Experimental approach for identifying building surface materials based on hyperspectral remote sensing imagery

The management of hazardous building materials poses legal and financial challenges for those in the construction, real estate, and property management fields. Building surface materials have different spectral responses in the electromagnetic energy spectrum. Remote sensors can receive the energy reflection and transmission from such materials. In this study we investigated the spectral characteristics of building materials in wavelengths ranging from 350 nm to 2500 nm. We explored a new method for identifying color steel, clay, glazed tile, and asphalt concrete using hyperspectral remote sensing based on building material spectrum characteristics. We discussed methods for extracting information about the construction materials from hyperspectral remote sensing images. We described a practical applied model, based on spectrum measurements, for the analysis of common building materials, and tested the model using hyperspectral remote sensing data from the EO-1 Hyperion sensor and Chinese airborne hyperspectral data from the pushbroom hyperspectral imager (PHI) spectrometer, covering an urban area. Our results show that building surface materials can be identified from hyperspectral remote sensing images with a reasonable quality, based on the spectral sensitivity of different building materials. For example, concrete and asphalt are more sensitive than other materials. We concluded that the proposed method based on hyperspectral remote sensing images and spectral recognition techniques is an efficient way to extract information about building materials.