Wir verwenden Cookies

Wir nutzen Cookies auf unserer Website. Einige von ihnen sind essenziell, während andere uns helfen, diese Website und Ihre Erfahrung zu verbessern.

Essenziell
 
Digital

Wissenschaftliche Publikation

Forest Assessment Using High Resolution SAR Data in X-Band

Publikation aus Digital

Perko R., Raggam H., Deutscher J., Gutjahr K., Schardt M.

Remote Sensing, vol3, 792-815, 2011

Abstract:

Novel radar satellite missions also include sensors operating in X-band at very high resolution. The presented study reports methodologies, algorithms and results on forest assessment utilizing such X-band satellite images, namely from TerraSAR-X and COSMO-SkyMed sensors. The proposed procedures cover advanced stereo-radargrammetric and interferometric data processing, as well as image segmentation and image classification. A core methodology is the multi-image matching concept for digital surface modeling based on geometrically constrained matching. Validation of generated surface models is made through comparison with LiDAR data, resulting in a standard deviation height error of less than 2 meters over forest. Image classification of
 forest regions is then based on X-band backscatter information, a canopy height model and  interferometric coherence information yielding a classification accuracy above 90%. Such information is then directly used to extract forest border lines. High resolution X-band sensors deliver imagery that can be used for automatic forest assessment on a large scale.

Download (9055 kB)