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Satellite Remote Sensing Contributions to Wildland Fire Science and Management
Title | Satellite Remote Sensing Contributions to Wildland Fire Science and Management |
Publication Type | Journal Article |
Year of Publication | 2020 |
Authors | Chuvieco, E, Aguado, I, Salas, J, Garcia, M, Yebra, M, Oliva, P |
Journal | Current Forestry Reports |
Date Published | 04/2020 |
Keywords | fire detection, management, remote sensing, Wildfire |
Abstract | PurposeThis paper reviews the most recent literature related to the use of remote sensing (RS) data in wildland fire management. Recent FindingsStudies dealing with pre-fire assessment, active fire detection, and fire effect monitoring are reviewed in this paper. The analysis follows the different fire management categories: fire prevention, detection, and post-fire assessment. Extracting the main trends from each of these temporal sections, recent RS literature shows growing support of the combined use of different sensors, particularly optical and radar data and lidar and optical passive images. Dedicated fire sensors have been developed in the last years, but still, most fire products are derived from sensors that were designed for other purposes. Therefore, the needs of fire managers are not always met, both in terms of spatial and temporal scales, favouring global over local scales because of the spatial resolution of existing sensors. Lidar use on fuel types and post-fire regeneration is more local, and mostly not operational, but future satellite lidar systems may help to obtain operational products. Regional and global scales are also combined in the last years, emphasizing the needs of using upscaling and merging methods to reduce uncertainties of global products. Validation is indicated as a critical phase of any new RS-based product. It should be based on the independent reference information acquired from statistically derived samples. SummaryThe main challenges of using RS for fire management rely on the need to improve the integration of sensors and methods to meet user requirements, uncertainty characterization of products, and greater efforts on statistical validation approaches. |
URL | https://link.springer.com/article/10.1007/s40725-020-00116-5?wt_mc=socialmedia.twitter.1.SEM.ArticleAuthorOnlineFirst |
DOI | 10.1007/s40725-020-00116-5 |
Refereed Designation | Refereed |
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