The application of an integrated monitoring tool to assess and understand the effects of annually occurring forest fires is presented, with special emphasis to Mediterranean and Temperate Continental zones of Europe. The distinctive features of the information conveyed by optical and microwave remote sensing data have been firstly investigated, and pertinent information have been subsequently combined to identify burned areas at the regional scale. We therefore propose a fuzzy-based multisource framework for burned area mapping, in order to overcome the limitations inherent to the use of only optical data (which can be severely affected by cloud cover or include low albedo surface targets). The relevant experimental validation has been carried out on an extensive area, thus quantitatively demonstrating how our approach successes in identifying areas affected by fires. Furthermore, the proposed methodological framework can also be profitably applied to Sentinel (optical and SAR) data.
Remote sensing of burned area: a fuzzy-based framework for joint processing of optical and microwave data
Daniela Stroppiana;Antonio Pepe;Pasquale Imperatore;Mirco Boschetti;Pietro Alessandro Brivio;Riccardo Lanari
2015
Abstract
The application of an integrated monitoring tool to assess and understand the effects of annually occurring forest fires is presented, with special emphasis to Mediterranean and Temperate Continental zones of Europe. The distinctive features of the information conveyed by optical and microwave remote sensing data have been firstly investigated, and pertinent information have been subsequently combined to identify burned areas at the regional scale. We therefore propose a fuzzy-based multisource framework for burned area mapping, in order to overcome the limitations inherent to the use of only optical data (which can be severely affected by cloud cover or include low albedo surface targets). The relevant experimental validation has been carried out on an extensive area, thus quantitatively demonstrating how our approach successes in identifying areas affected by fires. Furthermore, the proposed methodological framework can also be profitably applied to Sentinel (optical and SAR) data.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.