## 3 Literature Review and Comparison of Interferometric Coherence and Intensity Correlation
### Improvement of SAR Data Based Damage Assessment Techniques by Additional Data
[PERSON] and [PERSON] [105] applied the aforementioned approach to the 1999 Izmit, Turkey Earthquake using ERS SAR imagery. Furthermore, they reported an unsupervised procedure, which uses both the interferometric coherence, as well as the SAR intensity as input for the statistical analysis of a city block of the urban area of the AoI. According to [PERSON] and [PERSON] [105], the lognormaldistribution is best suited in urban areas applications as this distribution best adapts to abrupt changes in the intensity caused by the high density of strong scatters in urban area. [PERSON] _et al._[104] applied the aforementioned unsupervised methodology additionally to the 1999 G dc uk (Turkey) and the Bam 2003 (Iran) Earthqu using pre- and post-event ERS-1/2 and ENVISAT ASAR imagery, respectively. The authors reported a good similarity between the damage patterns achieved by the SAR amplitude, intensity correlation and the coherence based statistical analysis with a slightly increase of the overall accuracy for the combination of intensity correlation and coherence analysis. Furthermore, the authors found out that the interferometric coherence is better suited for the detection of slightly damaged areas in comparison to the SAR intensity. Additionally to the aforementioned (Section 3.2) SAR backscattering investigation of the 2008 Wenchuan Earthquake in China by [PERSON] and [PERSON] [113], the authors used optical FORMOSAT-2 and ASTER imagery to increase the information content of their damage assessment. To detect damaged buildings after the Haiti Earthquake (2010), [PERSON] and [PERSON] [10] used pre- and post-disaster SAR data of TerraSAR-X. Their SAR backscattering and intensity correlation based damage assessment approach is supported by building polygons derived from the post-disaster need assessment (PDNA) survey atlas. The PDNA atlas was produced by the UNTAR/UNOSAT collaboration with several agencies, such as the World Bank [126]. Furthermore, vegetated areas were excluded before the damage assessment processing using pre-disaster (Quickbird) optical imagery. Their procedure achieved an overall accuracy of _ca._ 74%, with a user's and producer's accuracy for the damaged buildings of _ca._ 67% or 41%, respectively. Investigating the 2009 L'Aquila, Italy, Earthquake, [PERSON] _et al._[115] (described in more detail in Section 3.6) improved the accuracy of their damage assessment from 65.5% (using only the SAR data of COSMO-SkyMed) up to 81% when fusing the information derived from SAR and optical (Quickbird and IKONOS) data. In conclusion, this section clearly demonstrated the surplus value of additional data such as optical imagery and GIS data to increase the accuracy and usability of damage assessment based on SAR imagery. Thereby, (I) pre-event optical imagery can be used to mask out vegetated areas, which would disturb the damage analysis results (temporal de-correlation of vegetated areas) [8,10]; or (II) an image pair of pre- and post-event optical imagery can directly be incorporated into the damage assessment together with the SAR imagery [7,78,113,115]. Besides to increasing the accuracy of the damage assessment by the additional use of GIS data [2,104,105,125], such information also enables the generation of damage maps, which are more suited to the user, as the damage levels are presented at meaningful distributions (e.g., city parcel boundaries, building blocks, _etc._). Moreover, as already mentioned in Section 3.2, with the availability of very high spatial resolution (1-3 m) SAR sensors such as TerraSAR-X and COSMO-SkyMed (both launched in 2007), the analysis of more recent earthquakes with this SAR data enabled more detailed analysis [10,115]. Contrary to this, studies of natural disasters happened before 2007 rely on data from SAR missions with coarser spatial resolution such as ERS, ENVISAT ASAR, and ALOS PALSAR (_cf._ Table 2). This enables damage assessment at the block level or at the scale of city parcels.