Otwarty dostęp

Tracking the long-term structure changes of a mature deciduous broadleaf forest stand using digital hemispherical photography

 oraz    | 21 lis 2019

Zacytuj

Anderson, M.C. 1964. Studies of the woodland light climate: I. The photographic computation of light condition. – Journal of Ecology, 52, 27–41.10.2307/2257780Search 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), 132–141.10.1080/22797254.2017.1411169Search 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), 1–12.10.1016/j.agrformet.2006.04.009Search 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, 103–113.10.2307/2257250Search 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, 128−143.10.1016/j.envsoft.2019.02.009Search in Google Scholar

Kuusk, A. 1995. A fast, invertible canopy reflectance model. – Remote Sensing of Environment, 51, 342–350.10.1016/0034-4257(94)00059-VSearch 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, 109–148.10.1007/978-3-642-21907-8_4Search 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/rs10071153Search 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/mcx054559141428575199Open 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, 13–27.10.2478/fsmu-2013-0008Search 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), 20–29.10.1016/j.agrformet.2009.08.001Search 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, 15–21.10.1016/j.agrformet.2017.05.021Search 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, 25–28.10.1016/0002-1571(71)90092-6Search 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.a083148Search in Google Scholar

Welles, J.M., Norman, J.M. 1991. Instrument for indirect measurement of canopy architecture. – Agronomy Journal, 83, 818–825.10.2134/agronj1991.00021962008300050009xSearch 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, 418–437.10.1016/j.rse.2015.08.016Search in Google Scholar

eISSN:
1736-8723
Język:
Angielski
Częstotliwość wydawania:
2 razy w roku
Dziedziny czasopisma:
Life Sciences, Plant Science, Ecology, other