Articles containing the keyword 'forest canopy'

Leaf area index (LAI) is a critical parameter that influences many biophysical processes within forest ecosystems. Collecting in situ LAI measurements by forest canopy hemispherical photography is however costly and laborious. As a result, there is a lack of LAI data for calibration of forest ecosystem models. Citizen science has previously been tested as a solution to obtain LAI measurements from large areas, but simply asking citizen scientists to collect forest canopy images does not stimulate enough interest. As a response, this study investigates how gamified citizen science projects could be implemented with a less laborious data collection scheme. Citizen scientists usually have only mobile phones available for LAI image collection instead of cameras suitable for taking hemispherical canopy images. Our simulation results suggest that twenty directional canopy images per plot can provide LAI estimates that have an accuracy comparable to conventional hemispherical photography with twelve images per plot. To achieve this result, the mobile phone images must be taken at the 57° hinge angle, with four images taken at 90° azimuth intervals at five spread-out locations. However, more images may be needed in forests with large LAI or uneven canopy structure to avoid large errors. Based on these findings, we propose a gamified solution that could guide citizen scientists to collect canopy images according to the proposed scheme.

• Zhang, School of Forest Sciences, University of Eastern Finland, Yliopistokatu 7, FI-80101 Joensuu, Finland https://orcid.org/0000-0001-7876-9635 E-mail: shaohui.zhang@uef.fi
• Korhonen, School of Forest Sciences, University of Eastern Finland, Yliopistokatu 7, FI-80101 Joensuu, Finland https://orcid.org/0000-0002-9352-0114 E-mail: lauri.korhonen@uef.fi
• Nummenmaa, Tampere University, Kalevantie 4, FI-33100 Tampere, Finland https://orcid.org/0000-0002-9896-0338 E-mail: timo.nummenmaa@tuni.fi
• Bianchi, Natural Resources Institute Finland (Luke), Latokartanonkaari 9, FI-00790 Helsinki, Finland https://orcid.org/0000-0001-9544-7400 E-mail: simone.bianchi@luke.fi
• Maltamo, School of Forest Sciences, University of Eastern Finland, Yliopistokatu 7, FI-80101 Joensuu, Finland https://orcid.org/0000-0002-9904-3371 E-mail: matti.maltamo@uef.fi

• Korhonen, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: lauri.korhonen@joensuu.fi
• Korhonen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: ktk@nn.fi
• Stenberg, Univ. of Helsinki, Dept of Forest Resource Management, P.O. BOX 27, FI-00014 University of Helsinki, Finland E-mail: ps@nn.fi
• Maltamo, University of Joensuu, Faculty of Forest Sciences, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: mm@nn.fi
• Rautiainen, Univ. of Helsinki, Dept of Forest Resource Management, P.O. BOX 27, FI-00014 University of Helsinki, Finland E-mail: mr@nn.fi

• Korhonen, University of Joensuu, P.O. Box 68, FI-68101 Joensuu, Finland E-mail: lauri.korhonen@joensuu.fi
• Korhonen, University of Joensuu, P.O. Box 68, FI-68101 Joensuu, Finland E-mail: ktk@nn.fi
• Rautiainen, University of Joensuu, P.O. Box 68, FI-68101 Joensuu, Finland E-mail: mr@nn.fi
• Stenberg, University of Joensuu, P.O. Box 68, FI-68101 Joensuu, Finland E-mail: ps@nn.fi

Fast and accurate estimates of canopy cover are central for a wide range of forestry studies. As direct measurements are impractical, indirect optical methods have often been used in forestry to estimate canopy cover. In this paper the accuracy of canopy cover estimates from two widely used canopy photographic methods, hemispherical photography (DHP) and cover photography (DCP) was evaluated. Canopy cover was approximated in DHP as the complement of gap fraction data at narrow viewing zenith angle range (0°–15°), which was comparable with that of DCP. The methodology was tested using artificial images with known canopy cover; this allowed exploring the influence of actual canopy cover and mean gap size on canopy cover estimation from photography. DCP provided robust estimates of canopy cover, whose accuracy was not influenced by variation in actual canopy cover and mean gap size, based on comparison with artificial images; by contrast, the accuracy of cover estimates from DHP was influenced by both actual canopy cover and mean gap size, because of the lower ability of DHP to detect small gaps within crown. The results were replicated in both DHP and DCP images collected in real forest canopies. Finally, the influence of canopy cover on foliage clumping index and leaf area index was evaluated using a theoretical gap fraction model. The main findings indicate that DCP can overcome the limits of indirect techniques for obtaining unbiased and precise estimates of canopy cover, which are comparable to those obtainable from direct, more labour-intensive techniques, being therefore highly suitable for routine monitoring and inventory purposes.

• Chianucci, Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria – Forestry Research Centre, viale Santa Margherita 80, 52100 Arezzo, Italy http://orcid.org/0000-0002-5688-2060 E-mail: fchianucci@gmail.com