Presentation + Paper
26 October 2022 Fusion of optical and SAR satellite data for environmental monitoring: assessment of damages and disturbances originated by forest fires
Author Affiliations +
Abstract
In this paper, we propose a processing chain jointly employing Sentinel-1 and Sentinel-2 data aimed at monitoring changes in the status of the vegetation cover by integrating the four visible and near infrared (VNIR) bands with the three red-edge (RE) bands of Sentinel-2, approximately spanning the gap between Red and NIR bands (700 nm – 800 nm) with bandwidths of 15/20 nm and 20 m pixel spacing. The RE bands will be sharpened to 10 m and the resulting 7-bands, 10 m fusion product will be integrated with polarimetric features calculated from the Interferometric Wide (IW) Ground Range Detected (GRD) product of Sentinel-1, available at 10 m pixel spacing. Key point of the fusion of optical bands is the correction of atmospheric path radiance before fusion is accomplished through modulation of the interpolated band by a sharpening term achieved through the hyper-sharpening paradigm. Whenever surface reflectance data are available, haze estimation and correction can be skipped. Hyper-sharpening of Sentinel-2 multispectral (MS) bands and modulation-based integration of Sentinel-1 polarimetric synthetic aperture radar (SAR) features are applied on a multitemporal dataset acquired before and after a recent fire event.
Conference Presentation
© (2022) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Luciano Alparone, Alberto Arienzo, Andrea Garzelli, Simone Lolli, and Claudia Zoppetti "Fusion of optical and SAR satellite data for environmental monitoring: assessment of damages and disturbances originated by forest fires", Proc. SPIE 12267, Image and Signal Processing for Remote Sensing XXVIII, 122670E (26 October 2022); https://doi.org/10.1117/12.2638984
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KEYWORDS
Synthetic aperture radar

Polarimetry

Vegetation

Image enhancement

Spatial resolution

Data fusion

Reflectivity

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