## 3 Literature Review and Comparison of Interferometric Coherence and Intensity Correlation
### SAR Amplitude Data with Focus on Intensity Correlation
Their procedure achieved good match with public damage reports and aerial photo analysis. For the 2008 Wenchuan Earthquake [PERSON] and [PERSON] [113] investigated the relationship between building damage level and the differences of the backscattered SAR intensity values in pre- and post-disaster ALOS PALSAR imagery. They were able to distinguish three damage classes ranging from slightly to moderately and extremely destroyed. The authors mentioned that due to the long repeat cycle of the space-borne SAR missions rapid changes on the ground (_i.e._, damages) caused by a series of aftershocks cannot be separated. Only the summary of all changes that occurred in the time period between two repeat cycles can be detected. This is especially true for the ALOS PALSAR data (repeat cycle 44 days, _cf._ Table 2), which was used by [PERSON] and [PERSON] [113]. [PERSON] and [PERSON] [101] proposed a building damage ratio estimation model for L-band SAR imagery. They adapted a former procedure based on C-band SAR data to L-band using pre- and post-event JERS-1 data from the 1995 Kobe Earthquake, Japan, as training. Then, they applied their model to the 2007 Chincha Earthquake, Peru, using ALOS PALSAR imagery. Comparison of their damage assessment results with field survey data showed a qualitatively good agreement of the distribution of the building damage, especially for seriously and severely damaged buildings. Based on ENVISAT ASAR data, [PERSON] _et al._[121] investigated the 2011 Tohoku Earthquake, Japan, and reported a decrease of the SAR backscattering in damaged urban area caused by the decrease of the double bounce effect. However, one has to take into account that the tsunami, which reached the coast shortly after the Earthquake, washed numerous buildings away. This effect also strongly reduced the SAR backscatter. For the damage assessment of the 2009 L'Aquila Earthquake, Italy, [PERSON] _et al._[114] investigated changes of double bounce features using co-registered and calibrated (sigma naught) pre- and post-event COSMO-SkyMed imagery. The authors reported good agreement of their damage assessment results with visual analysis of optical imagery. Based on the developments reported in [114], [PERSON] and [PERSON] [118] developed an unsupervised damage detection technique based on amplitude data of very high spatial resolution SAR sensors (e.g., TerraSAR-X and COSMO-SkyMed) acquired at similar imaging geometry (see also Section 2). Curvilinear features are extracted from the pre-event imagery. Next, double-bounce candidates are selected to derive a simplified geometrical building model. The damage is detected by comparison with post-event SAR data. This method is suited for analysis of single buildings. However, as the method focuses on the analysis of double bounce features (_i.e._, building walls), at several circumstances the damage level of the building is either under- or overestimated. For instance, at their test site Port-au-Prince, Haiti (Earthquake 2010), the authors reported an underestimation of the damage level for buildings with collapsed roofs, but still intact walls. On the other hand, the damage level is overestimated for slightly damaged buildings where only one part collapsed. However, due to its strong double bouncing this part has a strong influence on the derived building model. In general, this method is a good approach for damage assessment of single buildings. Combination with other techniques will provide more accurate results. Summarizing Section 3.2 we can distinguish between methods suited for damage assessment at the block level [9,97,121] and procedures enabling the damage analysis at the scale of single buildings [114,118]. The former is based on SAR data with a spatial resolution ranging from 8 to 30 m and coarser (Radarsat-1, ERS, ENVISAT, JERS and ALOS PALSAR, _cf._ Table 2), while the latter uses X-band SAR missions with very high spatial resolution of 1-3 m (e.g., COSMO-SkyMed and TerraSAR-X).