Nowadays disasters increase in both intensity and frequency. The Sustainable Development Goals agenda during the 2015 UN session, as well as the Sendai Framework for Disaster Risk Reduction (2015 -2030), have paid much attention to disaster risk reduction. For example, Goal 11 (Make cities and human settlements inclusive, safe, resilient and sustainable) and Goal 13 (Take urgent action to combat climate change and its impacts) cover many of the main aspects related to disaster risk reduction in the context of sustainable development.
Disaster data is crucial as it links science based assessment to aid policy development for disaster risk reduction. Disaster data, therefore could contribute to many applications, such as hazards mapping, disaster risk modelling, disaster loss compensation, disaster loss accounting, at various spatial and temporal scales, such as national, regional and global. This multi-faceted aggregation requires consistency and standardization of data, minimizing biases and errors while increasing compatibility in quality and in frequency of data generation.
Big Earth Data is a type of big data associated with the Earth sciences, derived from but not limited to Earth observation. It is becoming a new frontier in contributing to the advancement of Earth science and significant scientific discoveries. Since the launch of the first Earth observation satellite in 1962, the spatial, spectral and radiometric resolutions of satellite sensors have increased dramatically, composing a large amount of Big Earth Data. European Commission, and countries like China, United Sates, Russia, France, Italy, India, Japan, and Brazil have developed national or regional level Earth observation missions. All of them are composed of the Global Earth Observation System of Systems (GEOSS).
Satellite based spatial data and technologies, especially Big Earth Data approaches, are an essential tool for improving our understanding of disaster risks, and for coordinated efforts to reduce climate change and sustainable development. Although the large amount of Big Earth Data exist, managing and using the large amount of data, especially for disasters are challenging.
Therefore, we encourage authors to submit Original Research and Review articles to improve knowledge on disaster risk reduction with Big Earth Data. Potential contributions could include, but are not limited to:
• Hazards mapping methodologies and applications;
• Disaster risk modelling and prediction;
• Disaster loss compensation and accounting;
• Disaster assessment and data management.
Nowadays disasters increase in both intensity and frequency. The Sustainable Development Goals agenda during the 2015 UN session, as well as the Sendai Framework for Disaster Risk Reduction (2015 -2030), have paid much attention to disaster risk reduction. For example, Goal 11 (Make cities and human settlements inclusive, safe, resilient and sustainable) and Goal 13 (Take urgent action to combat climate change and its impacts) cover many of the main aspects related to disaster risk reduction in the context of sustainable development.
Disaster data is crucial as it links science based assessment to aid policy development for disaster risk reduction. Disaster data, therefore could contribute to many applications, such as hazards mapping, disaster risk modelling, disaster loss compensation, disaster loss accounting, at various spatial and temporal scales, such as national, regional and global. This multi-faceted aggregation requires consistency and standardization of data, minimizing biases and errors while increasing compatibility in quality and in frequency of data generation.
Big Earth Data is a type of big data associated with the Earth sciences, derived from but not limited to Earth observation. It is becoming a new frontier in contributing to the advancement of Earth science and significant scientific discoveries. Since the launch of the first Earth observation satellite in 1962, the spatial, spectral and radiometric resolutions of satellite sensors have increased dramatically, composing a large amount of Big Earth Data. European Commission, and countries like China, United Sates, Russia, France, Italy, India, Japan, and Brazil have developed national or regional level Earth observation missions. All of them are composed of the Global Earth Observation System of Systems (GEOSS).
Satellite based spatial data and technologies, especially Big Earth Data approaches, are an essential tool for improving our understanding of disaster risks, and for coordinated efforts to reduce climate change and sustainable development. Although the large amount of Big Earth Data exist, managing and using the large amount of data, especially for disasters are challenging.
Therefore, we encourage authors to submit Original Research and Review articles to improve knowledge on disaster risk reduction with Big Earth Data. Potential contributions could include, but are not limited to:
• Hazards mapping methodologies and applications;
• Disaster risk modelling and prediction;
• Disaster loss compensation and accounting;
• Disaster assessment and data management.