Unraveling Housing Growth in Kerala: An Economic and Infrastructure Perspective

 

Housing construction is a critical indicator of economic vitality and urban expansion. In Kerala, where land availability is constrained by geography, demography, and policy interventions, understanding the factors driving new residential development is essential. Unlike rapidly expanding metropolitan regions, Kerala’s housing growth follows a unique trajectory shaped by economic activity, infrastructure development, and government-led interventions such as the LIFE Mission and PMAY (Urban & Rural) schemes.

This study explores the economic and spatial determinants of housing growth across Kerala’s districts. A closer look at district-wise economic activity reveals that the stretch from Ernakulam to Kannur exhibits a distinctive pattern—higher economic productivity, greater infrastructure development, and an active housing market. Whether this signals the emergence of a well-connected economic corridor or reflects broader state-wide trends is a key question guiding this analysis.

Additionally, Kerala’s housing expansion poses a crucial dilemma:

• Is growth occurring through urban densification, where existing cities accommodate more residents?
• Or is housing growth primarily driven by outward expansion into previously undeveloped or ecologically sensitive areas?

This distinction holds significant implications for environmental sustainability, infrastructure planning, and equitable growth. If housing development follows an outward sprawl pattern, it could lead to fragmented urbanization and the risk of encroaching upon Kerala’s fragile ecosystems. On the other hand, if densification is driving growth, cities may need better policies to accommodate rising populations while ensuring livability.

To explore these dynamics, this study integrates multiple datasets and analytical techniques, including spatial mapping, economic indicators, and Ordinary Least Squares (OLS) regression models. The analysis examines both economic forces (business activity, infrastructure, per capita income) and urban mobility indicators (motor vehicles, population density, tourism) to determine their respective roles in housing growth.

Before diving into econometric analysis, the following sections will establish a district-level spatial and economic overview, setting the stage for a deeper investigation into the key drivers of Kerala’s housing expansion.

Percentage of Urbanisation: GIS map by me. Date source: KERALA Economic Review_2024_Eng_Vol 1

Regional Economic Trends: GDVA at Basic Prices (₹ in Lakh) Across Kerala's Districts. Graph by me. Date source: KERALA Economic Review_2024_Eng_Vol 1

The chart reveals a noticeable economic corridor of high productivity extending from Ernakulam to Kannur, encompassing Thrissur, Palakkad, and Kozhikode. These contiguous districts exhibit relatively high GDVA, indicating strong commercial, industrial, and service sector activity. This region benefits from well-developed infrastructure, transportation networks, and urbanization, making it a key driver of Kerala’s economy. In contrast, districts like Idukki and Wayanad, with their predominantly forested and hilly terrain, show lower economic output, reinforcing the role of geography in shaping economic performance. Understanding these spatial patterns helps contextualize regional development strategies and housing growth dynamics.

Exploring the Link Between Population Density and Per Capita Income

Before delving into our regression analysis, we first examine a fundamental relationship in urban economics: the correlation between population density and per capita income. Understanding this link is crucial, as density can often indicate the degree of economic activity, access to infrastructure, and urbanization levels.

Is there a Correlation between Population Density & Per Capita Income? Graph by me. Date source: KERALA Economic Review_2024_Eng_Vol 1

Two different measures of correlation provide insight into this relationship:

• Pearson correlation coefficient: 0.42 – This suggests a moderate positive correlation between population density and per capita income. This implies that, generally, districts with higher population density tend to have higher per capita income, though the relationship is not particularly strong.
• Spearman correlation coefficient: 0.38 – A slightly weaker correlation, indicating that while there is a positive trend, the rank order of districts by density does not perfectly match their rank order by per capita income.

Scatter plot by me. Date source: KERALA Economic Review_2024_Eng_Vol 1

The scatter plot further illustrates this relationship, with the red trendline showing a positive slope, confirming that districts with higher population densities do tend to have higher per capita incomes. However, the spread of data points indicates that other factors are at play, and population density alone does not fully explain income variations.

This correlation serves as a starting point for our deeper analysis. While a moderate relationship exists, the next step is to examine multiple economic and infrastructural factors together to understand what truly drives housing development and economic growth across Kerala's districts.

Mapping Kerala's Housing Landscape

Before delving into our econometric analysis, it is crucial to visualize the spatial distribution of key factors that influence housing development across Kerala. The following maps and charts provide a clearer picture of the regional variations in housing initiatives, land use, and infrastructure growth.

1. Housing Development Through Life Mission:
   
   
   

The Life Mission initiative has played a significant role in addressing housing shortages, with varying levels of success across districts. The first chart showcases the number of houses built in each phase, highlighting the concentration of housing efforts in districts such as Thiruvananthapuram, Palakkad, and Malappuram.

1.      Extent of Homelessness Addressed:

The second graph illustrates the number of homeless and landless families yet to be rehabilitated.

 

1.      Forest Cover and Land Constraints:

 

The third visualization shows the distribution of forest cover across Kerala. Districts such as Idukki, Wayanad, and Palakkad possess large tracts of ecologically sensitive land, which inherently limits urban expansion. The interaction between land availability and housing growth is a key factor in determining where new construction can feasibly occur.

These visual insights set the stage for a deeper quantitative analysis. These spatial trends highlight the interplay between economic activity, government intervention, and geographic constraints. While Life Mission has made significant contributions, forested districts like Wayanad and Idukki face inherent limitations to expansion. Meanwhile, high economic output in urbanized regions suggests infrastructure and economic vibrancy as key drivers of new housing construction. The following econometric models test whether business activity, infrastructure, mobility, or tourism best explain housing growth patterns across Kerala’s districts.

Two Key Drivers of Housing Growth: Economic Expansion and Urban Mobility.

Two separate OLS regression models were developed to investigate housing growth.

1. The first model explores the relationship between housing construction and economic/infrastructure indicators, focusing on:
• Per Capita Income (Economic well-being and housing affordability)
• Number of Registered MSMEs (A proxy for business growth and employment)
• Length of PWD Roads (Infrastructure accessibility and urban expansion)

  

  Graph by me. Date source: KERALA Economic Review_2024_Eng_Vol 1

1. The second model shifts focus to urbanization and mobility factors:
• Percentage of Urban Population (Extent of urbanization)
• Population Density (Indicator of land availability and demand constraints)
• Number of Motor Vehicles (Economic mobility and urban demand)
• Domestic Tourist Arrivals (Potential impact of tourism-induced housing demand)

By analyzing these two models side by side, we derive a broader understanding of Kerala’s housing growth patterns and the potential policy implications.

 

Regression Results and Interpretation

Model 1: Economic and Infrastructure Drivers of Housing Construction

This model examines the influence of economic and infrastructural factors—Per Capita Income, MSME presence, and Road Length—on the number of new residential units.

 

	Dependent variable:
	`Total_Residential_Units_21-22`
Per_Capita_Income	-0.062***
	(0.011)
Number_of_Registered_MSMEs	2.380***
	(0.152)
Length_of_PWD_Roads_km	1.608*
	(0.816)
Constant	5,354.697**
	(1,736.952)
Observations	14
R2	0.970
Adjusted R2	0.961
Residual Std. Error	1,334.727 (df = 10)
F Statistic	108.910*** (df = 3; 10)
Note:	*p**p***p<0.01

Findings:

Variable	Effect on New Housing Units	Reliability
Per Capita Income	For every ₹1,000 increase in per capita income, new housing decreases by 62 units	Highly reliable (p < 0.01)
Number of Registered MSMEs	For every 100 new MSMEs, 238 more houses are built	Very strong effect (p < 0.001)
Adjusted R²	96.1% of housing variation explained by this model	Very strong model
F-statistic	Model overall is statistically significant (p < 0.01)

• Economic activity (MSMEs) is a major driver of housing growth, likely due to increased employment and migration towards business hubs.
• Per capita income negatively correlates with new housing construction, suggesting that wealthier districts either already have sufficient housing stock or rely more on redevelopment than new construction.
• Infrastructure expansion (road networks) shows a moderate positive effect on housing, supporting the idea that accessibility boosts residential growth.

 

Model 2: Urbanization and Mobility Factors in Housing Growth

This model explores the impact of urbanization rate, population density, motor vehicle ownership, and domestic tourism on housing growth.

 

	Dependent variable:
	`Total_Residential_Units_21-22`
percentage_urban_pop	5,014.516
	(5,982.209)
Density_per_sqkm	-6.435
	(3.738)
Number_of_Motor_Vehicles_L	1,294.811***
	(246.772)
Domestic_Tourist_Arrivals_2023_L	-228.366***
	(65.564)
Constant	6,739.679**
	(2,074.591)
Observations	14
R2	0.882
Adjusted R2	0.829
Residual Std. Error	2,806.003 (df = 9)
F Statistic	16.797*** (df = 4; 9)
Note:	*p**p***p<0.01

 

While economic growth indicators like MSME presence and road expansion significantly drive housing development, urban mobility trends add another layer of insight. The number of motor vehicles shows a strong correlation with housing expansion, reinforcing the idea that housing growth follows economic dynamism. However, traditional urbanization metrics—such as population density—do not show a strong effect, suggesting that housing growth is expanding outward rather than concentrating in existing urban centers.

Findings:

Variable	Effect on New Housing Units	Reliability
Percentage of Urban Population	A 10% increase in urbanization adds 500 new houses, but this effect is statistically weak	Unreliable (p > 0.10)
Number of Motor Vehicles	For every 1,000 new vehicles, 1,294 more houses are built	Very strong effect (p < 0.01)
Domestic Tourist Arrivals	For every 10,000 additional tourists, 228 fewer houses are built	Highly reliable (p < 0.01)
Adjusted R²	82.9% of housing variation explained by this model	Strong model
F-statistic	Model overall is statistically significant (p < 0.01)

 

• More motor vehicles correlate with higher housing construction, reinforcing the role of economic activity and mobility in residential expansion.
• Urbanization percentage and density are weak predictors, suggesting that new housing is expanding outward rather than densifying existing urban areas.
• Domestic tourism negatively correlates with housing growth, indicating that tourism-driven demand might be concentrated in rental accommodations rather than new residential projects.

 

Key Takeaways: What Do These Findings Tell Us?

1. Economic growth, not just population growth, fuels housing expansion

MSME density and vehicle ownership are more predictive of housing demand than population density or overall urbanization levels.

2. Urban sprawl rather than densification

Higher per capita income areas are not driving new housing, and urban percentage does not significantly predict construction. This suggests that growth is expanding outward into newly developing peri-urban areas, rather than densifying existing city centers.

3. Tourism is not a major driver of new residential construction

Despite Kerala’s prominence as a tourist destination, the housing sector does not appear to be directly influenced by tourism. This could mean that much of the tourism-related housing demand is met through hotels and homestays rather than new residential construction.

 

Conclusion

By integrating both analyses, this study provides a holistic perspective on Kerala’s housing growth dynamics. The findings indicate that economic activity and infrastructure development play a more significant role in housing construction than mere population growth. Notably, the expansion of roads and business activity correlates with increased housing units, suggesting that new developments are more aligned with outward expansion rather than densification. This pattern highlights the importance of strategic infrastructure planning to guide urban growth while mitigating risks of urban sprawl.

These insights are crucial for policymakers seeking to balance economic expansion with sustainable urban planning. A more nuanced approach—considering both economic drivers and spatial constraints—can help optimize housing policies to enhance connectivity, preserve ecological integrity, and ensure equitable growth.

This study not only reveals the economic and spatial determinants of Kerala’s housing expansion but also highlights the urgency of sustainable urban planning. If policymakers fail to guide housing growth strategically, rapid expansion could strain infrastructure and disrupt ecological balance. Future work integrating GIS-based spatial analysis will provide more precise, data-driven interventions to ensure that Kerala's housing boom aligns with both economic growth and environmental sustainability.

Unlocking Kerala’s Carbon Wealth: A Call for Monetizing Forest Carbon Stock

 

Introduction

Kerala, with its lush forests covering over 54.42% of its landmass, holds a carbon stock of approximately 205.523 million tonnes as per the Forest Survey of India (FSI) 2021. This translates to 754.27 million tonnes of CO₂ equivalent—a resource of immense economic value that remains largely untapped. Given the escalating global efforts to combat climate change and the rising importance of carbon markets, it is imperative that Kerala strategically positions itself to monetize this asset.

Despite global carbon pricing mechanisms offering potential economic returns, India, has yet to integrate carbon stock monetization into its state-level economic frameworks. This article advocates for a paradigm shift in Kerala’s Forest governance, proposing policy interventions, institutional frameworks, and a road-map for leveraging forest carbon wealth to enhance sustainable development, climate resilience, and economic security.

Fig 01: Forest Cover Map of Kerala: This map illustrates the distribution of very dense forest, moderately dense forest, and open forest across Kerala, along with non-forest areas, water bodies, and district boundaries. Source: Forest Survey of India (FSI), Government of India.

Understanding the Valuation of Kerala’s Carbon Stock

Carbon Pricing: A Rational Basis for Valuation

International carbon markets function based on cap-and-trade systems, carbon taxes, and voluntary carbon credit mechanisms. Prices fluctuate based on supply-demand dynamics, regulatory environments, and commitments under agreements like the Paris Accord.

As of 2024, carbon pricing varies widely:

• European Union Emissions Trading System (EU ETS): $90–$100 per tonne of CO₂
• California Cap-and-Trade Program: $30–$40 per tonne of CO₂
• Voluntary Carbon Markets (e.g., REDD+ credits): $5–$20 per tonne of CO₂
• Global average carbon price (World Bank estimate): $50 per tonne of CO₂

Thus, taking a conservative global average price of $50 per tonne of CO₂, Kerala’s Forest carbon stock is valued at approximately $37.7 billion (or ₹3.13 lakh crore). Even at the lower bound of $5 per tonne, Kerala’s forests could still represent a $3.77 billion economic asset. Would be good to know in this context that, the total annual budget of Kerala for the fiscal year 2024-25 is approximately ₹1.74 lakh crore, or $21 billion USD.

India’s National Carbon Credit Trading System:

India is establishing a regulated carbon market under the Energy Conservation (Amendment) Act, 2022. The Bureau of Energy Efficiency (BEE) and the Ministry of Power are working on a National Carbon Credit Trading Scheme, expected to be fully operational by 2025. Initially, it will focus on energy efficiency credits but may later expand to greenhouse gas (GHG) emissions trading.

Under the Perform, Achieve & Trade (PAT) Scheme, a cap-and-trade system launched in 2012 under the National Mission on EnhancedEnergy Efficiency (NMEEE). Here, large industries in energy-intensive sectors (steel, cement, power) are assigned energy consumption reduction targets. Companies exceeding targets earn Energy Saving Certificates (ESCerts), which they can trade with underperforming companies.

The Renewable Energy Certificate (REC) Mechanism encourages industries to invest in renewable energy projects. It allows carbon credit generation from renewable energy, which can be traded in India’s Power Exchanges. India does not yet have a national voluntary carbon market, but companies participate in global carbon credit trading (e.g., Verra, Gold Standard), while some Indian firms like Tata, Infosys, and ITC are engaging in voluntary carbon offsets.

There is no Direct Carbon Tax in India unlike countries such as Sweden or Canada. However, it levies an implicit carbon price through the Coal Cess (National Clean Energy Fund) - ₹400 per tonne on coal production, and through Excise Duties & GST on fossil fuels.

Some Global Practices:

1. Costa Rica’s Payment for Ecosystem Services (PES) Program that pays landowners for carbon sequestration and has attracted over $500 million in climate finance.
2. Colombia’s Carbon Tax & Offsetting System which is a national-level carbon tax mandates emitters to purchase forest-based carbon credits.
3. California’s Cap-and-Trade Linkages allows tropical forest credits from developing nations, offering a precedent for Indian states to access Western carbon markets.

Article 6.2 of the Paris Agreement and Its Relevance to Kerala’s Carbon Market Strategy

The Paris Agreement, under Article 6, establishes mechanisms for international cooperation on carbon markets to help countries achieve their Nationally Determined Contributions (NDCs) more efficiently.

Article 6.2 specifically allows countries to transfer carbon credits between nations through bilateral or multilateral agreements, known as Internationally Transferred Mitigation Outcomes (ITMOs). These credits can be used by countries to meet their emission reduction targets while ensuring transparency and avoiding double counting.

Although Kerala, as a state, cannot independently negotiate ITMO agreements with foreign nations, it can still benefit from India's participation in Article 6.2 mechanisms by:

1.    Contributing to India’s ITMO Strategy

The Government of India (GoI) is responsible for negotiating ITMO agreements with high-emission countries (e.g., Japan, Germany, Canada) that need carbon credits to meet their climate commitments. Kerala can advocate for forest-based carbon credits to be included in India’s ITMO, ensuring that credits generated from its afforestation, conservation, and carbon sequestration projects are recognized and sold internationally.

2.    Generating Revenue from India’s Carbon Market Exports

If India sells ITMOs internationally, revenue from these transactions can be allocated to states that contribute significant carbon sequestration. Kerala could push for a revenue-sharing mechanism where a portion of earnings from international carbon credit sales flows back to the state.

Challenges to Monetizing Forest Carbon in Kerala

1. Absence of a Regulatory Carbon Market Framework

India currently lacks a comprehensive domestic carbon pricing policy. While initiatives like the Perform, Achieve, and Trade (PAT) scheme and the Renewable Energy Certificate (REC) system exist, they do not address carbon sequestration in forests. Kerala has recently announced policies promoting green hydrogen and is engaging in broader discussions about climate resilience financing. While this is not directly linked to carbon credit trading, it indicates the state's awareness of global carbon markets. Programs like Haritha Keralam focus on tree planting and ecosystem restoration, which could align with voluntary carbon markets if formalized.

2. Limited Participation in Voluntary Carbon Markets

There have been informal discussions within policy circles about leveraging Kerala’s extensive forests, particularly in the Western Ghats, for carbon sequestration projects. However, no official legislation or structured market participation has emerged. Projects such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation) offer pathways for carbon trading, but Kerala has yet to register large-scale afforestation or conservation programs in these markets. Kerala is aligned with India’s commitments under the UNFCCC, but lacks a dedicated state-level REDD+ strategy.

3. Lack of Institutional Mechanisms for Carbon Credit Accounting

Institutions like Kerala State Biodiversity Board (KSBB) and Centre for Climate Change Studies (CCCS) have explored carbon sequestration potential but have not yet moved towards implementation of carbon credit programs. Effective monetization requires a robust MRV (Monitoring, Reporting, and Verification) system for Kerala’s carbon sequestration. While India’s National Adaptation Fund for Climate Change (NAFCC) supports climate resilience projects, no dedicated institution oversees state-level carbon financing.

A key bureaucratic hurdle is determining which agency should oversee Kerala’s carbon credit system. Should it fall under the Forest Department, which manages conservation efforts, the Kerala State Pollution Control Board (KSPCB), which handles environmental regulations, or should the state establish a dedicated Carbon Trading Authority? The absence of clarity in governance can slow down policy adoption and deter private sector investments.

Additionally, there are State vs. Centre conflicts in approvals that must be resolved. Carbon trading mechanisms require alignment with India’s national carbon market and international commitments. Kerala would need explicit approvals from the Union Ministry of Environment, Forest and Climate Change (MoEFCC) to integrate its carbon credit projects with India’s emissions trading system. The state would also require new legislation or amendments to existing forestry laws to enable private sector participation, ensuring compliance with national and global carbon credit frameworks.

Given Kerala’s fiscal constraints, integrating carbon monetization into economic planning could be a future move. The idea has not yet become a major policy priority, but it could gain traction if economic benefits are clearly demonstrated.

What can Kerala start doing in this regard.

1. Establishing a Kerala Carbon Credit Registry (KCCR) and develop a Kerala Green Bond Initiative

A state-level carbon registry should be developed to catalogue forest carbon assets, facilitate carbon credit trading, and ensure transparency in Kerala’s carbon market. This registry can integrate with national carbon credit mechanisms, allowing the state to position itself as a major player in nature-based climate solutions. Additionally, a Kerala Green Bond Initiative can be introduced to attract domestic and global investors, raising capital for large-scale afforestation, sustainable forestry, and carbon sequestration projects. These bonds can help finance the transition to a low-carbon economy while offering attractive returns for investors focused on sustainability.

.2. Engaging Private Sector Participation

Kerala can actively engage the private sector by creating public-private partnerships (PPPs) that facilitate corporate investments in afforestation, biodiversity conservation, and sustainable agroforestry projects. Companies with net-zero commitments can be incentivized to purchase Kerala’s carbon credits through a state-managed carbon exchange, helping industries offset their emissions while contributing to local environmental sustainability.

Potential buyers of Kerala’s carbon credits include Tech & IT firms (e.g., Infosys, TCS) looking to enhance their sustainability profiles, hospitality & eco-tourism sectors seeking carbon-neutral operations, and manufacturing & logistics industries aiming to balance their environmental impact.

To ensure practical implementation, the state must identify specific areas for afforestation under PPP models. Given Kerala’s increasing land-use pressures from road network expansion, urbanization, and developmental projects, afforestation commitments should focus on:

Degraded forest patches and buffer zones around existing protected areas to enhance biodiversity corridors, Riparian zones along Kerala’s rivers and backwaters, restoring ecological functions while providing natural flood mitigation, and Hillside plantations in selected non-forest revenue lands to prevent soil erosion and maintain watershed health.

Additionally, increasing human-wildlife conflicts resulting in casualties and fatalities pose a growing concern. Any afforestation initiative must be designed to reduce habitat fragmentation and mitigate human-wildlife interactions, ensuring a balance between conservation and community safety. Integrated solutions such as wildlife corridors, community-managed buffer zones, and compensation mechanisms for affected populations should be incorporated into the afforestation strategy.

Projected Economic Gains for Kerala

As mentioned earlier, if Kerala successfully integrates its forest carbon into structured trading mechanisms, it stands to gain Carbon credit revenue at $50 per tonne = ₹3.13 lakh crore, and an annual carbon offset revenue (at 1% sequestration rate) = ₹30,710 crore

Conclusion:

Kerala stands at a historic crossroads where it can choose to lead India’s climate finance revolution. By harnessing its vast forest carbon reserves, Kerala can achieve climate mitigation, economic resilience, and sustainable development. The time for inaction has long passed—Kerala must move swiftly to convert its natural wealth into a financial asset that secures economic stability and environmental justice for future generations.

Carbon is no longer just an environmental concern—it is an economic opportunity waiting to be seized. As the world accelerates toward net-zero, Kerala must not remain a spectator but take its rightful place in the global carbon economy. The time for action is now.

Kerala's Migration Pulse: Visualizing Emigration and Net Emigration Trends in 2023

 

The maps presented here offer a compelling visual narrative of Kerala's migration landscape, based on data from the Kerala Migration Survey 2023 conducted by S. Irudaya Rajan with support from the Gulati Institute of Finance and Taxation (GIFT). These visuals delve into two key aspects: overall emigration patterns and net emigration, highlighting the districts that are experiencing significant migration pressures and returns.

Emigration Map: Kerala’s Global Footprint

Figure 1: District-wise emigration from Kerala in 2023, visualized by me using QGIS. The map highlights Malappuram as the leading district in international migration, followed by Thrissur, Kannur, and Kozhikode. Data sourced from the Kerala Migration Survey 2023.

This map presents the emigrant population by district—individuals who have left Kerala to live or work abroad. This longstanding trend reflects Kerala's enduring relationship with international migration, particularly to the Gulf countries.

Key highlights from the map:

• Malappuram stands out with the highest number of emigrants at 377,647, continuing its historical trend as a major migration hub.
• Districts such as Thrissur (233,177), Kannur (212,208), and Kozhikode (193,697) also record significant emigrant populations, underlining strong overseas ties.
• Additionally, Ernakulam has seen a notable rise in student emigration, reflecting the district’s emphasis on higher education and global exposure. The surge in students seeking international academic opportunities highlights a growing aspiration among the younger population for specialized qualifications and better career prospects abroad.
• Idukki and Wayanad show notably lower emigration rates, possibly due to their rural nature.

This distribution pattern underscores the economic and cultural importance of international migration, with certain districts having deeply entrenched migration networks.

Net Emigration Map: The Balance of Movement

Figure 2: Net emigration across Kerala districts in 2023, calculated by subtracting return emigrants from total emigrants. Visualized by me using QGIS, the map reveals Kannur as having the highest positive net emigration, while Thiruvananthapuram and Kozhikode show a higher rate of returnees than new emigrants. Data sourced from the Kerala Migration Survey 2023.

The second map shifts the focus to net emigration, calculated by subtracting return emigrants from the total emigrants in each district. This provides a clearer picture of how migration flows are impacting the state's demographics.

Noteworthy observations:

• Kannur emerges as the district with the highest positive net emigration of 105,800, suggesting that while many leave the district, fewer are returning. This could reflect the region's limited job creation capacity, pushing residents to seek opportunities abroad.
• Kottayam (69,547) and Pathanamthitta (60,703) also show substantial positive net emigration, indicating a steady outflow of skilled labor and professionals.
• Conversely, Thiruvananthapuram (-77,778) highlight a different trend. The capital city, bolstered by the growth of IT hubs like Technopark, has become a significant employment generator, attracting returnees and reducing the need for emigration.
• Thrissur (-6,262) and Kozhikode (-16,591) also exhibit signs of more people returning than leaving, reflecting a possible shift in economic opportunities within these districts.
• Ernakulam (35,107) demonstrates a moderate positive net emigration, but its economic dynamics are distinct from districts like Kannur or Pathanamthitta. As Kerala’s commercial capital and home to major urban centers, Ernakulam benefits from a more diverse economy. Ernakulam’s moderate positive net emigration could also be attributed to the increasing number of students pursuing education abroad.

These visualizations provide a nuanced understanding of migration trends in Kerala, and the need to address the socio-economic challenges and opportunities posed by migration.

Data Source: Kerala Migration Survey 2023 by S. Irudaya Rajan.

Ernakulam Improved Lighting 2012 to 2022- Source: Bhuvan

 Are you interested in doing this on your own?

Please try!

Google 'bhuvan portal"

Click "Bhuvan" or 

use this: https://bhuvan.nrsc.gov.in/ngmaps?mode=Hybrid#3.71/22.91/82.78

From the Open Menu icon, select "Satellite Data Analytics" and the rest as shown or any place or State you wish to see. 

Choose these to get this option on screen:

Select "Swipe" and then change the Left Layer to 2012 and Right layer to 2022.

Now that you know, try different options to see the changes in other areas you are interested in.