Spectral characteristics of moist birch leaves and synthetic materials: experimental studies and evaluation of models

Abstract

The optical depth of biomaterials and natural backgrounds varies with their environment and incoming light properties. Deciduous trees, for instance, have canopy thicknesses that vary significantly from one place to another. Leaves constituting canopies absorb most of the light in the visible region, while transmitting a large ratio of the incoming near-infrared light. Such variations in the spectral properties of biomaterials pose complicated challenges for developing camouflage material and precise land area mapping by remote sensors. We aim to address these challenges by investigating multi-layered birch leaves, a biomaterial abundant throughout Northern Europe. We measured and compared the reflectance, transmission, and absorptance of moist birch leaves between 250 and 2500 nm and compared their values with the spectral properties of three different synthetic materials. We found that the spectral properties of the synthetic materials matched those of the birch leaf at certain wavelengths and material thicknesses. The results highlight the importance of choosing appropriate material thickness when designing camouflage and having knowledge of the thickness variation of the biomaterial constituting the background. Furthermore, the results are of relevance for wavelength-dependent detections based on spectral anomalies of artificial objects when recorded through vegetation layers. Moreover, we tested the spectral data of the materials against an earlier published extinction model. With few exceptions, the model fit the spectral data well and could be used to estimate the spectral properties of the materials as a function of their thickness. We also compared the accuracy of the extinction model with two other models and discussed their value and practicality. Our findings will be valuable for the development of camouflage materials as well as advanced multi-layered fabric technology and remote sensing applications.