Remote sensing-based prediction of forest fire characteristics

C. Maffei

Optical and Laser Remote Sensing

Research output: Thesis › Dissertation (TU Delft)

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2021
Combining multi-spectral and thermal remote sensing to predict forest fire characteristics
Maffei, C., Lindenbergh, R. & Menenti, M., 2021, In: ISPRS Journal of Photogrammetry and Remote Sensing. 181, p. 400-412 13 p.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
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11 Citations (Scopus)

70 Downloads (Pure)
2019
Predicting forest fires burned area and rate of spread from pre-fire multispectral satellite measurements
Maffei, C. & Menenti, M., 2019, In: ISPRS Journal of Photogrammetry and Remote Sensing. 158, p. 263-278 16 p.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
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25 Citations (Scopus)

97 Downloads (Pure)
2018
Relating spatiotemporal patterns of forest fires burned area and duration to diurnal land surface temperature anomalies
Maffei, C., Alfieri, S. M. & Menenti, M., 1 Nov 2018, In: Remote Sensing. 10, 11, 1777.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access
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31 Citations (Scopus)

45 Downloads (Pure)
2014

A MODIS-based perpendicular moisture index to retrieve leaf moisture content of forest canopies
Maffei, C. & Menenti, M., 2014, In: International Journal of Remote Sensing. 35, 5, p. 1829-1845 17 p.
Research output: Contribution to journal › Article › Scientific › peer-review

Open Access

11 Citations (Scopus)