Articles containing the keyword 'canopy'

Differences in vegetation cover estimation by field biologists of the 8th National Forest Inventory in Finland were tested. Eleven observers estimated the canopy coverages of six forests taxa in 25 sample plots, located in one stand. The experiment was arranged after the field work. The coverage of Vaccinium vitis-idaea and the ground layer appeared to be the most difficult to estimate. The mean of the highest estimator was about double that of the lowest one. The least abundant species and the sample plots with the smallest coverages had the largest estimation errors. The most important compositional gradient of the data was natural, even though the test was made in a homogenous area. However, the effect of the observer could be recognized. The differences between observers could be caused by the differences both in visual estimation level and in placing the sampling frame. The results suggest that tests should always be made when several observers are used in vegetation surveys. If calibration is used, it should be made separately for each species.

The PDF includes an abstract in Finnish.

• Tonteri, E-mail: tt@mm.unknown

The utilization of direct radiation was studied in five model stands of Poisson-type tree distribution and cone-shaped crowns. The radiation extinction depended on the self-shading of the crown and the shading caused by other trees. The results indicate that at low sun elevation a stand populated by very narrow-crowned trees is most effective in light interception and photosynthesis. At high sun elevation a broad-crowned canopy is best illuminated and most favourable for photosynthesis. A stand with a two-storey canopy is effective in all latitudes when the crowns are moderately narrow. In two-storey canopies the foliage of the lower storey can be better illuminated than in the lower parts of the upper storey, because of the smaller self-shading in the small crowns of the lower storey. A canopy where the crown volume is concentrated on few big crowns is less effective than a canopy consisting of many small crowns.

The PDF includes an abstract in Finnish.

• Pukkala, E-mail: tp@mm.unknown
• Kuuluvainen, E-mail: tk@mm.unknown

Especially in forest vegetation studies, the light climate below the canopy is of great interest. In extensive forest inventories, direct measurement of the light conditions is too time-consuming. Often only the standard tree stand parameters are available. The present study was undertaken with the aim to develop methods for estimation of the light climate on the basis of readily measurable tree stand characteristics. The study material includes 40 sample plots representing different kinds of more or less mature forest stands of Scots pine (Pinus sylvestris L.) and Norway spruce (Picea abies (L.) H. Karst.).

In each forest stand, a set of hemipherical photographs was taken and standard tree stand measurements were performed. A regression approach was applied in order to elaborate linear models for predicting the canopy coverage. The total basal area of the stand explained 63% of variance in the canopy coverage computed from hemipherical photographs. A coefficient representing the relative proportion of Norway spruce in the stand increased the explanatory power into 75%. When either the stand density (stems/unit area) or dominant age of the stand was included into the model, increment of the explanatory power into 80% was achieved. By incorporating both of the preceding predictors, an explanatory power of 85% was reached.

The PDF includes a summary in Finnish.

• Kuusipalo, E-mail: jk@mm.unknown

The effect of growth rate on wood basic density in even-age Norway spruce (Picea abies (L.) H. Karst.) plantations was studied on the basis of samples collected from 53 stands; 30 trees were sampled in each stand. The prediction of basic density with the help of growth rate and some other tree characteristics could be improved if the social status of the tree was taken into account. Within a stand, the smaller trees had a lower density, while taller trees had a higher density than they should have had on the basis of growth rate alone.

The PDF includes a summary in Finnish.

• Kärkkäinen, E-mail: mk@mm.unknown

The needle area distribution and crown structure of a young planted Scots pine (Pinus sylvestris L.) stand are described. The crown structure and crown shape showed apparent regularity in crown structure regardless of stand dynamics. Similarly, the shoot structure and individual needle area showed regularity in the number of needles per branch and shoot length unit, and consequent phytoarea density inside the needle cylinder. Also, the shoot area and needle area distributions were found to show a regular distribution of needle biomass throughout the crown, also inside the crown, in the dominant trees. In the suppressed trees the needle biomass was located in the upper crown and on the surface area of the crown. Estimates of the canopy needle area and distributions are given. The results were applied in calculations of the within-stand light regime. The results correlated well with the empirical results.

The PDF includes a summary in Finnish.

• Kellomäki, E-mail: sk@mm.unknown
• Oker-Blom, E-mail: po@mm.unknown

The proportions of needle and wood in current-year shoots in crown systems of young Scots pine (Pinus sylvestris L.) trees was studied. The proportion of needles out of the total shoot biomass increased according to the increasing number of the whorl counted from the apex. In the lower part of the crown system the needle biomass of newly-formed shoots was 50–60 fold compared to that of wood and bark biomass. In the upper part of the crown system the same ratio was 1–2. The variation in ratio between needle and wood biomass was whorl-specific and independent of tree class. The magnitude of the ratio was not related to the position of the tree in the stand nor to the prevailing light conditions within the state.

The PDF includes a summary in Finnish.

• Mäkelä, E-mail: am@mm.unknown
• Hari, E-mail: ph@mm.unknown
• Kellomäki, E-mail: sk@mm.unknown

The concept of tree class as indicated by dominant, codominant, intermediate and suppressed trees is analysed using empirical material representing 13 younger Scots pine (Pinus sylvestris L.) stands. The relative needle biomass, i.e. the needle biomass related to the maximum needle biomass in the stand, was closely related to the relative height of the tree and independent of the stand characteristics. Furthermore, the relative illumination of the crown system was related to the relative height of the trees as well as the relative photosynthetic capacity and tree-to-tree variation in growth. When calculated per needle biomass unit it appeared that height growth, radial growth, needle growth and other growth parameters were the highest in the suppressed trees. The suppressed trees thus appear to be more efficient in utilizing available resources than other tree classes. The ecologic significance of the results is discussed.

The PDF includes a summary in Finnish.

• Kellomäki, E-mail: sk@mm.unknown
• Hari, E-mail: ph@mm.unknown

Light intensity inside the canopy varies considerably both in space and time. A new apparatus was developed which is disturbed as little as possible by the above-mentioned variation. The construction is based on the linear relationships between light intensity (measured using silicon diodes) and photosynthesis. This procedure permits linear operations (summing and integration) to be carried out on the output of the diodes without any loss of accuracy. There are five diodes in each assimilation chamber. A model, in which the independent variables include ligth, measured with the present equipment, and temperature, fits the photosynthetic rates well even inside the canopy.

The PDF includes a summary in Finnish.

• Hari, E-mail: ph@mm.unknown
• Huhtamaa, E-mail: mh@mm.unknown
• Pelkonen, E-mail: pp@mm.unknown
• Pohjonen, E-mail: vp@mm.unknown
• Salminen, E-mail: rs@mm.unknown

The study is based on observations in a Scots pine (Pinus sylvestris L.) stand on a dry upland forest site in Karhumäki, where a 10-15-year old seedling stand grew under a hold-overs of larger trees that had been left in the site in a previous felling. The root systems of 80-120 cm tall seedlings growing around single mother trees were unearthed. Root maps were drawn of the root systems of 120 seedlings.

No seedlings grew around old, large hold-overs. It seems that seedlings could not compete with their root system. If the hold-overs were stunted in their growth, seedlings grew also under the canopy of the mother tree. 90% of the seedlings had a tap root. Rest of the roots grew horisontally in the topsoil. Around a vigorous mother tree, the seedlings grew their roots away from the mother tree. Hold-overs that had belonged originally to the lower canopy layer of the old forest did not have similar effect on the root orientation of the seedlings. Their roots had been previously affected by trees of higher canopy layer, later removed in the felling.

The PDF includes a summary in German.

• Kalela, E-mail: ek@mm.unknown

Crown class is useful tool both in forest management and forest mensuration. The study presents a detailed crown classification for Scots pine (Pinus sylvestris L.). It was used to classify the sample trees prior detailed measurements of the crown and stem form. The stem form of a tree was dependent on which canopy layer it belonged. This relation was detected on both Vaccinium and Calluna site type forests. In addition, the stem tapers faster in poorer forest site types compared to better sites. The shorter the self-pruned part of the stem is, the faster the stem tapers. According to the study, the stems of stunted trees taper faster than trees of other crown classes. Also the age group affects stem form.

The PDF includes a summary in German.

• Lakari, E-mail: ol@mm.unknown

• 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

Forest stands, crucial for inventory, planning, and management, traditionally rely on time-consuming visual analysis by forest managers. To enhance efficiency, there is a growing need for automated methods that take into account essential forest attributes. In response, we propose a novel approach utilizing airborne Light Detection and Ranging (LiDAR) and hyperspectral data for automated forest stand delineation. Our approach initiates with over-segmentation of the Canopy Height Model (CHM), followed by attribute calculation for each segment using both CHM and hyperspectral data. Two rules are applied to merge homogeneous segments and eliminate others based on calculated attributes. The effectiveness of our method was validated using three types of reference forest stands with two indices: the explained variance (R²) and Intersection over Union (IoU). Results from our study demonstrated notable accuracy, with a R² of 97.35% and 97.86% for mean tree height and mean diameter at breast height (DBH), respectively. The R² for mean canopy height is 81.80%, outperforming manual delineation by 7.31% and multi-scale segmentation results by 2.13%. Furthermore, our approach achieved high IoU values, which indicates a strong spatial agreement with manually delineated forest stands and leading to fewer manual adjustments when applied directly to forest management. In conclusion, our forest stand delineation method enhances both internal consistency and spatial accuracy. This method contributes to improving practical performance and forest management efficiency.

• Xiong, Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China; Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration, Beijing 100091, China; School of Geospatial Engineering and Science, Sun Yat-sen University, Zhuhai 519082, China https://orcid.org/0000-0003-4432-2485 E-mail: xiongh29@mail2.sysu.edu.cn
• Pang, Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China; Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration, Beijing 100091, China https://orcid.org/0000-0002-9760-6580 E-mail: pangy@ifrit.ac.cn
• Jia, Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China; Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration, Beijing 100091, China E-mail: jiawen@ifrit.ac.cn
• Bai, Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China; Key Laboratory of Forestry Remote Sensing and Information System, National Forestry and Grassland Administration, Beijing 100091, China E-mail: baiyu9224@163.com

Remote sensing using unmanned aerial vehicle (UAV) -borne sensors is currently a highly interesting approach for the estimation of forest characteristics. 3D remote sensing data from airborne laser scanning or digital stereo photogrammetry enable highly accurate estimation of forest variables related to the volume of growing stock and dimension of the trees, whereas recognition of tree species dominance and proportion of different tree species has been a major complication in remote sensing-based estimation of stand variables. In this study the use of UAV-borne hyperspectral imagery was examined in combination with a high-resolution photogrammetric canopy height model in estimating forest variables of 298 sample plots. Data were captured from eleven separate test sites under weather conditions varying from sunny to cloudy and partially cloudy. Both calibrated hyperspectral reflectance images and uncalibrated imagery were tested in combination with a canopy height model based on RGB camera imagery using the k-nearest neighbour estimation method. The results indicate that this data combination allows accurate estimation of stand volume, mean height and diameter: the best relative RMSE values for those variables were 22.7%, 7.4% and 14.7%, respectively. In estimating volume and dimension-related variables, the use of a calibrated image mosaic did not bring significant improvement in the results. In estimating the volumes of individual tree species, the use of calibrated hyperspectral imagery generally brought marked improvement in the estimation accuracy; the best relative RMSE values for the volumes for pine, spruce, larch and broadleaved trees were 34.5%, 57.2%, 45.7% and 42.0%, respectively.

• Tuominen, Natural Resources Institute Finland (Luke), Economics and society, P.O. Box 2, FI-00791 Helsinki, Finland http://orcid.org/0000-0001-5429-3433 E-mail: sakari.tuominen@luke.fi
• Balazs, Natural Resources Institute Finland (Luke), Economics and society, P.O. Box 2, FI-00791 Helsinki, Finland E-mail: andras.balazs@luke.fi
• Honkavaara, Finnish Geospatial Research Institute, National Land Survey of Finland, Geodeetinrinne 2, FI-02430 Masala, Finland E-mail: eija.honkavaara@nls.fi
• Pölönen, University of Jyväskylä, Faculty of Information Technology, P.O. Box 35, FI-40014 Jyväskylä, Finland E-mail: ilkka.polonen@jyu.fi
• Saari, VTT Microelectronics, P.O. Box 1000, FI-02044 VTT, Finland E-mail: heikki.saari@vtt.fi
• Hakala, Finnish Geospatial Research Institute, National Land Survey of Finland, Geodeetinrinne 2, FI-02430 Masala, Finland E-mail: teemu.hakala@nls.fi
• Viljanen, Finnish Geospatial Research Institute, National Land Survey of Finland, Geodeetinrinne 2, FI-02430 Masala, Finland E-mail: niko.viljanen@nls.fi

Canopy gap is the driving force of forest succession. Due to the uncontrollability, however, the influences of natural disturbances on gap formation and gap distribution pattern have been rarely understood in temperate secondary forest ecosystems. We monitored the gap formation and gap distribution pattern using high-resolution remote sensing images before and after two disturbances (wind/snowstorm in 2003 and flood in 2013). The results showed that after wind/snowstorm, the gap nearest neighbor index (GNNI) decreased, the vacant land area did not obviously change while the gap fraction and gaps density (especially medium size) increased. After the flood, GNNI decreased, the number of small gaps increased but larger gaps were in many cases extended to vacant land areas leading to a smaller total number of medium and large gaps but considerable increase in vacant land area. We also found that the gap densities increased with slope and altitude for wind/snowstorm-formed gaps, but they increased with increasing slope and decreasing altitude for flood-formed gaps. These results indicated that gaps were aggregated in steep slope and high altitude areas after wind/snowstorm, but in steep slope and low altitude areas after the flood. Medium gaps were mainly created by the wind/snowstorm due to the individual-level death of dominant tree with the continuous fall of surrounding trees. While, vacant lands were obviously created during the flood because of integral sweeping. Besides, smaller trees were easily damaged by runoff of flood, which induced small gaps. In summary, forest managers may pay more attention to use gaps to accelerate forest succession after wind/snowstorms and to restore vegetation in vacant lands after floods.

• Zhu, E-mail: Chunyuzhu123@126.com
• Zhu, E-mail: jiaojunzhu@iae.ac.cn
• Zheng, E-mail: xiaozheng@iae.ac.cn
• Lu, E-mail: delianglu14@hotmail.com
• Li, E-mail: delianglu14@hotmail.com

In this paper we examine the feasibility of data from unmanned aerial vehicle (UAV)-borne aerial imagery in stand-level forest inventory. As airborne sensor platforms, UAVs offer advantages cost and flexibility over traditional manned aircraft in forest remote sensing applications in small areas, but they lack range and endurance in larger areas. On the other hand, advances in the processing of digital stereo photography make it possible to produce three-dimensional (3D) forest canopy data on the basis of images acquired using simple lightweight digital camera sensors. In this study, an aerial image orthomosaic and 3D photogrammetric canopy height data were derived from the images acquired by a UAV-borne camera sensor. Laser-based digital terrain model was applied for estimating ground elevation. Features extracted from orthoimages and 3D canopy height data were used to estimate forest variables of sample plots. K-nearest neighbor method was used in the estimation, and a genetic algorithm was applied for selecting an appropriate set of features for the estimation task. Among the selected features, 3D canopy features were given the greatest weight in the estimation supplemented by textural image features. Spectral aerial photograph features were given very low weight in the selected feature set. The accuracy of the forest estimates based on a combination of photogrammetric 3D data and orthoimagery from UAV-borne aerial imaging was at a similar level to those based on airborne laser scanning data and aerial imagery acquired using purpose-built aerial camera from the same study area.

• Tuominen, Natural Resources Institute Finland (Luke), Economics and society, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: sakari.tuominen@luke.fi
• Balazs, Natural Resources Institute Finland (Luke), Economics and society, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: andras.balazs@luke.fi
• Saari, VTT Technical Research Centre of Finland Ltd, P.O. Box 1000, FI-02044 VTT, Finland E-mail: Heikki.Saari@vtt.fi
• Pölönen, University of Jyväskylä, Department of Mathematical Information Technology, P.O. Box 35, FI-40014 University of Jyväskylä, Finland E-mail: ilkka.polonen@jyu.fi
• Sarkeala, Mosaicmill Oy, Kultarikontie 1, FI-01300 Vantaa, Finland E-mail: janne.sarkeala@mosaicmill.com
• Viitala, Häme University of Applied Sciences (HAMK), P.O. Box 230, FI-13101 Hämeenlinna, Finland E-mail: Risto.Viitala@hamk.fi

Gap formation and its effects on regeneration have been reported as being important in forest development, but seldom studies concentrated on the gap closure process by lateral extension growth of canopy trees surrounding gaps. We monitored the closure process of 12 artificial gaps for 7 years with three size classes: small (from 68 m² to 125 m²), middle (from 174 m² to 321 m²), and large (from 514 m² to 621 m²); and investigated the regeneration twice in a temperate secondary forest, Northeast China. The closure process can be described through quadratic functions, which showed the closure rates slowed down with gap ages. Large gaps had a higher closure rate (39 m² a^–1) than middle gaps (25 m² a^–1) and small gaps (11 m² a^–1). According to the quadratic equations, the lateral growth could last 11, 13 and 16 years for small, middle and large gaps with a remaining size of 12, 69 and 223 m², respectively. As expected, regeneration exhibited the highest seedling density and volume in large gaps. There was no significant difference in regeneration density between middle gaps, small gaps and forest understory in the final investigation; but the volume of regenerated woody species increased significantly from small gaps to large gaps compared with forest understory. These results may provide references on the choice of appropriate gap sizes to promote the regeneration in temperate secondary forests.

• Lu, State Key Laboratory of Forest and Soil Ecology, Qingyuan Forest CERN, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China;  University of Chinese Academy of Sciences, Beijing 100049, China E-mail: delianglu14@hotmail.com
• Zhu, State Key Laboratory of Forest and Soil Ecology, Qingyuan Forest CERN, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China E-mail: jiaojunzhu@iae.ac.cn
• Sun, State Key Laboratory of Forest and Soil Ecology, Qingyuan Forest CERN, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China E-mail: yirongsun@iae.ac.cn
• Hu,  Chinese Research Academy of Environmental Sciences, Beijing 100012, China E-mail: lilehu@gmail.com
• Zhang, State Key Laboratory of Forest and Soil Ecology, Qingyuan Forest CERN, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China;  University of Chinese Academy of Sciences, Beijing 100049, China E-mail: zgq04713@163.com

• Ferrarese, College of Forestry and Conservation, The University of Montana, Missoula, MT, USA; (present) Center for the Environmental Management of Military Lands, 1490 Campus Delivery, Colorado State University, Fort Collins, CO 80523, USA E-mail: jena.ferrarese@colostate.edu
• Affleck, College of Forestry and Conservation, University of Montana, Missoula, MT, USA E-mail: david.affleck@cfc.umt.edu
• Seielstad, College of Forestry and Conservation, University of Montana, Missoula, MT, USA E-mail: carl.seielstad@firecenter.umt.edu

• Hökkä, Finnish Forest Research Institute, Rovaniemi Unit, Eteläranta 55, FI-96300 Rovaniemi, Finland E-mail: hannu.hokka@metla.fi
• Mäkelä, Lapland University of Applied Sciences, Jokiväylä 11 C, FI-96300 Rovaniemi, Finland E-mail: hanna.makela@edu.ramk.fi

• Hökkä, Finnish Forest Research Institute, Rovaniemi Unit, P.O. Box 16, FI-96301 Rovaniemi, Finland E-mail: hannu.hokka@metla.fi
• Repola, Finnish Forest Research Institute, Rovaniemi Unit, P.O. Box 16, FI-96301 Rovaniemi, Finland E-mail: jaakko.repola@metla.fi
• Moilanen, Finnish Forest Research Institute, Oulu Unit, P.O. Box 413, FI-90014 University of Oulu, Finland E-mail: mikko.moilanen@metla.fi
• Saarinen, Finnish Forest Research Institute, Parkano Unit, Kaironiementie 15, FI-39700 Parkano, Finland E-mail: markku.saarinen@metla.fi

• Meen, Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, P.O. Box 5003, NO-1432 Ås, Norway E-mail: eivind.meen@umb.no
• Nielsen, Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, P.O. Box 5003, NO-1432 Ås, Norway E-mail: an@nn.no
• Ohlson, Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, P.O. Box 5003, NO-1432 Ås, Norway E-mail: mo@nn.no

• Bottero, University of Turin, Department Agroselviter, Via Leonardo da Vinci 44, 10095 Grugliasco (TO), Italy E-mail: alessandra.bottero@unito.it
• Garbarino, University of Turin, Department Agroselviter, Via Leonardo da Vinci 44, 10095 Grugliasco (TO), Italy E-mail: mg@nn.it
• Dukic, University of Banja Luka, Faculty of Forestry, Banja Luka, Bosnia and Herzegovina E-mail: vd@nn.ba
• Govedar, University of Banja Luka, Faculty of Forestry, Banja Luka, Bosnia and Herzegovina E-mail: zg@nn.ba
• Lingua, University of Padua, Department of TeSAF, Legnaro (PD), Italy E-mail: el@nn.it
• Nagel, University of Ljubljana, Department of Forestry and Renewable Forest Resources, Ljubljana, Slovenia E-mail: tan@nn.si
• Motta, University of Turin, Department Agroselviter, Via Leonardo da Vinci 44, 10095 Grugliasco (TO), Italy E-mail: rm@nn.it

• Hökkä, Finnish Forest Research Institute, Rovaniemi Research Unit, FI-96301 Rovaniemi, Finland E-mail: hannu.hokka@metla.fi
• Repola, Finnish Forest Research Institute, Rovaniemi Research Unit, FI-96301 Rovaniemi, Finland E-mail: jr@nn.fi
• Moilanen, Finnish Forest Research Institute, Muhos Research Unit, Muhos, Finland E-mail: mm@nn.fi
• Saarinen, Finnish Forest Research Institute, Parkano Research Unit, Parkano, Finland E-mail: ms@nn.fi

• Korpela, University of Helsinki, Department of Forest Sciences, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: ilkka.korpela@helsinki.fi
• Ørka, Norwegian University of Life Sciences, Department of Ecology and Natural Resource Management, P.O.Box 5003, NO-1432 Ås, Norway E-mail: hoo@nn.no
• Maltamo, University of Eastern Finland, School of Forest Science, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: mm@nn.fi
• Tokola, University of Eastern Finland, School of Forest Science, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: tt@nn.fi
• Hyyppä, Finnish Geodetic Institute, Department of Photogrammetry and Remote Sensing, P.O.Box 15, FI-02431 Masala, Finland E-mail: jh@nn.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

• Zhang, College of Environmental Science and Engineering, Hunan University, Hunan Province, Changsha 410082, P.R. China; Hunan Environmental Protection Bureau, Hunan Province, Changsha, 410076, P.R. China E-mail: gz@nn.cn
• Zeng, College of Environmental Science and Engineering, Hunan University, Hunan Province, Changsha 410082, P.R. China E-mail: zgming@hnu.cn
• Jiang, College of Environmental Science and Engineering, Hunan University, Hunan Province, Changsha 410082, P.R. China; Hunan Environmental Protection Bureau, Hunan Province, Changsha, 410076, P.R. China E-mail: ymj@nn.cn
• Du, College of Environmental Science and Engineering, Hunan University, Hunan Province, Changsha 410082, P.R. China E-mail: cyd@nn.cn
• Huang, College of Environmental Science and Engineering, Hunan University, Hunan Province, Changsha 410082, P.R. China E-mail: ghh@nn.cn
• Yao, Xiangya Hospital, Central-south University, Hunan Province, Changsha 410008, P.R. China E-mail: jmy@nn.cn
• Zeng, College of Environmental Science and Engineering, Hunan University, Hunan Province, Changsha 410082, P.R. China E-mail: mz@nn.cn
• Zhang, College of Environmental Science and Engineering, Hunan University, Hunan Province, Changsha 410082, P.R. China E-mail: xlz@nn.cn
• Tan, College of Environmental Science and Engineering, Hunan University, Hunan Province, Changsha 410082, P.R. China E-mail: wt@nn.cn

• Korpela, Department of Forest Resource Management, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: ilkka.korpela@helsinki.fi

• Hotanen, Finnish Forest Research Institute, Joensuu Research Unit, P.O. Box 68, FI-80101 Joensuu, Finland E-mail: juha-pekka.hotanen@metla.fi
• Maltamo, University of Joensuu, Faculty of Forestry, P.O. Box 111, FI-80101 Joensuu, Finland E-mail: mm@nn.fi
• Reinikainen, Finnish Forest Research Institute, Vantaa Research Unit, P.O. Box 18, FI-01301 Vantaa, Finland E-mail: ar@nn.fi

• Légaré, Université du Québec en Abitibi-Témiscamingue, Groupe de recherche en écologie forestière interuniversitaire, 445, boulevard de l'Université, Rouyn-Noranda, QC, Canada J9X 5E4 E-mail: sonia.legare@uqat.uquebec.ca
• Bergeron, NSERC-UQAT-UQAM, Industrial Chair in sustainable forest management, CP 8888, succ. Centre-Ville, Montréal, QC, Canada H3C 3P8 E-mail: yb@nn.ca
• Paré, Natural Resources Canada, Canadian Forest Service, Laurentian Forestry Centre, P.O. Box 3800, Sainte-Foy, QC, Canada G1V 4C7 E-mail: dp@nn.ca

• Burton, Symbios Research and Restoration, P.O. Box 3398, 3868 13th Avenue, Smithers, British Columbia, Canada V0J 2N0 E-mail: symbios@bulkley.net

• Harper, Université de Québec à Montréal, Groupe de recherche en écologie forestière interuniversitaire, CP 8888, succ. A, Montréal, QC, Canada H3C 3P8 E-mail: c1444@er.uqam.ca
• Bergeron, NSERC-UQAT-UQAM, Industrial Chair in sustainable forest management, CP 8888, succ. Centre-Ville, Montréal, QC, Canada H3C 3P8 E-mail: yb@nn.ca
• Gauthier, Canadian Forest Service, Laurentian Forestry Centre, P.O. Box 3800, Sainte-Foy, QC, Canada G1V 4C7 E-mail: sg@nn.ca
• Drapeau, Université de Québec à Montréal, Groupe de recherche en écologie forestière interuniversitaire, CP 8888, succ. A, Montréal, QC, Canada H3C 3P8 E-mail: pd@nn.ca

• Mussche, Laboratory of Forestry, Ghent University, Geraardsbergse Steenweg 267, B-9090 Melle, Belgium E-mail: sm@nn.be
• Samson, Laboratory of Plant Ecology, Ghent University, Coupure Links 653, B-9000 Gent, Belgium E-mail: rs@nn.be
• Nachtergale, Laboratory of Forestry, Ghent University, Geraardsbergse Steenweg 267, B-9090 Melle, Belgium E-mail: ln@nn.be
• De Schrijver, Laboratory of Forestry, Ghent University, Geraardsbergse Steenweg 267, B-9090 Melle, Belgium E-mail: An.Deschrijver@rug.ac.be
• Lemeur, Laboratory of Plant Ecology, Ghent University, Coupure Links 653, B-9000 Gent, Belgium E-mail: rl@nn.be
• Lust, Laboratory of Forestry, Ghent University, Geraardsbergse Steenweg 267, B-9090 Melle, Belgium E-mail: nl@nn.be

European beech (Fagus sylvatica L.) forests have a long history of coppicing, but the majority of formerly managed coppices are currently under conversion to high forest. The long time required to achieve conversion requires a long-term perspective to fully understand the implication of the applied conversion practices. In this study, we showed results from a long-term (1992–2014) case-study comparing two management options (natural evolution and periodic thinning) in a beech coppice in conversion to high forest. Leaf area index, litter production, radiation transmittance and growth efficiency taken as relevant stand descriptors, were estimated using both direct and indirect optical methods. Overall, results indicated that beech coppice showed positive and prompt responses to active conversion practices based on periodic medium-heavy thinning. A growth efficiency index showed that tree growth increased as the cutting intensity increased. Results from the case study supported the effectiveness of active conversion management from an economic (timber harvesting) and ecological (higher growth efficiency) point of view.

• 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
• Salvati, Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria – Research Centre for the Soil-Plant System, via della Navicella 2–4, 00184 Roma, Italy E-mail: bayes00@yahoo.it
• Giannini, Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria – Forestry Research Centre, viale Santa Margherita 80, 52100 Arezzo, Italy E-mail: tessa.giannini@entecra.it
• Chiavetta, Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria – Forestry Research Centre, viale Santa Margherita 80, 52100 Arezzo, Italy E-mail: ugo.chiavetta@entecra.it
• Corona, Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria – Forestry Research Centre, viale Santa Margherita 80, 52100 Arezzo, Italy E-mail: piermaria.corona@unitus.it
• Cutini, Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria – Forestry Research Centre, viale Santa Margherita 80, 52100 Arezzo, Italy E-mail: andrea.cutini@entecra.it

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

• Riihelä, Finnish Meteorological Institute, P.O. Box 503, FI-00200 Helsinki, Finland E-mail: aku.riihela@fmi.fi
• Manninen, Finnish Meteorological Institute, P.O. Box 503, FI-00200 Helsinki, Finland E-mail: tm@nn.fi

• Rautiainen, Department of Forest Ecology, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: miina.rautiainen@helsinki.fi
• Stenberg, Department of Forest Ecology, P.O. Box 27, FI-00014 University of Helsinki, Finland E-mail: ps@nn.fi
• Nilson, Tartu Observatory, EE-61602 Tõravere, Tartumaa, Estonia E-mail: tn@nn.ee