## 2 Study Area and Data
### Data Source  
The remote sensing data used in this study are all from freely available public satellite images. The optical image mainly adopts the Sentinel-2A/2B satellite Level-1C images provided by European Space Agency (ESA) [32]. Sentinel-2 is a wide-swath, high-resolution, multi-spectral imaging mission supporting Copernicus Land Monitoring studies, including the monitoring of vegetation, soil and water cover, as well as observation of inland waterways and coastal areas [33]. Each of the satellites carries a multi-spectral instrument (MSI), covering 13 spectral bands in the visible, near-infrared (NIR), and short-wave infrared (SWIR) ranges: four bands at 10 m, six bands at 20 m and three bands at 60 m spatial resolution [34]. The satellite group has a revisit period of 5 days, and the Level-1C product is the atmospheric apparent reflectance product after ortho correction and geometric precision correction. In order to make up for some of the images that could not be used due to excessive cloud cover and to form a dense time series data stack, we also collected Level-1C products of the Landsat-8/9 satellite from the United States Geological Survey (USGS) [35]. The payload of the satellite group is the Operational Land Imager (OLI) and the thermal infrared sensor (TIRS), which can acquire images in 11 bands from visible to short-wave infrared range, including eight visible and infrared bands with a resolution of 30 m, one  
Figure 1: Geographical location of the study area. panchromatic band with a resolution of 15 m and two thermal infrared bands with a resolution of 100 m [36]. The sensors carried by Landsat-9 have improved radiation accuracy and have more vital ground object detection ability [37]. The satellite group had a revisit period of 8 days. In addition to collecting all images that were not obscured or slightly obscured by clouds during the conflict period (24 February 2022-16 May 2022), we also collected two images before the conflict and an image after the conflict for comparative analysis. The specific time and type of optical remote sensing images used in this study are shown in Figure 2.  
The Sentinel-1A satellite launched by ESA was used to map the change in urban building damage. It is a C-band (\(\lambda=5.6\) cm) medium-resolution SAR satellite with four imaging modes: Stripmap (SM), Interferometric Wide Swath (IW), Extra-Wide Swath (EW), and Wave (WV), with a revisit period of 12 days [38]. We acquired Sentinel-1A single look complex (SLC) images in IW mode from the Alaska Satellite Facility [39] from 4 February to 23 May 2022. These images are all descending orbit images with both VH and VV polarization, and the spatial resolution is 5 m \(\times\) 20 m. The temporal and spatial baselines between Sentinel-1A image pairs adopted in the study are shown in Figure 3; the positive and negative of the spatial baseline represent the difference between the baseline direction and the defined positive direction. Figure 3: The temporal–spatial baseline of SAR image pairs. Figure 2: Time series optical image of the study area. The vector data of buildings, land use types and roads used in the experiment came from the Open Street Map (OSM) platform [40]. These data contributed by platform registrants have the characteristics of inconsistent timeliness and complete alignment between the vector boundary of buildings and ground objects in satellite images. However, we tend to pay more attention to macro-scale damage and its change trend in large-scale armed conflicts. In medium-resolution images, a slight deviation of the building vector will not significantly impact the evaluation results, so we allow such errors.