Remote sensing-based prediction of forest fire characteristics

C. Maffei

Optical and Laser Remote Sensing

Research output: Thesis › Dissertation (TU Delft)

169 Downloads (Pure)

4 Article

4 results

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
File
5 Citations (Scopus)

47 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
File
16 Citations (Scopus)

80 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
File
25 Citations (Scopus)

40 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

10 Citations (Scopus)