New report titled “Amplifying the Global Value of Earth Observation” by the World Economic Forum has shed light on the immense potential of Earth Observation (EO) data to drive economic growth and sustainability worldwide.Earth observation data involves collecting, analysing, and presenting information about the Earth’s physical, chemical, and biological systems using remote sensing technologies.It involves acquiring information about the Earth’s surface, such as land cover, oceans, agriculture, and forestry, through energy emission and processing of reflected images.It is achieved through remote sensing, which is a geospatial technology that collects data about an object, place, or phenomenon without making physical contact with it.
Key Highlights of the Report
- Potential Economic Impact of EO Data: EO data could generate over USD 3 trillion in economic benefits globally by 2030.The global value of EO data is expected to grow from USD 266 billion currently to over USD 700 billion by 2030.This could contribute a cumulative USD 3.8 trillion to the global Gross Domestic Product (GDP) by 2030.
- Environmental Benefits: EO data can help eliminate 2 gigatonnes of greenhouse gas emissions annually by 2030.This is equivalent to the estimated combined annual emissions of 476 million gasoline-powered cars.EO can monitor climate variables, emissions, ecosystems, and biodiversity to inform actions to mitigate climate change and protect natural habitats.
- Regional Opportunities: The Asia Pacific region is poised to capture the largest share of EO’s value by 2030, reaching a potential value of USD 315 billion.Africa and South America are positioned to realise the largest percentage growth in EO data value.
- EO Blended with Enabling Technologies: Enabling technologies like artificial intelligence (AI) and digital twins can catalyse the adoption of EO data.A digital twin is a virtual representation of an object or system that accurately reflects a physical object. It covers the object’s entire lifecycle, is updated with real-time data, and utilises simulation, machine learning, and reasoning to aid in decision-making.
Key Areas of Application of Earth Observation Data
- Environmental Monitoring and Management: Monitoring deforestation and illegal logging activities in the forests like Amazon rainforest using satellite imagery.Tracking the spread of deserts and monitoring desertification in regions like the Sahara.Monitoring the coastal areas and marine ecosystems, such as coral reef bleaching and oil spills.
- Agriculture and Precision Farming: Using multispectral imagery to monitor crop. health, estimate yields, and optimise precision agriculture practices for crops like wheat, rice, and corn.Assessing soil moisture levels in agricultural fields and identifying areas requiring irrigation in regions prone to drought.Detecting and mapping the spread of pests and diseases affecting crops.
- Urban Planning and Development: Mapping urban areas and monitoring urban sprawl in rapidly growing cities like Shanghai(China) and Mumbai(India).Identifying suitable locations for infrastructure development, such as new roads, airports, and housing projects.Monitoring changes in land use patterns and urban growth in megacities like Tokyo (Japan).
- Natural Resource Management: Mapping and monitoring mineral resources and mining activities in regions like the Permian Basin in the US (second-largest shale gas producing region in the US).Monitoring water resources, such as lakes, rivers, and groundwater levels in areas prone to water scarcity, like parts of Africa and the Middle East.
- Climate Change Studies: Monitoring changes in glaciers, sea ice, and polar regions, such as the Arctic and Antarctic.Tracking global temperatures and atmospheric conditions, including greenhouse gas emissions and their impact on climate.Disaster Management and Emergency Response: Assessing the extent of damage caused by natural disasters like hurricanes, earthquakes, and wildfires.
- Identifying areas affected by disasters for targeted relief efforts, such as the 2004 Indian Ocean tsunami.