Post-event Spaceborne VHR Radar for Seismic Damage Assessment: Integrating Pre-event Optical Data?

Previous work from the authors’ research group has highlighted a link between the level of seismic damage in urban areas, expressed in terms of area rate covered by the damaged buildings within each block, and some numerical indexes derived from texture maps extracted from postevent VHR radar images. The link is unfortunately somehow weak, though visible, and its operational exploitation requires a more reliable connection to be established between texture values and damage level. To do this, one possible approach is that of sorting out the blocks whose behaviour is farther from the “perfect” index-damage correlation and investigating the causes for the mismatch to set a base for corrective measures. This paper illustrates some early findings in such investigation in progress on the 2010 Haiti case as observed in 1-m COSMO/SkyMed spotlight images

Post-event only VHR radar satellite data for automated damage assessment: a study on COSMO/SkyMed and the 2010 Haiti earthquake

In recent years, a number of destructive earthquakes took place around the world. Earth Observation (EO) -based damage assessment was among the tools used to coordinate relief efforts; most of the published maps, however, are still based on weather-dependent optical data and visual interpretation. Only recently, methods based on radar data began to emerge, although not yet consolidated. In this paper we elaborate on a method for damage assessment on urban areas set up on the occasion of the 2008 Sichuan event and tuned on the 2009 L’Aquila earthquake; direct investigation of the 2010 Haiti earthquake, providing an even larger statistical base thanks to the extent of the Port-au-Prince urban area, allowed pinpointing some characteristic behaviours, potentially useful to improve damage assessment results. In particular, we note how results changed thanks to a more reliable and accurate revision of ground truth data and outline a possible start point for correction of damage over/underestimation. Quantitative results are provided

Post-event only VHR radar satellite data for automated damage assessment: a study on COSMO/SkyMed and the 2010 Haiti earthquake

In recent years, a number of destructive earthquakes took place around the world. Earth Observation (EO) -based damage assessment was among the tools used to coordinate relief efforts; most of the published maps, however, are still based on weather-dependent optical data and visual interpretation. Only recently, methods based on radar data began to emerge, although not yet consolidated. In this paper we elaborate on a method for damage assessment on urban areas set up on the occasion of the 2008 Sichuan event and tuned on the 2009 L’Aquila earthquake; direct investigation of the 2010 Haiti earthquake, providing an even larger statistical base thanks to the extent of the Port-au-Prince urban area, allowed pinpointing some characteristic behaviours, potentially useful to improve damage assessment results. In particular, we note how results changed thanks to a more reliable and accurate revision of ground truth data and outline a possible start point for correction of damage over/underestimation. Quantitative results are provided

Damage Assessment in Post-Event VHR Radar Images: a Preliminary Study on COSMO/SkyMed Data from 2009 Italy Earthquake

EO-based earthquake damage assessment is a valuable tool to support management of the post-earthquake phase. Most methods available so far either rely on visual interpretation or pre-post-event comparison. Pre-event data may not be available when Very High Resolution spaceborne data is used. In this paper we present some basic facts that may eventually lead to a damage assessment method requiring only post-event data

Urban block outlining in High-Resolution SAR images based on detection of linear features

While analysing remotely sensed images of urban areas, in many cases an at least approximate knowledge of block partition is useful for specialising operations over areas within which a certain degree of homogeneity can be assumed. In the case of use for emergency management, though, this information may not be accessible in a reasonable time or with a reasonable effort, while it would be useful as a basis for e.g. earthquake damage assessment at the block level [1]. Automatic extraction of block boundaries becomes thus an interesting tool to fill this possible gap. City blocks are usually separated by major urban roads, and a linear feature extractor, originally developed for road network extraction, can provide basic features upon which to partition a very high resolution SAR scene acquired over an urban area. After the first experiments described in [2], the method has been improved and new results produced on a series of COSMO/SkyMed images over geohazard-prone areas. [1] Dell'Acqua, F., Polli, D., Lisini, G. (2010). “ Automatic Mapping of Earthquake Damage using Post-event Radar Satellite Data: The Story Goes On”. Proceeding of the 30th EARSeL Symposium, Paris, France, 31th May - 4th June 2010. [2] Fabio Dell'Acqua, Paolo Gamba, Luca Odasso, Gianni Lisini (2009): "Segment-based urban block outlining in High-Resolution SAR images". Proc. of the 2009 Joint Urban Remote Sensing Event (JURSE 2009), 20-22 May 2009, Shanghai, P.R.C. Unformatted CD-RO

Mapping Earthquake Damage from Post-Event only VHR SAR Texture Maps: Zooming into Poor Estimation Cases

The use of EO data in earthquake contexts, especially for damage assessment purposes, has been widely proposed and a number of results have been presented after every event, mostly based on optical data and some degree of manual interpretation. Our research group tries and focus on radar data and on automatization of the damage assessment procedure by investigating the pos-sibility to use only post-event, Very High Resolution (VHR) radar data to estimate the damage level aggregated at the size of the city block. The usefulness of considering post-event only data lies in the independence from availability of pre-event VHR data, still quite scarce given the young age of meter-resolution spaceborne SAR systems like for the COSMO/SkyMed data used for these experiments. Preliminary research has highlighted some degree of connection between the damage level and the block-averaged values of some texture maps, which is probably a consequence of the different aspects in VHR SAR images between undamaged and damaged buildings. After the 2008 event in Sichuan, China, the 2009 event in L'Aquila, Italy the 2010 event in Haiti is currently being investigated and special attention is being given to the urban blocks whose damage estimates appears to diverge more from the actual situation on the ground. This paper illustrates the latest findings

Integration of EO-based vulnerability estimation into EO-based seismic damage assessment: a case study on L’Aquila, Italy, 2009 earthquake

Remote sensing is proving very useful for identifying damage and planning support activities after an earthquake has stricken. Radar sensors increasingly show their value as a tool for damage detection, due to their shape-sensitiveness, their extreme versatility and operability all weather conditions. The previous work of our research group, conducted on 1-m resolution Spotlight images produced by COSMO-SkyMed, has led to the discovery of a link between some selected texture measures, computed on radar maps over single blocks of an urban area, and the damage found in these neighborhoods. Texture-to-damage correlation was used to develop a SAR-based damage assessment method, but significant residual within-class variability makes estimations sometimes unreliable. Among the possible remedies the injection of physical vulnerability data into the model was suggested. The idea here is to do so while keeping all the sources of data in the EO domain, by estimating physical vulnerability from observation of high-resolution optical data on the area of interest. Although preliminary results seem to suggest that no significant improvement can be directly obtained on classification accuracy, there appears to be some link between estimated damage and estimated accuracy on which to build a more refined version of the damage estimator