The DOI matches its Crossref record; 150 of the 150 references it cites were found in a registry or an index.
Satellite Remote Sensing Contributions to Wildland Fire Science and Management
Open accessAbstract
Purpose This paper reviews the most recent literature related to the use of remote sensing (RS) data in wildland fire management. Recent Findings Studies 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. Summary The 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.
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Cites
Global fire emissions estimates during 1997–2016
(2017) · doi:10.5194/essd-9-697-2017 · Cited by 2,493
Continuous change detection and classification of land cover using all available Landsat data
Zhu, Z., & Woodcock, C. E. (2014) · Remote Sensing of Environment · doi:10.1016/j.rse.2014.01.011 · Cited by 1,803
The collection 6 MODIS active fire detection algorithm and fire products
Giglio, L., Schroeder, W., & Justice, C. O. (2016) · Remote Sensing of Environment · doi:10.1016/j.rse.2016.02.054 · Cited by 1,617
The Collection 6 MODIS burned area mapping algorithm and product
Giglio, L., Boschetti, L., Roy, D. P., Humber, M. L., & Justice, C. O. (2018) · Remote Sensing of Environment · doi:10.1016/j.rse.2018.08.005 · Cited by 1,286
A human-driven decline in global burned area
Andela, N., Morton, D. C., Giglio, L., Chen, Y., van der Werf, G. R., Kasibhatla, P. S., DeFries, R. S., Collatz, G. J., Hantson, S., Kloster, S., et al. (2017) · Science · doi:10.1126/science.aal4108 · Cited by 1,262
The New VIIRS 375 m active fire detection data product: Algorithm description and initial assessment
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Self-citationAn active-fire based burned area mapping algorithm for the MODIS sensor
Giglio, L., Loboda, T., Roy, D. P., Quayle, B., & Justice, C. O. (2009) · Remote Sensing of Environment · doi:10.1016/j.rse.2008.10.006 · Cited by 657
Chuvieco, E., Mouillot, F., van der Werf, G. R., San Miguel, J., Tanase, M., Koutsias, N., García, M., Yebra, M., Padilla, M., Gitas, I., et al. (2019) · Remote Sensing of Environment · doi:10.1016/j.rse.2019.02.013 · Cited by 619
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Implementation of the LandTrendr Algorithm on Google Earth Engine
Kennedy, R. E., Yang, Z., Gorelick, N., Braaten, J., Cavalcante, L., Cohen, W. B., & Healey, S. (2018) · Remote Sensing · doi:10.3390/rs10050691 · Cited by 562
Cited by
Global and Regional Trends and Drivers of Fire Under Climate Change
Jones, M. W., Abatzoglou, J. T., Veraverbeke, S., Andela, N., Lasslop, G., Forkel, M., Smith, A. J. P., Burton, C., Betts, R. A., van der Werf, G. R., et al. (2022) · Reviews of Geophysics · doi:10.1029/2020rg000726 · Cited by 1,332
Metadata
- Authors
- Chuvieco, E., Aguado, I., Salas, J., García, M., Yebra, M., & Oliva, P.
- Venue
- Current Forestry Reports
- Published
- 2020-04-30
- Volume
- 6
- Issue
- 2
- Pages
- 81-96
- ISSN
- 2198-6436 (ISSN-L)
- OpenAlex
- W3022794580
- Cited by
- 259
- References
- 150
- FWCI
- 8.00
- Type
- journal article
- Language
- en
- Open access
- green
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