The research team, led by Fathima Jasleena of Tamil Nadu Agricultural University together with colleagues at institutions across the state, set out to answer a deceptively simple question: which parts of Coimbatore are hottest, which are coolest, and why? To do so, they combined satellite-derived land surface temperature measurements with a suite of spectral indices that track the city’s physical makeup — the Normalized Difference Vegetation Index (NDVI) for green cover, the Normalized Difference Built-up Index (NDBI) for concrete and asphalt, and the Bare Soil Index (BSI) for exposed earth. Built-up surfaces now dominate the landscape, covering 35.59 percent of the study area, a figure that underscores just how thoroughly the city’s natural cooling infrastructure has been paved over.

The technical heart of the study lies in its integration of remote sensing with the InVEST Urban Cooling Model, an open-source tool developed by the Natural Capital Project that simulates how vegetation, shade, evapotranspiration and albedo combine to moderate local temperatures. By feeding the model with land cover data, reference evapotranspiration parameters derived from FAO CLIMWAT and CROPWAT tools, and meteorological inputs from NASA POWER, the researchers produced a spatially explicit map of the city’s Heat Mitigation Index. The results were striking: cooling capacity reached values as high as 0.84 in vegetated and peri-urban zones, while dense urban cores scored far lower, revealing a stark thermal divide running through the city.

One of the most consequential findings concerns which land-cover signal best predicts surface temperature. Across both winter and summer, NDBI — the index of impervious built-up surfaces — showed the strongest association with land surface temperature, outperforming both the bare soil index and the vegetation index. In practical terms, this means the density of sealed, sun-baked surfaces governs the city’s thermal ceiling more than the loss of vegetation or the exposure of bare ground alone. It is a nuance with real policy weight: simply leaving patches of undeveloped land is not enough if those patches are later replaced with concrete rather than canopy.

The seasonal dynamics add another layer of urgency. The researchers found that the extent of urban heat hotspots expanded by roughly 40 percent from winter to summer, yet the same administrative wards recurred as thermal centers in both seasons. That persistence is significant. It indicates that Coimbatore’s heat problem is structural rather than transient — baked into the morphology of particular neighborhoods rather than the product of a single anomalous heatwave. Wards dominated by dense construction and minimal green cover are, in effect, locked into chronic thermal vulnerability that intensifies with the seasons but never fully releases.

The human stakes become vivid when the team turns from surface temperature to heat stress on the body. Using the Wet Bulb Globe Temperature, an index that integrates temperature, humidity and radiant heat and is widely used to gauge occupational heat risk, the study found values exceeding 35 degrees Celsius in the city’s dense urban cores. That threshold is not arbitrary. Physiological research has identified sustained wet-bulb conditions near 35 degrees Celsius as a limit beyond which even young, healthy people struggle to dissipate metabolic heat through sweating. For outdoor workers, the elderly and those without access to cooling, conditions in these wards during summer approach or cross into genuinely dangerous territory.

Epidemiological work from southern India has already linked occupational heat exposure to measurable health burdens among working populations, and Coimbatore’s industrial economy depends heavily on outdoor and factory labor. The study’s spatially explicit approach means that employers, public health officials and ward-level administrators can now identify precisely which neighborhoods face the most severe stress, rather than relying on citywide averages that obscure the extremes. In a warming climate, the difference between a heat island of 10 degrees and one of nearly 15 degrees can translate into thousands of additional hours of unsafe heat exposure for the people who live and work there.

What distinguishes this research from much of the urban heat literature is its insistence on actionable, ward-specific prescriptions rather than generic exhortations to plant trees. The authors recommend a differentiated toolkit: high-albedo materials — reflective roofing and paving that bounce solar radiation back into the atmosphere — for wards where impervious cover is the dominant driver; ventilation corridors that channel prevailing winds through the street network to flush accumulated heat; nature-based solutions such as urban greening in wards dominated by bare soil; and building-level measures, including rooftop gardens and shading, in wards already so dense that street-level interventions have little room to operate. Crucially, they argue these measures must be coordinated with peri-urban planning, because the study shows the city’s strongest cooling reserves lie in its vegetated periphery, and explicit alignment with Sustainable Development Goal 11, which targets inclusive, safe, resilient and sustainable cities.

The methodological framework is as much a contribution as the findings themselves. Every dataset used in the study is openly available: Landsat 9 Collection-2 Level-2 surface temperature imagery from the USGS Earth Explorer platform, Sentinel-2 multispectral imagery from the Copernicus Data Space Ecosystem, meteorological inputs from NASA POWER, and the InVEST Urban Cooling Model version 3.17.2 from the Natural Capital Project. The geospatial analysis was performed in QGIS and Google Earth Engine, both free tools. This means any other rapidly urbanizing secondary city — and there are hundreds across Asia and Africa — can replicate the workflow at minimal cost, producing the same kind of ward-level heat maps and cooling capacity assessments that Coimbatore now possesses. In a policy landscape where data scarcity is often the excuse for inaction, that replicability matters.

Coimbatore’s story is ultimately the story of dozens of emerging cities that sit below the radar of global urban climate research, which has historically focused on megacities like Delhi, Mumbai and Shanghai. Secondary cities are urbanizing fastest, often with the weakest planning institutions and the least thermal monitoring infrastructure. By demonstrating that a combination of free satellite data and open modeling tools can deliver a clinically detailed diagnosis of urban heat — down to the ward, the season and the governing land-cover driver — this study offers those cities a template. The alternative, the seasonal numbers from Coimbatore suggest, is a future in which the same hot wards keep getting hotter, the cooling periphery keeps eroding, and the 49.6-degree summer surface becomes not an outlier but the new baseline.

Subject of Research: Urban heat island dynamics and thermal resilience assessment in Coimbatore City, India, using geospatial techniques and the InVEST urban cooling model

Article Title: Urban heat island dynamics and thermal resilience assessment using geospatial techniques and InVEST urban cooling model: a case study of Coimbatore City, Tamil Nadu, India

Article References: Jasleena, F., Madasamy, N., Kannan, B., Meiyappan, V., Kalaiselvan, A., & Alagirisamy, B. (2026). Urban heat island dynamics and thermal resilience assessment using geospatial techniques and InVEST urban cooling model: a case study of Coimbatore City, Tamil Nadu, India. Theoretical and Applied Climatology, 157(11), Article 707. https://doi.org/10.1007/s00704-026-06632-x

Image Credits: AI Generated

DOI: 10.1007/s00704-026-06632-x

Keywords: urban heat island, land surface temperature, Coimbatore, InVEST urban cooling model, remote sensing, Landsat 9, heat stress, wet bulb globe temperature, NDVI, NDBI, SDG 11, urban planning

Social interaction anxiety, the fear and distress experienced when meeting, talking with or being evaluated by other people, is more than ordinary shyness. Psychologists treat it as a continuum that can undermine academic performance, friendship formation and long-term quality of life. The Coimbatore study grounded its investigation in the theory of compensatory internet use, a framework proposed by researcher David Kardefelt-Winther in 2014. The theory holds that people do not simply become addicted to screens in a vacuum; instead, they turn to the internet to compensate for unmet psychological needs, including relief from social discomfort. In that framing, the relationship between screens and anxiety can become self-reinforcing: an anxious person retreats into the phone, the phone displaces opportunities to practise social skills, and the resulting skill deficit deepens the anxiety that drove the retreat in the first place.

The research team set out to test whether patterns of internet and gadget use were associated with social interaction anxiety in two generations defined by different technological starting points. Generation Z, roughly the cohort born from the mid-1990s to the early 2010s, grew up alongside the explosion of social media and smartphones but still remembers dial-up-era childhoods in many households. Generation Alpha, born from around 2010 onward, entered families in which smartphones, tablets and streaming services were already ambient fixtures of daily life. Because both groups are considered digital natives, the researchers asked which variables best tracked their anxiety levels: hours spent on smartphones and laptops, the age at which a respondent first used a smartphone, and the type of content each respondent preferred most.

Methodologically, the study relied on non-parametric statistics appropriate to its sample size and data distribution. The researchers used the Mann-Whitney U framework, reporting mean ranks to compare anxiety between the two generational groups, and drew on rank-based correlation techniques in the tradition of Spearman’s method to test associations between screen-use variables and anxiety scores across the entire sample. Anxiety itself was measured with instruments derived from the Social Interaction Anxiety Scale, a widely validated measure developed by Mattick and Clarke and later condensed into short forms. The authors secured ethical clearance from the first author’s institution and followed the principles of the Belmont Report and the Declaration of Helsinki; informed consent came directly from the Generation Z participants, while for Generation Alpha children consent was obtained both from the children themselves and from their parents.

The central comparison produced an unambiguous result. Generation Alpha participants showed a higher mean rank of social interaction anxiety than Generation Z participants, with the difference statistically significant at the p < 0.01 level. In practical terms, the youngest generation in the sample, currently at what the authors describe as a vulnerable age for social development, reported more discomfort in social interaction than the cohort just ahead of them. The finding resonates with a growing international literature. Prevalence studies across seven countries have documented substantial rates of social anxiety in young people, and systematic reviews have repeatedly linked higher screen time with symptoms of depression and anxiety in adolescents, although the direction of causation remains one of the most contested questions in digital-behaviour research.

Among the study’s secondary findings, one stood out for its breadth: across the combined sample of 200 respondents, early exposure to smartphones was correlated with higher social interaction anxiety. The earlier a person’s life had been touched by a smartphone, the greater their anxiety in social settings tended to be. This aligns with developmental research showing that the years from roughly age three to five are a sensitive period for language acquisition and social learning, and that high smartphone exposure in that window has been associated with behavioural difficulties. It also dovetails with recent post-pandemic studies documenting delays in pragmatic language skills among children whose early years were spent in lockdown, and with long-term evidence linking the COVID-19 era to measurable effects on language development at age three. Generation Alpha’s earliest social worlds were shaped precisely during that period of disrupted schooling and heightened screen reliance.

The study also examined content preferences, hours of use on smartphones and laptops, and their associations with anxiety, situating its results within a body of work that distinguishes passive from active screen time. Research from Canada and across 38 countries has suggested that passive consumption, such as watching video content, carries different psychological risks than active, interactive use, and that both forms relate to sleep quality, psychosomatic complaints and mood. A meta-analysis of social anxiety and internet use has likewise found that socially anxious individuals gravitate toward online environments where they can control disclosure and avoid immediate evaluation, a pattern consistent with the compensatory framework the Coimbatore authors adopted. Parasocial relationships with online creators, documented in research on YouTube use, offer a further illustration of how screens can substitute for, rather than supplement, genuine social contact.

What makes the Coimbatore study notable is its setting and its subjects. Most screen-time research comes from North America, Europe and East Asia; comparatively little has examined Generation Alpha in India, a country with one of the world’s largest smartphone user bases and a young demographic profile. By sampling both generations in the same city, the researchers held many environmental factors constant while comparing cohorts whose technological biographies differ sharply. The authors argue that their results underscore the importance of digital hygiene, the deliberate management of screen habits, especially for Generation Alpha members who are still developing the social competencies that anxiety can erode. They suggest that a reduction in screen time could yield psychological and social benefits for this group, a conclusion consistent with intervention research showing that interaction-based programmes in schools and communities support children’s mental health.

The findings arrive amid a broader scientific debate about how much digital technology actually matters for youth well-being. Some large-scale analyses have argued that the statistical association between adolescent well-being and digital technology use is modest, while others point to specific populations, such as socially anxious adolescents, for whom the effects appear more consequential. Research on socially anxious teenagers shows that their everyday social interactions carry measurable costs for mood and depression risk, which strengthens the plausibility of a feedback loop in which screens both soothe and deepen social fear. The Coimbatore data cannot settle questions of causation, since it is cross-sectional and correlational, but the generational gap it documents, with the more screen-saturated cohort reporting more anxiety, adds weight to calls for precaution rather than complacency.

For parents, educators and policymakers, the study’s practical message is that the age of first smartphone exposure may matter as much as the total hours logged. Delaying that first exposure, modelling balanced device habits at home, protecting sleep and face-to-face play, and teaching children to recognise when screens are being used to escape social discomfort are all strategies consistent with the compensatory internet use framework. The authors, who analysed the data and collected responses respectively, note that Generation Alpha is currently at a vulnerable developmental stage, and that promoting digital hygiene now, before maladaptive patterns harden into adult habits, could pay dividends across the generation’s social future. As the first cohort to grow up entirely within the smartphone era reaches adolescence, the Coimbatore findings offer an early statistical warning that the youngest digital natives may need more deliberate support in learning the oldest of human skills: talking to one another.

Subject of Research: Screen use and social interaction anxiety among Generation Alpha and Generation Z in India

Article Title: Screen use and social interaction anxiety among Gen. Alpha vs. Gen. Z in Coimbatore City

Article References: Krishnan, S. R. G., & Meena, B. P. (2026). Screen use and social interaction anxiety among Gen. Alpha vs. Gen. Z in Coimbatore City. SN Social Sciences, 6(9), Article 418. https://doi.org/10.1007/s43545-026-01718-9

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01718-9

Keywords: Generation Alpha, Generation Z, social interaction anxiety, screen time, smartphone use, compensatory internet use, digital hygiene, India, Coimbatore, social phobia, adolescent mental health, digital natives

The research, led by Manoharan Sambath and Sembulichampalayam Sennimalai Chandrasekaran of Vellore Institute of Technology together with Sandeep Maithani of the Indian Institute of Remote Sensing, forms part of a broader effort to assess urban seismic risk in India, a country where rapid construction often outpaces detailed geotechnical knowledge. Funded by the Indian Space Research Organisation through its RESPOND program, the study combined borehole records, geophysical surveys and computational modeling to produce some of the most granular ground-motion estimates yet available for the city.

At the heart of the work lies a technique called Site-Specific Seismic Ground Response Analysis, or SSGRA. The method takes an earthquake signal defined at bedrock depth and propagates it upward through the local soil column, accounting for how each layer stiffens, softens and dissipates energy as it is deformed. Because soil is not a simple elastic medium, the team ran two parallel formulations: an equivalent linear approach, which uses averaged stiffness and damping values, and a more computationally demanding nonlinear analysis that tracks the true stress-strain behavior of the sediments under strong cyclic loading.

The input side of the calculation was equally rigorous. The researchers drew on a probabilistic seismic hazard analysis of the Coimbatore region, which they had previously developed using a logic-tree framework, to define five distinct hazard zones based on bedrock peak ground acceleration. For each zone, they constructed a Uniform Hazard Response Spectrum and then spectrally matched eleven suitable recorded ground motions to it, ensuring that the input signals carried the right energy content across the frequency range that matters for buildings. These matched motions were then applied for two hazard levels, corresponding to return periods of 475 and 2475 years, roughly the shaking expected once in 475 and once in 2475 years respectively.

Characterizing the soils themselves required fieldwork across the city. The team used 40 geospatially distributed bore logs, which record the layering and index properties of the subsurface, together with active Multichannel Analysis of Surface Waves tests. MASW surveys measure how seismic surface waves disperse through the ground, allowing engineers to compute the average shear-wave velocity in the top 30 meters, a parameter known as Vs30 that has become the international standard for classifying site conditions. Soils with low Vs30 values, typically soft clays and loose sands, amplify ground motion far more than dense gravels or rock.

The results paint a strikingly uneven picture of Coimbatore’s seismic vulnerability. The neighborhoods of Rathinapuri, Avinashi, Gandhipuram and NGGO Colony showed a broad variation in surface peak ground acceleration, meaning that even within these areas, the intensity of shaking could differ substantially from one site to the next depending on local soil conditions. Such block-by-block variability has direct consequences for building codes, which often assume a single design value across an entire city.

Perhaps the most consequential finding concerns spectral acceleration, the quantity that most directly governs structural design. The central part of the city exhibits the highest surface spectral accelerations at spectral periods of 0.5 and 1.0 seconds, ranges that coincide with the natural vibration periods of many mid-rise reinforced concrete buildings. In an earthquake, structures resonate with ground motion at their own natural periods, so elevated spectral acceleration in this band implies that a significant share of Coimbatore’s building stock could experience forces well above what a uniform hazard map would suggest.

The study also found a clear geographic pattern in amplification, the ratio of surface motion to bedrock motion. The western region of the city experienced higher amplification factors for the 475-year return period event, indicating that its subsurface conditions selectively boost moderate-intensity shaking. Interestingly, the relationship between amplification and shaking intensity is not constant: as input motions grow stronger, soils soften and damp more, which is precisely why the team ran both linear-equivalent and nonlinear analyses across the two return periods rather than relying on a single scenario.

The comparison with codified design spectra carries a cautionary message for practitioners. The site-specific Acceleration Design Response Spectrum proposed in the study was found to be overestimated, particularly for the second group of bedrock PGA-based hazard zones, when set against the nonlinear surface response spectra computed by the analysis. In other words, for those hazard zones, the design spectrum is conservative, demanding more seismic resistance than the physics of the soil column requires. While conservatism is not inherently dangerous, it imposes unnecessary construction costs; the flip side is that in zones where the spectrum is not conservative, the margin of safety may be thinner than assumed.

For Coimbatore, a city whose economy is anchored by textile manufacturing, engineering industries and a dense fabric of both formal and informal construction, the maps produced by this study offer a practical template for risk-sensitive planning. The work also demonstrates a methodology that other Indian cities can replicate: combine probabilistic hazard analysis with dense geotechnical sampling, geophysical profiling and dual-formulation site response modeling to move from city-wide averages to neighborhood-level truth. As India’s seismic monitoring network expands and urban populations grow, studies of this kind convert abstract hazard curves into concrete guidance about where the ground will shake hardest, and where engineers should look most carefully before the next earthquake tests their assumptions.

Subject of Research: Site-specific seismic ground response analysis and geospatial mapping of surface ground motion parameters for Coimbatore city, India

Article Title: Geospatial variation of surface ground motion parameters using the 1-D Site-Specific Seismic Ground Response Analysis (SSGRA) for Coimbatore city, Tamil Nadu, India

Article References: Geospatial variation of surface ground motion parameters using the 1-D Site-Specific Seismic Ground Response Analysis (SSGRA) for Coimbatore city, Tamil Nadu, India. (n.d.). https://doi.org/10.1007/s10518-026-02705-4

Image Credits: AI Generated

DOI: 10.1007/s10518-026-02705-4

Keywords: seismic hazard, ground response analysis, Coimbatore, shear-wave velocity, MASW, peak ground acceleration, spectral acceleration, site amplification, soil dynamics, earthquake engineering, India, borehole data