## 5 Discussion  
Our research shows that the public medium-resolution remote sensing image has the ability of stable response and large range observation in detecting the change of urban burning and damaged buildings caused by armed conflict. However, optical satellite imaging is usually affected by clouds, rain, snow and other weather conditions, especially in a battlefield environment filled with smoke, which greatly affects the effectiveness of earth observation. Therefore, the joint observation of optical and SAR images is the key to solving the problem.  
The IFB-CEM we designed allows for better detection of burning areas by more effectively separating burning and non-burning area responses. However, it is greatly affected by the preset sample target spectral curve, so it is necessary to choose the pixel of a burning area with moderate energy as far as possible to balance the detection of the potential weak burning area and super strong burning center area.  
In addition, the DPNCI of medium-resolution SAR images can better depict the distribution and change trend of damaged buildings in the conflict [48]. Combined with the area and intensity of nighttime lighting in Mariupol [49], the damaged buildings are closely related to nighttime light changes in time and space. Nevertheless, the lack of high resolution will cause a change of coherence not only from the damage to the building structure. For example, the coherence of small buildings and buildings with high urban greening degrees is easily affected by the scattering of electromagnetic waves by other ground objects, which brings uncertain factors to the detection of damaged grades.  
At the same time, we should fully realize the important role of public internet data in assisting remote sensing image interpretation, which can quickly provide relatively reliable information before the lack of real statistics. It should be noted that without understanding the actual situation of the study area, it is extremely difficult and time-consuming to locate these data from the Internet on the map. In the experiment, we locate the damaged buildings in the image by looking for iconic ground objects. For this work, perhaps Cross  
Figure 14: The change map of building damage in Mariupol.  
View Matching technology for Image-Based Ground-to-Aerial Geo-Localization can be efficiently completed [50]. Moreover, the classification of damaged degree also has a certain degree of subjectivity in this study; the accuracy of damage results obtained by inversion of the empirical model obtained by visual interpretation and statistics still has great room for improvement. In fact, the humanitarian disaster survey results released by UNITAR are a valuable reference, and we also note that these data have been used as an assessment basis in relevant studies [20; 22]. Figure 15 shows the damaged buildings result of Mariupol interpreted and released by UNITAR according to the worldview-2 image on 14 March 2022 [51]. Regrettably, we did not adopt it because we do not know what standard UNITAR uses to divide the damage degree of buildings, and the worldview-2 image and Sentinel-1 image are not acquired simultaneously, and the time difference may lead to different damage degrees of the same building, especially in the most intense period of conflict.  
According to the above discussion and the inversion results of the damage degree of the building, we believe that the overall low accuracy is also due to the time difference between SAR images and acquired images or photos from the Internet.