## 3 Literature Review and Comparison of Interferometric Coherence and Intensity Correlation
### SAR Amplitude Data with Focus on Intensity Correlation  
After reviewing the coherence based damage assessment methods in the previous chapter, this section gives an overview on methodologies, which use the SAR amplitude, especially the intensity correlation (_cf._ Section 2.2). The different appearance of undamaged and damaged buildings in SAR imagery was investigated by [97,123]. By comparing pre- and post-event ERS and JERS SAR intensity data of the 1995 Hygoken-Nanbu Earthquake, Japan, [PERSON] and [PERSON] [97] found out that the SAR backscatter value decrease with increasing damage. In general, artificial structures show comparatively high backscatter values due to double bouncing effects (building wall--ground). Contrary to this, open space and damaged areas are characterized by diffuse scattering of lower intensity values. The authors reported a good match of their damage assessment results with analysis retained from optical satellite imagery (Landsat). The 1999 Kocaeli (Turkey) and the 2001 Gujarat (India) Earthquakes were analyzed by [PERSON] and [PERSON] [102] using a procedure combining SAR intensity correlation and backscatter coefficient approaches. The extracted damage distributions were in good agreement with the actual situations investigated by field surveys. For the analysis of the Gujarat Earthquake a pre- and post-disasterRadarsat-1 image pair (fine mode, 8 m spatial resolution) was used. The temporal and spatial baseline were with more than 400 days and 6 km, respectively, too large for successful application of coherence based damage assessment methods (_cf._ Section 2.1). However, as reported in [PERSON] and [PERSON] [102] SAR intensity based methodologies are suited even for these \"extreme\" conditions. Comparing pre- and post-disaster ERS SAR imagery, [PERSON] and [PERSON] [99] identified notable lower intensity correlation values and backscattering coefficients for damaged areas. Based on their investigations, [PERSON] and [PERSON] [99] developed an automated technique for damage area detection, which showed relatively good agreements with field survey based damage mapping results. In [PERSON] and [PERSON] [100,109], the authors improved their method to be more suitable for the 2003 Bam Earthquake, Iran, and to be able to detect lower damage classes at the 2006 Mid Java Earthquake using the Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) and C-band ENVISAT ASAR imagery, respectively (_cf._ Table 2, Section 1.2). Although the ENVISAT data covered a longer period--which might cause many temporal surface changes not belonging directly to the earthquake--damage assessments using data of both wavelengths showed good agreement in between each other and with field survey reports and visual damage interpretation using high spatial resolution optical imagery. [PERSON] and [PERSON] [100] used the backscattering coefficient of ASAR data to map damaged areas of the 1995 Kobe Earthquake, Japan. The results were compared with interpretation of satellite imagery and field data and showed a relatively good match. [PERSON] _et al._[124] investigated the change of pre- and post-disaster SAR intensity imagery and reported an increase of the intensity values with increasing damage. To determine surface changes (subsidence and uplift) caused by the 2004 Indonesia Earthquake, [PERSON] _et al._[9] used ERS and ENVISAT ASAR data to apply the SAR intensity correlation coefficient and SAR backscattering as basis for visual interpretation (RGB combinations of pre- and post-event intensity correlation or backscatter images, respectively). The results were compared with GPS station data. The authors reported a higher accuracy of their damage assessment when combining both SAR backscattering and intensity correlation compared to the usage of either SAR backscattering or intensity correlation. [PERSON] and [PERSON] [111] used pre- and post-disaster amplitude imagery of the L-band ALOS PALSAR sensor for damage assessment of the 2008 Wenchuan Earthquake, China.