# Remote Sensing-Based Proxies for Urban Disaster Risk Management and Resilience: A Review
## 4 Remote Sensing-Based Proxies for DRM in Urban Areas
### Natural RS-Based Proxies  
Table 8 lists existing RS-based proxies capturing the natural environment for urban DRM. As one of the most important sources of information for assessing urban DRM, the natural environment relies on the vegetation cover information. Vegetation spatial heterogeneity serves as a proxy to extract changes in vegetation pattern, and to monitor ecosystem changes before and after a disaster at the landscape scale for natural damage assessment [149]. Spatial heterogeneity may affect functions and processes in ecological systems, which is a key to assess ecosystem changes [150]. Vegetation cover has been used as a proxy to extract the damages to the natural and ecological environment of an urban area by comparing the vegetation cover before and immediately after a disaster [99; 151]. Decrease in vegetation cover ratio of an area demonstrates the ecological damage ratio. In a different study, [PERSON], et al. [152] use vegetation cover change to assess the long-term effects of a hurricane in the urban natural environment recovery in New Orleans after Hurricane Katrina. Specifically, while using MODIS and Landsat images, [PERSON] and colleagues assess the period from immediately after the event to ten years later to discover that a decade later the vegetation cover is still at a lower level than before Katrina, indicating that the area has not yet fully recovered. Similarly, [PERSON], et al. [47] and [PERSON], et al. [46] use vegetation cover maps to assess the changes in vegetation/natural environment patterns in the recovery processes using NDVI between year1-year2. In addition, the cover ratio for various vegetation classes can provide detailed and reliable information for damage and recovery assessments. Fractional vegetation cover [153; 154], which represents the vegetation ecological function, and vegetation cover type [154], have also been used to assess the vegetation recovery after a disaster. Fractional vegetation index can be computed using NDVI values of vegetation and soil, and is a powerful tool for vegetation cover classification and extraction [155]. A change analysis allows for computing the vegetation recovery rate. In addition, vegetation offers an important ecosystem service in flood-prone areas by providing a low drainage density and high permeable surfaces, thus contributing to preventing floods [156]. Accordingly, vegetation cover ratio has also been used as a proxy for vulnerability assessment of urban areas, particularly for water-related hazards [103; 39; 106]. Furthermore, vegetation cover ratio has been used as a proxy to evaluate the biophysical [106] and ecological [157] vulnerability, as well as resilience. A higher ratio of vegetation cover signified and increase in resilience (the vegetation coverage is one of the most important indicators for measuring ecological capacity for self-restoration). In a similar study, [PERSON] and [PERSON] [158] use the Standard Deviation of NDVI as a proxy to extract diversity of the plants in vegetated areas for vulnerability assessment. Debris and floodwater removal are also important for environmental recovery after a disaster, as it provides space for the vegetated area to regrow [32; 46; 49; 88; 97]. The environmental role of public spaces and urban green areas, in addition to providing clean air, is to provide habitats for biodiversity and helps to regulate temperature. Therefore, it has been used as a proxy to assess natural recovery processes [34; 48]. Presence of debris, mud, and salt in water as an indicator of water contamination [34; 49] and the availability of land as a provision of access to recreation has been employed as proxies for natural recovery assessment. [PERSON] and [PERSON] [49] used the permeability of surfaces to measure environmental quality as a proxy for recovery assessment. For example, the permeability of impervious surfaces is very low in urban areas, which leads to an increase in flood frequency and storm flows, and consequently influences urban climate and pollution levels [159].