| Summary: | Modern armed conflicts can cause serious humanitarian disasters, and remote sensing technology is critical in monitoring war crimes and assessing post-war damage. In this study, a constrained energy minimization algorithm incorporating the feature bands (IFB-CEM) is designed to detect urban burning areas in optical images. Due to the difficulty of obtaining the ground survey data of the battlefield, the dual-polarization normalized coherence index (DPNCI) is designed based on the multi-temporal synthetic aperture radar (SAR) image, and the quantitative inversion and evaluation of the destruction of urban architecture are combined with the public images on the Internet. The results show that the burning area is widely distributed in the armed conflict region, and the distribution is most concentrated around the Azovstal steel and iron works. The burning area reached its peak around 22 March, and its change is consistent with the conflict process in time and space. About 79.2% of the buildings in the city were severely damaged or completely destroyed, and there was a significant correlation with burning exposure. The results of this study show that publicly available medium-resolution remote sensing data and Internet information have the ability to respond quickly to the damage assessment of armed conflict and can provide preliminary reference information for dealing with humanitarian disasters.
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