Data Fusion for Remote Sensing of Fires and Floods in the Sentinels Era

Dear Colleagues

This Special Issue aims to collect scientific contributions proposing multisource Data Fusion methods for the remotely sensed mapping, monitoring and assessment of fires and floods in the Sentinels Era.

Natural hazards such as fires and floods are phenomena with a large spatial dimension and impact. Mapping, monitoring and assessment can be carried out using satellite remote image platforms. Sentinel missions have brought a new era for operational monitoring, providing reliable and up-to-date information for ecosystem monitoring and managing.

Climate change poses further challenges for the exacerbation of the impacts and effects of extreme events on the ecosystems; in this framework, remotely sensed data can support environmental analyses and monitoring by making particular use of Earth Observation Sentinel missions.

Besides Sentinel, from a broader perspective, Earth Observation systems orbiting the Earth encompass several missions, providing data with distinct spectral, spatial and temporal granularities. Algorithms and methods that are able to fully exploit the complementarity of these systems are necessary to provide robust and operational semantic information that is easily interpretable by humans.

Moreover, the integration of remotely sensed data with data collected by ground/in situ measurements calls for new methods and applications of data fusion to enhance and improve traditional approaches to the remote sensing of natural resources.

This Special Issue aims to collect a broad set of scientific contributions proposing Data Fusion methods for remotely sensed mapping, monitoring and assessment of fires and floods by the use of multisource sensors and data, including both Sentinel and alternative remote-sensing data, in situ sensors and human sensors. Topics of interest include both theoretic and applicative themes:

Dr. Gloria Bordogna
Dr. Daniela Stroppiana
Guest Editors

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