Forest Assessment Using High Resolution SAR Data in X-Band

Remote Sensing

Roland Perko¹  Hannes Raggam²  Janik Deutscher²  Karlheinz Gutjahr² 

[1] Remote Sensing and Geoinformation, Institute for Information and Communication Technologies, Joanneum Research, Steyrergasse 17, 8010 Graz, Austria;

关键词: SAR;    high resolution;    X-band;    forestry;    mapping;    radargrammetry;    classification;    DSM/DTM;   

DOI  :  10.3390/rs3040792

来源: mdpi

【 摘 要 】

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.

【 授权许可】

CC BY   
© 2011 by the authors; licensee MDPI, Basel, Switzerland.