Articles by Matti Mõttus

• Astola, VTT Technical Research Centre of Finland, Tekniikantie 1, 02150 Espoo, Finland https://orcid.org/0000-0003-4989-9910 E-mail: heikki.astola@gmail.com
• Kangas, Natural Resources Institute Finland (Luke), Bioeconomy and Environment, Yliopistokatu 6, 80100 Joensuu, Finland https://orcid.org/0000-0002-8637-5668 E-mail: annika.kangas@luke.fi
• Minunno, Yucatrote, Rua António Gavina L49, 8600-214 Luz, Lagos, Portugal https://orcid.org/0000-0002-7658-6402 E-mail: francesco.minunno@helsinki.fi
• Mõttus, VTT Technical Research Centre of Finland, Tekniikantie 1, 02150 Espoo, Finland https://orcid.org/0000-0002-2745-1966 E-mail: Matti.Mottus@vtt.fi

Physically-based reflectance models offer a robust and transferable method to assess biophysical characteristics of vegetation in remote sensing. Forests exhibit explicit structure at many scales, from shoots and branches to landscape patches, and hence present a specific challenge to vegetation reflectance modellers. To relate forest reflectance with its structure, the complexity must be parametrised leading to an increase in the number of reflectance model inputs. The parametrisations link reflectance simulations to measurable forest variables, but at the same time rely on abstractions (e.g. a geometric surface forming a tree crown) and physically-based simplifications that are difficult to quantify robustly. As high-quality data on basic forest structure (e.g. tree height and stand density) and optical properties (e.g. leaf and forest floor reflectance) are becoming increasingly available, we used the well-validated forest reflectance and transmittance model FRT to investigate the effect of the values of the “uncertain” input parameters on the accuracy of modelled forest reflectance. With the state-of-the-art structural and spectral forest information, and Sentinel-2 Multispectral Instrument imagery, we identified that the input parameters influencing the most the modelled reflectance, given that the basic forestry variables are set to their true values and leaf mass is determined from reliable allometric models, are the regularity of the tree distribution and the amount of woody elements. When these parameters were set to their new adjusted values, the model performance improved considerably, reaching in the near infrared spectral region (740–950 nm) nearly zero bias, a relative RMSE of 13% and a correlation coefficient of 0.81. In the visible part of the spectrum, the model performance was not as consistent indicating room for improvement.

• Halme, VTT Technical Research Centre of Finland, P.O. Box 1000, FI-02044 VTT Espoo, Finland https://orcid.org/0000-0002-7517-6663 E-mail: eelis.halme@vtt.fi
• Mõttus, VTT Technical Research Centre of Finland, P.O. Box 1000, FI-02044 VTT Espoo, Finland https://orcid.org/0000-0002-2745-1966 E-mail: matti.mottus@vtt.fi

Leaf reflectance and transmittance spectra are essential information in many applications such as developing remote sensing methods, computing shortwave energy balance (albedo) of forest canopies, and monitoring health or stress of trees. Measurement of coniferous needle spectra has usually been carried out with single integrating spheres, which has involved a lot of tedious manual work. A small double integrating sphere would make the measurements considerably faster, because of its ease of operation and small sample sizes required. Here we applied a compact double integrating sphere setup, used previously for measurement of broad leaves, for measurement of coniferous needles. Test measurements with the double integrating sphere showed relative underestimation of needle albedo by 5–39% compared to a well-established single integrating sphere setup. A small part of the bias can be explained by the bias of the single sphere. Yet the observed bias is quite significant if absolute accuracy of measurements is required. For relative measurements, e.g. for monitoring development of needle spectra over time, the double sphere system provides notable improvement. Furthermore, it might be possible to reduce the bias by building an optimized measurement setup that minimizes absorption losses in the sample port. Our study indicates that double spheres, after some technical improvement, may provide a new and fast way to collect extensive spectral libraries of tree species.

• Hovi, Aalto University, School of Engineering, Department of Built Environment, P.O.Box 14100, FI-00760 Aalto, Finland https://orcid.org/0000-0002-4384-5279 E-mail: aarne.hovi@aalto.fi
• Mõttus, VTT Technical Research Centre Finland, P.O. Box 1000, FI-02044 VTT, Finland https://orcid.org/0000-0002-2745-1966 E-mail: matti.mottus@gmail.com
• Juola, Aalto University, School of Engineering, Department of Built Environment, P.O.Box 14100, FI-00760 Aalto, Finland E-mail: jussi.juola@aalto.fi
• Manoocheri, Aalto University, School of Electrical Engineering, Metrology Research Institute, Maarintie 8, FI-02150 Espoo, Finland https://orcid.org/0000-0003-3935-3930 E-mail: farshid.manoocheri@aalto.fi
• Ikonen, VTT Technical Research Centre Finland, P.O. Box 1000, FI-02044 VTT, Finland; Aalto University, School of Electrical Engineering, Metrology Research Institute, Maarintie 8, FI-02150 Espoo, Finland https://orcid.org/0000-0001-6444-5330 E-mail: erkki.ikonen@aalto.fi
• Rautiainen, Aalto University, School of Engineering, Department of Built Environment, P.O.Box 14100, FI-00760 Aalto, Finland; Aalto University, School of Electrical Engineering, Department of Electronics and Nanoengineering, P.O. Box 15500, FI-00760 Aalto, Finland https://orcid.org/0000-0002-6568-3258 E-mail: miina.a.rautiainen@aalto.fi

• Rautiainen, Tartu Observatory, 61602 Tõravere, Estonia, and Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: miina.rautiainen@helsinki.fi
• Mõttus, Tartu Observatory, 61602 Tõravere, Estonia E-mail: mm@nn.ee
• Stenberg, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: ps@nn.fi
• Ervasti, City of Vantaa, Land Use and Environment / Green Area Unit, Kielotie 13, FI-01300 Vantaa, Finland E-mail: se@nn.fi