Remote Sensing Roof Damage Detection

Much promising work has been conducted in this area.

Remote sensing roof damage detection.

The emergence of vhr remote sensing imagery with detailed texture and context information makes it possible to detect building damage based on only post event data. Although there have been several researches carried out to improve techniques for building damage detection a reliable damage assessment requires semantic integration of remote sensing data based on structural engineering knowledge. Change detection in heterogeneous remote sensing images is crucial for disaster damage assessment. This study utilized high spatial resolution oblique remote sensing data to assess the condition of garage doors and roof structure damage on residential structures following two tornadoes and one hurricane.

Used a maximum likelihood ml classifier on sar features derived from the european remote sensing mission in combination with eo data provided by the indian remote sensing satellite in order to identify damaged structures. Automatic building damage detection method using high resolution remote sensing images and 3d gis model. One technique for damage detection involves fusion of sar and eo data in pixel based damage detection. State of the art remote sensing technologies provide an opportunity to obtain damage information faster and cheaper.

Recent methods use homogenous transformation which transforms the heterogeneous optical and synthetic aperture radar sar remote sensing images into the same feature space to achieve change detection. Jihui tu a b haigang sui a wenqing feng a zhina songa. Failures of these large openings can lead to internal pressurization which can cause additional structural damage to roofs and walls.