[Anderson, M.C. 1964. Studies of the woodland light climate: I. The photographic computation of light condition. – Journal of Ecology, 52, 27–41.]Search in Google Scholar
[Arumäe, T., Lang, M. 2018. Estimation of canopy cover in dense mixed-species forests using airborne lidar data. – European Journal of Remote Sensing, 51(1), 132–141.]Search in Google Scholar
[Cescatti A. 2007. Indirect estimates of canopy gap fraction based on the linear conversion of hemispherical photographs: Methodology and comparison with standard thresholding techniques. – Agricultural and Forest Meteorology, 143(1–2), 1–12.]Search in Google Scholar
[Coffin, D. 2014. Decoding raw digital photos in Linux. [WWW Document]. – URL http://www.dechifro.org/dcraw/. [Accessed 11 November 2014].]Search in Google Scholar
[Evans, G.C., Coombe, D.E. 1959. Hemispherical and woodland canopy photography and the light climate. – Journal of Ecology, 47, 103–113.]Search in Google Scholar
[Fernandes, R., Plummer, S., Nightingale, J., Baret, F., Camacho, F., Fang, H., Garrigues, S., Gobron, N., Lang, M., Lacaze, R., LeBlanc, S., Meroni, M., Martinez, B., Nilson, T., Pinty, B., Pisek, J., Sonnentag, O., Verger, A., Welles, J., Weiss, M., Widlowski, J.L. 2014. Global leaf area index product validation good practices. Version 2.0. – Schaepman-Strub, G., Román, M., Nickeson, J. (eds.). Best Practice for Satellite-Derived Land Product Validation (p. 76): Land Product Validation Subgroup (WGCV/CEOS). DOI:10.5067/doc/ceoswgcv/lpv/lai.002.]Search in Google Scholar
[Härkönen, S., Neumann, M., Mues, V., Berninger, F., Bronisz, K., Cardellini, G., Chirici, G., Hasenauer, H., Koehl, M., Lang, M., Merganicova, K., Mohren, F., Moiseyev, A., Moreno, A., Mura, M., Muys, B., Olschofsky, K., Del Perugia, B., Rørstad, P.K., Solberg, B., Thivolle-Cazat, A., Trotsiuk, V., Mäkelä, A. 2019. A climate-sensitive forest model for assessing impacts of forest management in Europe. – Environmental Modelling & Software, 115, 128−143.]Search in Google Scholar
[Kuusk, A. 1995. A fast, invertible canopy reflectance model. – Remote Sensing of Environment, 51, 342–350.]Search in Google Scholar
[Kuusk, A., Lang, M., Kuusk, J. 2013. Database of optical and structural data for the validation of forest radiative transfer models. – Kokhanovsky, A.A. (ed.). Light Scattering Reviews 7: Radiative Transfer and Optical Properties of Atmosphere and Underlying Surface. Berlin-Heidelberg, Springer, 109–148.]Search in Google Scholar
[Kuusk, A., Lang, M., Kuusk, J., Lükk, T., Nilson, T., Mõttus, M., Rautiainen, M., Eenmäe, A. 2008. Database of optical and structural data for the validation of radiative transfer models. – Technical Report, 59 pp. Available online. http://www.aai.ee/bgf/jarvselja_db/jarvselja_db.pdf.]Search in Google Scholar
[Kuusk, A., Pisek, J., Lang, M., Märdla, S. 2018. Estimation of gap fraction and foliage clumping in forest canopies. – Remote Sensing, 10, 1153. DOI:10.3390/rs10071153.10.3390/rs10071153]Search in Google Scholar
[Lallemand, F., Püttsepp, Ü., Lang, M., Luud, A., Courty., P.E., Palancade, C., Selosse, M.A. 2017. Mixotrophy in Pyroleae (Ericaceae) from Estonian boreal forests does not vary with light or tissue age. – Annals of Botany, 120 (3), 361−371. DOI:10.1093/aob/mcx054.10.1093/aob/mcx054559141428575199]Open DOISearch in Google Scholar
[Lang, M., Kodar, A., Arumäe, T. 2013. Restoration of above canopy reference hemispherical image from below canopy measurements for plant area index estimation in forests. – Forestry Studies | Metsanduslikud Uurimused, 59, 13–27.]Search in Google Scholar
[Lang, M., Kuusk, A., Mõttus, M., Rautiainen, M., Nilson, T. 2010. Canopy gap fraction estimation from digital hemispherical images using sky radiance models and a linear conversion method. – Agricultural and Forest Meteorology, 150(1), 20–29.]Search in Google Scholar
[Lang, M., Nilson, T., Kuusk, A., Pisek, J., Korhonen, L., Uri, V. 2017. Digital photography for tracking the phenology of an evergreen conifer stand. – Agricultural and Forest Meteorology, 246, 15–21.]Search in Google Scholar
[Lukasová, V., Lang, M., Škvarenina, J. 2014. Seasonal changes in NDVI in relation to phenological phases, LAI and PAI of beech forests. – Baltic Forestry, 20, 248−262.]Search in Google Scholar
[Nilson, T. 1971. A theoretical analysis of the frequency gaps in plant stands. – Agricultural and Forest Meteorology, 8, 25–28.]Search in Google Scholar
[R Core Team. 2016. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. [WWW Document]. – URL https://www.R-project.org/. [Accessed 23 June 2016].]Search in Google Scholar
[Watson, D.J. 1947. Comparative physiological studies on the growth of field crops: I. Variation in net assimilation rate and leaf area between species and varieties, and within and between years. – Annals of Botany, 11, 41–76.10.1093/oxfordjournals.aob.a083148]Search in Google Scholar
[Welles, J.M., Norman, J.M. 1991. Instrument for indirect measurement of canopy architecture. – Agronomy Journal, 83, 818–825.]Search in Google Scholar
[Widlowski, J.L., Mio, C., Disney, M., Adams, J., Andredakis, I., Atzberger, C., Brennan, J., Busetto, L., Chelle, M., Ceccherini, G., Colombo, R., Côté, J.-F., Eenmäe, A., Essery, R., Gastellu-Etchegorry, J.-P., Gobron, N., Grau, E., Haverd, V., Homolová, L., Huang, H., Hunt, L., Kobayashi, H., Koetz, B., Kuusk, A., Kuusk, J., Lang, M., Lewis, P.E., Lovell, J.L., Malenovský, Z., Meroni, M., Morsdorf, F., Mõttus, M., Ni-Meister, W., Pinty, B., Rautiainen, M., Schlerf, M., Somers, B., Stuckens, J., Verstraete, M.M., Yang, W., Zhao, F., Zenone, T. 2015. The fourth phase of the radiative transfer model intercomparison (RAMI) exercise: Actual canopy scenarios and conformity testing. – Remote Sensing of Environment, 169, 418–437.]Search in Google Scholar
