Integration of intensity textures and local geometry descriptors from Terrestrial Laser Scanning to map chert in outcrops
The potential of Terrestrial Laser Scanner imaging (TLS) as a tool to map chert, an amorphous variety of silica diffused in sedimentary rocks, is here discussed together with an original method for its automatic detection. Reflectance measurements in the VIS-NIR band (4002500nm) show that chert displays low reflectance in the IR wavelengths that are operated by several commercial TLS. To develop and test a recognition method an outcrop of limestone with chert nodules was scanned with an IR (1541nm) TLS. The intensity information, after proper distance correction, was coupled with geometric and intensity descriptors for training Support Vector Machines (SVM) to separate vegetation from rock and limestone from chert. Results, cross inspected in the field and with reference pictures, demonstrate that TLS data can be efficiently exploited to map chert when the monochromatic information of the intensity is integrated with feature descriptors and SVM classifiers.
texture laser scanning tls classification geology data mining infrared point cloud