifically to Kerala’s unique settlement patterns. The majority-class method,
while practical and transparent, inevitably simplifies internal heterogeneity
within villages, many of which contain mixed rural and urban characteristics.
Large administrative villages, in particular, can include dense town centres as
well as sparsely populated agricultural areas. The study also assumes
methodological consistency between the 2020 and 2025 SMOD datasets, an
assumption that is reasonable but not entirely within the control of the
analyst. Despite these constraints, the approach provides a replicable and
objective framework for translating global raster data into meaningful, locally
interpretable indicators of change.
Conclusion
What emerges from the comparison of 2020 and 2025 is not
merely a picture of incremental growth, but evidence of a deeper spatial
transformation. Kerala did not simply become more urban in this period; it
urbanised in a different way, with change occurring far beyond the traditional
confines of major cities. The shift unfolded across hundreds of ordinary
villages, reflecting a dispersed and distributed process rather than isolated
expansion nodes. By converting global datasets into village-level insights, the
study demonstrates how large-scale remote-sensing information can be grounded
in local geography and governance. Taken together, the maps tell a clear story:
urbanisation in Kerala is no longer a discrete event confined to a few
locations, but a continuous and pervasive process reshaping the entire landscape.
Data and Credits
Data Source:
European Commission, Joint Research Centre. Global Human Settlement Layer –
Settlement Model (GHS-SMOD). Available at: https://human-settlement.emergency.copernicus.eu
Boundaries Used:
Kerala administrative village polygons
Methodology:
Raster zonal statistics using majority class assignment and transition analysis
Software:
QGIS
Analysis and Cartography:
Ajith Vyas Venugopalan
* DEGURBA
(Degree of Urbanisation) is an internationally used system developed by the
European Commission to classify human settlements based on population density
and built-up continuity. It does not rely on local administrative definitions
of “town” or “village,” but instead uses objective thresholds applied uniformly
across the world. The GHS-SMOD dataset used in this study assigns every 1 km
grid cell to one of eight categories:
Unpopulated, Very Low Density Rural, Low Density Rural,
Rural Cluster, Suburban/Peri-urban, Semi-dense Urban Cluster, Dense Urban
Cluster, and Urban Centre.
This approach allows places to be compared on the basis
of their physical and demographic characteristics rather than legal status. In
the Kerala context, it provides a way to measure urbanisation that is
independent of municipal boundaries or official reclassification.
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