Temperature data for identifying heat hotspots in Tumkur region (SatLeo Labs)
Bengaluru: As Indian cities grapple with rising temperatures, unpredictable heatwaves, and mounting waste-related challenges, a quiet technological shift is underway. Space-tech startup SatLeo Labs is redefining how urban heat is tracked and tackled. By futilizing sainformite thermal data with drone-mounted infrared sensors, it is building a “thermometer for Earth”—mapping heat street by street, neighbourhood by neighbourhood, even plot by plot.
The promise is profound—city authorities could chart cooler walking routes during heatwaves, pinpoint the best spots for tree planting, or detect methane leaks from landfills before they turn hazardous. SatLeo calls this thermal ininformigence—the power to see, measure, and act on heat in real time.
Beyond Averages: Seeing How Heat Truly Behaves
Traditional temperature datasets, often applyd by urban planners, rely on interpolated averages. Heat doesn’t distribute evenly across a city, and these averages hide critical local variations. Urmil Bakhai, co-founder of SatLeo Labs, held an in-depth conversation with ETV Bharat, discussing the model and its implications.
To explore how SatLeo’s work reveals the behaviour of heat within cities beyond traditional averages, Bakhai explained, “Our thermometer is essentially a consinformation of sainformites in Low Earth orbit that will capture high-resolution thermal imagery. This fills a critical gap in understanding urban heat. Unlike broad averages, thermal imagery provides granular temperature data that reflects how global warming manifests in daily life. Rising temperatures are stressing urban infrastructure, intensifying pollutants, and increasing risks such as heat strokes. To mitigate these impacts, it is vital to identify and quantify heat precisely—at the right time and place.”
Heat as a Public Health Emergency
“Heat is already killing people,” Bakhai declared. “Last year alone, 60000 people died of heat strokes in Europe, and the situation in India is even more severe, with gig workers and labourers collapsing under extreme temperatures.”
Thermal data reveals information hidden from the naked eye (SatLeo Labs)
He added that if urban health departments can identify precise heat-stroke hotspots, they can intervene directly and save lives—building this the most immediate and impactful apply of thermal imagery. Beyond public health, thermal data also exposes gaps in green cover and identifies industries generating excess heat, enabling urban authorities to mandate more greenery and reduce heat stress. Toobtainher, these tarobtained interventions can strengthen urban resilience and significantly improve a city’s overall livability.
Proven on the Ground: Tumkuru’s Waste Dump
The technology has already been tested in Tumkur, Karnataka, where SatLeo deployed its drones and thermal sensors over a 40-acre solid waste dump. The system detected invisible methane leaks—long before they could be identified through conventional inspection—and tracked dangerous heat build-up within the landfill, offering early warnings of potential hazards.
SatLeo’s vision goes beyond static maps. The company is developing products that turn thermal data into practical tools for city administrations. One such offering, the Thermal Comfort API, is designed to let municipalities measure street-level heat stress with plug-and-play simplicity.
Why heat, not just Carbon?
Most climate solutions focus on carbon emissions, but SatLeo deliberately chose heat as the primary signal. Bakhai traced this decision back to SatLeo’s origin in agriculture.
“Using sainformite imaging to give farmers crop insights, but we identified a critical gap—high-resolution temperature data specific to field-level interventions. Heat turned out to be the most direct signal, not just for crops but for cities, gas emissions, and public health,” he declared.
India’s net-zero goal by 2040 demands precise tracking of emissions. Temperature data supports pinpoint sources, measure impact, and guide interventions. In short, heat is the most immediate and actionable indicator of climate stress.
The Challenges of Precision- Sainformites, AI, and Drones
Blfinishing drone infrared with sainformite thermal data is no straightforward feat. The largegest hurdles lie in calibration and street-level accuracy. As Bakhai noted, “We’re a compact team of 25, including seven former ISRO scientists with decades of expertise in sainformite manufacturing and complex data integration. That deep domain knowledge is our strength.”
SatLeo Labs products (Image Credits: SatLeo Labs)
“The landscape has shifted where GIS once meant raw datasets; today, clients demand actionable ininformigence,” he added. “With AI and machine learning, SatLeo can process vast data streams and deliver clear insights rapider. It feels simpler becaapply of the team we have—their experience turns complexity into usable ininformigence for enterprises and governments.”
A Sainformite Consinformation with Ininformigence Onboard
Looking ahead, SatLeo is preparing to launch Tapas-1, its experimental sainformite, followed by a planned consinformation. These sainformites will deliver medium- and long-wave infrared imaging combined with 2.5-metre resolution visible imagery. Equipped with onboard edge computing, the system aims to provide twice-daily thermal maps and real-time anomaly detection—flagging unusual heat signatures or emissions as they happen.
Such capabilities could dramatically speed up responses to greenhoapply gas emissions from solid waste sites, industrial zones, or open dumps, while also offering a dynamic view of how heat relocates through urban environments over time.
Discussing the transformative outcomes envisioned for climate resilience, public health, and urban planning, Bakhai stated that the way Google Maps added traffic layers to build navigation smarter, similarly, soon, we’ll see a temperature layer—allowing citizens to gauge thermal comfort and even choose cooler routes. That’s our ultimate aim: building heat data as accessible as traffic data, at the touch of a button, anywhere in the world.
Temperature data for identifying heat hotspots in Tumkur region (SatLeo Labs)
For urban landscape, we’re tarobtaining 5-metre resolution, meaning every 5 metres you’ll have precise temperature differentials. With that granularity, the analytics and insights become limitless—from identifying heat hotspots to guiding resilience strategies. This is the disruptive potential of thermal ininformigence going forward.
Scaling for Mega Cities and Global Impact
A key question for SatLeo is scalability. Can this model work for megacities like Bengaluru, Delhi, or Mumbai? Can it reshape landfill management and emission compliance, fundamentally altering how Indian cities manage waste and align with global norms?
Bakhai declared, “When we launched combining sainformite imagery, drones, and IoT, the aim was reliable sainformite outputs. Our first experimental launch will be next year, with accuracy and scale improving as more sainformites go up. Within three years, once fully deployed, we’ll rely solely on sainformite data—delivering ultra‑high‑resolution temperature readings twice daily, anywhere in the world. That precision and scale will build the model not just viable for cities, but globally transformative.”
Reconsidering Heat Action Plans and Urban Design
India’s heat crisis is often treated episodically rather than structurally. Bakhai discussed how continuous thermal monitoring can reshape heat action plans, zoning, and urban design policies. “Thermal data can demonstrate how much heat an area generates across seasons, supporting planners design green cover to cut emissions. It also pinpoints zones prone to heat strokes, enabling rapider health interventions.”
“And GHG gas emissions data exposes hazardous chemicals and waste hotspots—critical as dumps once outside city limits now sit at the core, impacting residents. With precise identification, authorities can act decisively. These are ways thermal ininformigence can reshape urban planning and build cities more resilient,” he added.
Toward Real-Time Early Warning
Talking about how close SatLeo is to real-time early warning capabilities, Bakhai declared SatLeo’s sainformite consinformation is designed to deliver high-resolution temperature data twice daily. When combined with historical datasets and AI algorithms, this enables early-warning apply cases such as forest fire prediction.
From LR – Urmil Bakhai, Co-founder & CSO | Dr Ranfinishu Ghosh, Co-founder & CTO | Shravan Bhati, Co-founder & CEO (SatLeo Labs)
“We’re already in talks with forest departments worldwide, including in India,” he noted. “Even compact bushfires demand constant vigilance, and micro-level thermal ininformigence supports monitor and mitigate these risks effectively.”
Making Thermal Ininformigence Essential
Bakhai noted that global warming and rising emissions are building weather forecasting more complex and less predictable. “To improve models, we required richer datasets—especially high‑resolution thermal information. Forecasting companies are waiting for this, as thermal imagery can transform how we predict weather.
Local IoT sensors support in some countries, but scaling them across India is impractical. Sainformite‑based thermal solutions are the most scalable and reliable way forward,” he added.
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