How Remote Sensing and GIS Are Transforming Disaster Management in India Amid Rising Climate Extremes

India recorded 322 days of extreme weather in 2024, with floods, landslides, and heatwaves causing over 3,400 deaths. As climate change accelerates, technologies like Remote Sensing, GIS, and AI are becoming vital tools for real-time monitoring, risk reduction, and climate resilience.

As climate change intensifies, India finds itself increasingly vulnerable to erratic and extreme precipitation events, leading to devastating floods, landslides, cloudbursts, and heatwaves. In the wake of mounting climate threats, technologies like Remote Sensing (RS) and Geographic Information Systems (GIS) are emerging as transformative tools to strengthen disaster management, mitigation, and resilience efforts across the country.

Rising Frequency of Extreme Weather Events

In recent years, India has witnessed a disturbing surge in extreme weather. According to the Centre for Science and Environment (CSE), the country experienced extreme weather events on 322 days in 2024, 318 days in 2023, and 314 days in 2022. These included heavy rain, floods, landslides, heat and cold waves, cyclones, and lightning.

Data from the India Meteorological Department (IMD) paints an even grimmer picture: during the June–September monsoon season of 2024 alone, 1,528 people lost their lives, with Madhya Pradesh, Himachal Pradesh, and Maharashtra being among the worst-hit states. In total, 3,472 people died, 67,399 livestock perished, 4.07 million hectares of crops were damaged, and 2.9 lakh houses were destroyed due to extreme climatic events.

Projections and Climate Realities

The Intergovernmental Panel on Climate Change (IPCC), in its Sixth Assessment Report (AR6), projects that India will face intensified summer monsoons, increased heavy rainfall events, frequent floods, and prolonged, intense heatwaves in the coming years. Such findings emphasize the urgent need for technological interventions and improved policy frameworks to mitigate future losses.

Spatial Overview of Disasters Across India

The IPCC defines an extreme weather event as “an event that is rare at a particular place and time of year.”

In India, the spatial distribution of these events has been staggering. The 2024 monsoon brought landslides in Wayanad, flash floods in Himachal Pradesh and Jammu, and cloudbursts and mudslides in Dharali, Uttarakhand, claiming multiple lives. Punjab, Bihar, and Assam endured severe floods, while major urban centres such as Mumbai, Delhi, and Bengaluru faced recurrent waterlogging.

Interestingly, the traditionally drought-prone Marathwada region received 128% of its normal monsoonal rainfall between June and September 2024, resulting in immense agricultural and livelihood losses.

Meanwhile, the frequency and intensity of heatwaves have increased dramatically across northern and central India — areas collectively referred to as the heat core zone. This spatial heterogeneity stems from the interplay of local topography, atmospheric patterns, and global climate drivers.

Understanding the Causes and Consequences

A good monsoon remains vital for India’s agriculture, groundwater recharge, and hydropower generation, as 75% of the country’s total rainfall occurs between June and September. However, the temporal and spatial irregularities of rainfall have grown alarmingly unpredictable due to climate change and global warming. These shifts, coupled with unplanned urbanisation, deforestation, and poor infrastructure, exacerbate the severity of disasters.

Flash floods and landslides are now erasing years of investment in public infrastructure, while the psychological trauma of affected communities often goes unaddressed. Rising temperatures and prolonged heatwave conditions are also reducing labour productivity and straining energy and healthcare systems.

Furthermore, inconsistent standards for reporting extreme events across states, fragmented information systems, and the underreporting of losses continue to hinder accurate assessments and effective mitigation.

Bridging the Gaps Through Technology

To address these challenges, integrating modern technologies like Remote Sensing (RS) and Geographic Information Systems (GIS) is essential.

Remote Sensing (RS) refers to the process of collecting information about the Earth’s surface without direct contact, typically through satellites, drones, or aircraft-based sensors. It works on the principles of electromagnetic radiation, where every object with a temperature above absolute zero (-273°C) emits radiation detectable across various spectral bands, including visible, infrared, thermal, and microwave ranges.

Geographic Information Systems (GIS), on the other hand, are computer-based platforms that help organize, store, analyze, and visualize spatial data. When historical RS data—such as from Landsat or LISS satellites—is combined with GIS, it enables long-term tracking of land-use changes, environmental monitoring, and predictive modelling for hazard assessment.

Together, RS and GIS serve as the eyes and brain of modern disaster management, providing real-time locational intelligence that enhances preparedness and response. Drones, as part of RS applications, offer localized spatial insights critical for rapid assessment in affected zones.

Modern Disaster Management Strategies

India is increasingly recognizing the potential of these technologies. Initiatives like Mission Mausam aim to merge next-generation radar and satellite systems with GIS-based automated Decision Support Systems to ensure real-time data dissemination. Such integration facilitates evidence-based policymaking and faster response planning during crises.

A landmark development in this field is the launch of the NASA-ISRO Synthetic Aperture Radar (NISAR) satellite. This joint mission between NASA and ISRO will provide free global data, scanning nearly all land and ice surfaces twice every 12 days and detecting ground shifts as small as one centimetre. The mission is expected to revolutionize disaster prediction, climate change tracking, and environmental monitoring.

Building Climate Resilience: A Policy Imperative

Despite recurring disasters, India’s policy approach has largely remained reactive, focusing on post-disaster relief rather than risk reduction. There is now an urgent need to transition towards preparedness, early warning systems, and community resilience, aligning with the Sendai Framework for Disaster Risk Reduction (2015–2030), which advocates for “managing disaster risks rather than disasters.”

To truly enhance resilience, India must expand its satellite network to improve spatial resolution and data frequency, enabling more accurate early warnings and real-time monitoring. Additionally, the establishment of an integrated national data framework—linking climate data, loss assessments, and hazard maps—can drastically improve coordination across agencies and states.

Given that disasters often transcend administrative boundaries, policies must be shaped by geographical and ecological realities rather than political divisions. A comprehensive, inclusive national adaptation plan, leveraging RS, GIS, and Artificial Intelligence (AI), will be central to safeguarding India’s people, ecosystems, and economy against the escalating threats of climate change.

Harnessing technology for effective disaster management is no longer an option—it is an urgent necessity. By integrating Remote Sensing, GIS, and AI into governance and planning, India can move from a culture of reaction to one of resilience.

Only through this technological and institutional transformation can the nation hope to protect lives, livelihoods, and infrastructure from the intensifying fury of the climate crisis.

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