Big data offers significant potential for enhancing climate resilience. By combining big data with traditional knowledge, and social research, we can develop comprehensive and inclusive resilience strategies.
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This is part of the essay series: World Population Day 2024
Big data, characterised by vast volumes of structured and unstructured data generated at high velocity, has become a pivotal tool in addressing climate change. Fuelled by advances in computing, digital technologies, and the widespread availability of the internet, big data offers researchers unprecedented capabilities to handle intricate datasets, enabling more precise and nuanced data gathering and analysis. For development practitioners, this new era of data presents an opportunity to adopt innovative strategies for enhancing climate resilience. By leveraging large-scale datasets, practitioners can observe and assess the impacts of climate-related shocks and stressors with greater accuracy. This capability enables the formulation of more effective resilience-building strategies that address both immediate challenges and long-term climate impacts.
Due to its undoubted benefits, recent years have witnessed several use cases of big data, combined with advanced computing and algorithms, in climate action. For instance, big data technologies have been utilised to improve the accuracy of weather forecasts and climate models. Other examples include use of big data analytics for predicting forest fires and natural disasters.
Due to its undoubted benefits, recent years have witnessed several use cases of big data, combined with advanced computing and algorithms, in climate action.
However, despite these technological advancements, big data alone is not sufficient to achieve comprehensive climate resilience. This is particularly true in the context of the Global South, where a majority of the people most vulnerable to climate impacts live, yet are least equipped to anticipate, prepare, and act in the face of it. Such communities include agriculturalists, pastoralists, fisherfolk, forest-dwellers, and urban dwellers living in precarious or stressed conditions. While these communities stand to gain significantly from the application of big data, they also face unique hurdles and challenges.
Effectively addressing the multifaceted challenges of climate change, and building resilience of the most vulnerable, requires that we centre our efforts on people and communities, integrating their knowledge, experiences, and needs into resilience-building strategies and technologies.
For countries in the Global South, where the effects of climate change are often felt most acutely, the ability to predict and prepare for extreme weather events is invaluable. One of the most promising applications of big data in the Global South is its ability to enhance predictive capabilities. By integrating diverse data sources such as satellite imagery, sensor networks, and historical climate records, big data can improve the accuracy of weather forecasts and climate models. This allows for more precise predictions of extreme weather events, such as floods, droughts, and cyclones, providing critical lead time for communities to take preventive measures. For example, in India, big data analytics has been utilised to provide detailed weather forecasts and agricultural advice to farmers. This has helped them make informed decisions about planting and harvesting, thereby reducing crop losses and enhancing food security.
Similarly, big data can enable policymakers in the Global South to make more informed decisions regarding climate resilience. By analysing patterns in environmental data, governments can identify vulnerable areas and allocate resources more effectively. This data-driven approach can guide urban planning, and disaster preparedness strategies, ensuring that interventions are both targeted and effective.
Similarly, big data can enable policymakers in the Global South to make more informed decisions regarding climate resilience. By analysing patterns in environmental data, governments can identify vulnerable areas and allocate resources more effectively.
Similarly, the use of mobile technologies and social media by individuals and communities to share and access information about upcoming weather events and disasters can empower them to take timely actions and enhance overall preparedness. Moreover, the data generated from these communication channels becomes a valuable source of big data, with a close focus on people and their voices, and thus a useful tool to support disaster risk reduction, including preparedness, response, and post-event recovery activities.
One of the significant challenges in the Global South is the quality and integration of data. Many regions lack the infrastructure needed to collect comprehensive and accurate environmental data. Data gaps, coupled with inconsistent quality across different sources, can lead to unreliable analyses and misguided decisions. Bridging this needs investment in robust data collection and monitoring systems. Furthermore, integrating data from various sources—satellites, ground sensors, and citizen reports—into a cohesive analytical framework is complex. It requires advanced technical expertise and resources that are often in short supply in these regions.
The processing and analysis of large datasets demand substantial computational power and sophisticated algorithms. In many parts of the Global South, access to advanced computing infrastructure is limited, hindering the ability to fully leverage big data. This technological gap can result in slower, less accurate analyses, reducing the effectiveness of resilience strategies. Building local capacity through training and investment in technology is crucial to overcoming these limitations.
Many vulnerable populations, particularly those in the Global South, exist within a “surveillance gap”, often undocumented and excluded from development efforts. This invisibility gap means that big data models may perpetuate existing exclusions, rendering vast numbers of people invisible. These populations, most vulnerable to climate change, are in dire need of resilience interventions. To close the surveillance gap, big data systems must be designed to include all segments of society. For instance, in times of drought, public data systems like India’s digital ID system, Aadhar, can help deliver targeted benefits to millions of small and marginal farmers.
Many vulnerable populations, particularly those in the Global South, exist within a “surveillance gap”, often undocumented and excluded from development efforts.
However, the issue is not only for making vulnerable groups visible but also for ensuring that the information is used for their benefit, not for exploitation or harm. Technological advances in big data can insidiously take away individuals’ autonomy and invade their privacy. This leads to the challenge of a trust deficit in data and data collection practices, due to potentially invasive surveillance practices. Trust is well-established as a core feature of community resilience; surveillance must not damage that trust. Ensuring that data collection practices comply with ethical standards and protect privacy is essential.
Understanding the sociocultural and socioeconomic contexts of communities is critical for designing effective climate resilience strategies. Social research that explores how social, economic, and cultural factors influence vulnerability and adaptive capacity can help design interventions that are not only technically sound but also socially equitable and just. Big data should be used to inform, not dictate, these interventions, ensuring they are tailored to the specific needs and contexts of the communities they aim to serve.
Big data offers significant potential for enhancing climate resilience, but it is not a panacea. The limitations of big data, including the issues of data quality, computational capacity, ethical concerns, and the surveillance gap, highlight the need for a more holistic approach. Climate resilience efforts must centre on people and communities, integrating their knowledge, experiences, and needs into resilience-building strategies.
By combining big data with traditional knowledge, local expertise, and social research, we can develop comprehensive and inclusive resilience strategies. Engaging and empowering communities, building trust, and ensuring ethical data practices are essential for effective climate resilience. Ultimately, resilience is based on the strength and cohesion of communities. By placing people at the centre of our efforts, we can build a more resilient and equitable future in the face of climate change.
Vikrom Mathur is a Senior Fellow at the Observer Research Foundation.
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Vikrom Mathur is Senior Fellow at ORF. Vikrom curates research at ORF’s Centre for New Economic Diplomacy (CNED). He also guides and mentors researchers at CNED. ...
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