Background

The project explores and implements multi-scale and multi-sensor SAR change detection methodologies for event landslide mapping. Automated analysis for change detection is a challenging task due 
to the inherent noisiness of SAR imagery and also to the high sensitivity to texture variability due to different acquisition angles. Moreover, pre-processing (de-speckling) may lead to the degradation
 of the geometrical details and affect the accuracy of the
 final change map. For this reason and also for operative issue, identify and defining a SAR change detection 
feature which is robust to noise and look angle variation
 is an open issue, especially on new high-resolution 
images. Particular attention is devoted to the use of the
X-band SAR data in order to understand the potential and limitation of the TerraSAR-X sensor for this scope. Methodologies to derive soil moisture from SAR images under specific conditions (bare or sparsely vegetated
fields) will be also eventually addressed.

Timely and accurate change detection
 of Earths surface features provides the foundation for 
better understanding relationships and interactions 
between human and natural phenomena to better manage and use resources. In general, change detection mappings involves the application of multi-temporal datasets to quantitatively analyze the temporal effects of the phenomenon. The use of high and very-high resolution images and the exploitation of innovative change detection techniques are important support for many application domains, such disaster mapping and risk mitigation.

All classification methods exploiting optical images and remote sensing techniques are on average 
successful when landslides leave distinct radiometric signatures on the terrain, like in forested terrains, in
 tropical and equatorial areas and in arid or sub arid environments where the vegetation cover is sparse. Clouds and haze make problematic the acquisition of satellite optical images
 during or just after the event resulting in a critical
 lack of information. SAR images promise to facilitate the measure of change detection land cover when the persistency of clouds limits the use of optical images

Scopo

The expected results of the activity are: the analysis and the assessment of TerraSAR-X X-band SAR data for the detection and mapping of landslide under different conditions, the analysis of the potential and limitations of X band SAR for the mapping and monitoring of natural processes in synergy with other RS data and auxiliary information.

Metodi

Qualitative and quantitative assessment of RS data acquired from different sensors and at different scales. Particular attention is devoted to the use of the X-band SAR data in order to understand potentials and limitations. Investigation and development of advanced, robust and customized change detection techniques and algorithms for addressing the rapid mapping of event landslides. The comparison of the products derived at different scales and from different sensors, with the aim to derive useful guidelines for
their integration in the perspective of an integrated monitoring framework.