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Visible and near infrared hyperspectral imaging reveals significant differences in needle reflectance among Scots pine provenances


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ASNER, G. P. and R. E. MARTIN (2008): Spectral and chemical analysis of tropical forests: scaling from leaf to canopy levels. Remote Sensing of Environment 112: 3958-3970.10.1016/j.rse.2008.07.003Search in Google Scholar

BAJCSY, P. and P. GROVES (2004): Methodology for hyperspectral band selection. Photogrammetric Engineering and Remote Sensing Journal 7: 793-802.10.14358/PERS.70.7.793Search in Google Scholar

CARTER, G. A. (1993): Responses of leaf spectral reflectance to plant stress. American Journal of Botany 80: 239-43.10.1002/j.1537-2197.1993.tb13796.xSearch in Google Scholar

CARTER, G. A. (1991): Primary and secondary effects of water content on the spectral reflectance of leaves. American Journal of Botany 78: 916-924.10.1002/j.1537-2197.1991.tb14495.xSearch in Google Scholar

CARTER, G. A. and A. K. KNAPP (2001): Leaf optical properties in higher plants: linking spectral characteristics to stress and chlorophyll concentration. American Journal of Botany 88: 677-684.10.2307/2657068Search in Google Scholar

CASTRO-ESAU, K. L., G. A. SANCHEZ-AZOFEIFA and T. CAELLI (2004): Discrimination of lianas and trees with leaflevel hyperspectral data. Remote Sensing of Environment 90: 353-372.10.1016/j.rse.2004.01.013Search in Google Scholar

CURRAN, P. J. (1989): Remote sensing of foliar chemistry. Remote Sensing of Environment 30: 271-278.10.1016/0034-4257(89)90069-2Search in Google Scholar

DANUSEVIC˘IUS, D. and R. GARBRILAVIC˘IUS (2001): Variation in juvenile growth rhythm among Picea abies provenances from the Baltic states and adjacent regions. Scandinavian Journal of Forest Research 16: 305-317.10.1080/02827580152496696Search in Google Scholar

DANUSEVIC˘IUS, D., J. BUCHOVSKA, V. STANYS, J. B. S˘ IKS˘NIANIENE, V. MAROZAS and V. BENDOKAS (2013): DNA marker based identification of spontaneous hybrids between Pinus mugo and P. sylvestris at the Lithuanian sea-side. Nordic Journal of Botany 31: 1-9.Search in Google Scholar

DATT, B. (1998): Remote sensing of chlorophyll a, chlorophyll b, chlorophyll a+b, and total carotenoid content in leaves. Remote Sensing of Environment 66: 111-121.10.1016/S0034-4257(98)00046-7Search in Google Scholar

DE BACKER, S., P. KEMPENEERS, W. DEBRUYN and P. SCHEUNDERS (2005): Band selection for hyperspectral remote sensing. IEEE Geoscience and Remote Sensing Letters 2: 319-323.Search in Google Scholar

DORMLING, I. (1993): Bud dormancy, frost hardiness and frost drought in seedlings of Pinus sylvestris and Picea abies, pp. 285-298. In: Advances in cold hardiness edited by PH. LI, L. CHRISTERSSON, CRC Press.10.1201/9781351069526-20Search in Google Scholar

EICHE, V. (1966): Cold damage and plant mortality in experimental provenance plantations with Scots pine in northern Sweden. Studia Forestalia Suecica 36: 1-218.Search in Google Scholar

EISMANN, M. T. (2012): Hyperspectral Remote Sensing, SPIE Press, Bellingham, USA, 748 p.10.1117/3.899758Search in Google Scholar

EKBERG, I., G. ERIKSSON and I. DORMLING (1979): Photo - periodic reactions in conifer species. Holarctic Ecology 2: 255-263.Search in Google Scholar

EKBERG, I., G. ERIKSSON and Y. WENG (1985): Betweenand within-population variation in growth rhythm and plant height in four Picea abies populations. Studia Forestalia Suecica 167: 1-14.Search in Google Scholar

ERIKSSON, G. (1991): Challenges for forest geneticists. Silva Fennica 52: 257-269.10.14214/sf.a15623Search in Google Scholar

ERIKSSON, G., S. ANDERSSON, V. EICHE, J. IFVER and A. PERSSON (1980): Severity index and transfer effects on survival and volume production of Pinus sylvestris in northern Sweden. Studia Forestalia Suecica 156: 1-32.Search in Google Scholar

ERIKSSON, G., I. EKBERG, I. DORMLING and B. MATÉRN (1978): Inheritance of bud-set and bud-flushing in Picea abies (L.) Karst. Theoretical and Applied Genetics 52: 3-19.10.1007/BF00273761Search in Google Scholar

GARBRILAVIC˘IUS, R. and D. DANUSEVIC˘IUS (2003): Genetics and breeding of Norway spruce in Lithuania. Monograph. Lithuanian Forest Research Institute, Petrovo Ofsetas, Vilnius, 359 p. (in Lithuanian with English summary and figure, table headings).Search in Google Scholar

GITELSON, A. A., Y. GRITZ and M. N. MERZLYAK (2003): Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. Journal of Plant Physiology 160: 271-282.10.1078/0176-1617-00887Search in Google Scholar

GUYOT, G. (1989): Signatures spectrales des surfaces naturelles. Collection Teledetection Satellitaire No. 5, Paradigme, 178 p.Search in Google Scholar

HANNERZ, M. (1998): Genetic and seasonal variation in hardiness and growth rhythm in boreal and temperate conifers- a review and annotated bibliography. The Forest Research Institute of Sweden, Report 2, 140 p.Search in Google Scholar

HÄNNINEN, H. P. and PELKONEN (1989): Dormancy release in Pinus sylvestris L. and Picea abies (L.) Karst. seedlings: effects of intermittent warm periods during chilling. Trees 3: 179-184.10.1007/BF00226654Search in Google Scholar

HESKETH, M. and G. A. SÁNCHEZ-AZOFEIFA (2012): The effect of seasonal spectral variation on species classification in the Panamanian tropical forest. Remote Sensing of Environment 118: 73-82.10.1016/j.rse.2011.11.005Search in Google Scholar

HODKINSON, T. (2013): Assignment testing reveals multiple introduced source populations including potential ash hybrids (Fraxinus excelsior×F. angustifolia) in Ireland. European Journal of Forest Research 132: 195-209.10.1007/s10342-012-0667-9Search in Google Scholar

HOFFER, R. M. (1978): Biological and physical considerations in applying computer-aided analysis techniques to remote sensor data, pp. 55-96. In: Remote Sensing: the Quantitative Approach, edited by P. H. SWAIN, S. M. DAVIS, McGraw-Hill, New York.Search in Google Scholar

IM, J. and J. R. JENSEN (2008): Hyperspectral remote sensing of vegetation. Geography Compass 2: 1943-1961.10.1111/j.1749-8198.2008.00182.xSearch in Google Scholar

KALACSKA, M., S. BOHLMAN, G. A. SANCHEZ-AZOFEIFA, K. CASTRO-ESAU and T. CAELLI (2007): Hyperspectral discrimination of tropical dry forest lianas and trees: Comparative data reduction approaches at the leaf and canopy levels. Remote Sensing of Environment 109: 406-415.10.1016/j.rse.2007.01.012Search in Google Scholar

KOKALY, R. F. and R. N. CLARK (1999): Spectroscopic Determination of Leaf Biochemistry Using Band-Depth Analysis of Absorption Features and Stepwise Multiple Linear Regression. Remote Sensing of Environment 67: 267-287.10.1016/S0034-4257(98)00084-4Search in Google Scholar

KOONSANIT, K., C. JARUSKULCHAI and A. EIUMNOH (2012): Band selection for dimension reduction in hyper - spectral image using integrated information gain and principal components analysis technique. International Journal of Machine Learning and Computing 3: 248-251.10.7763/IJMLC.2012.V2.124Search in Google Scholar

KOHAVI, R. (1995): A study of cross-validation and bootstrap for accuracy estimation and model selection. IJCAI 14: 1137-1145.Search in Google Scholar

KREMER, A. (2006): Diversity: the driving force of sustainability and evolution. Annals of Forest Science 8: 809-811.10.1051/forest:2006081Search in Google Scholar

Kupková, L., M. POZU°C˘KOVÁ, K. ZACHOVÁ, Z. LHOTÁKOVÁ, V. KOPAC˘KOVÁ and J. ALBRECHTOVÁ (2012): Chloro - phyll determination in Silver Birch and Scots Pine foliage from heavy metal polluted regions using spectral reflectance data. EARSeL eProceedings 11: 64-73.Search in Google Scholar

LEBLON, B. (1997): Soil and vegetation optical properties. Faculty of Forestry and Environmental Management University of New Brunswick, Fredericton (NB), Canada.Search in Google Scholar

LEINONEN, I. (1996): Dependence of dormancy release on temperature in different origins of Pinus sylvestris and Betula pendula seedlings. Scandinavian Journal of Forest Research 23: 1043-1051.10.1080/02827589609382919Search in Google Scholar

LILLESAND, T. M., R. W. KIEFER and J. W. CHIPMAN (2008): Remote Sensing and Image Interpretation, 6th edition, Wiley, New York, USA, 756 p.Search in Google Scholar

LINDER, S. (1972): Seasonal variation of pigments in needles: a Study of Scots pine and Norway spruce seedlings grown under different nursery seasonal conditions. Studia Forestalia Suecia 100: 1-30.Search in Google Scholar

LUTHER, J. E. and A. L. CARROLL (1999): Development of an Index of Balsam Fir Vigor by Foliar Spectral Reflectance. Remote Sensing of Environment 69: 241-252.10.1016/S0034-4257(99)00016-4Search in Google Scholar

MANEVSKI, K., I. MANAKOS, G. P. PETROPOULOS and CH. KALAITZIDIS (2011): Discrimination of common Mediterranean plant species using field spectroradiometry. International Journal of Applied Earth Observation and Geoinformation 13: 922-933.10.1016/j.jag.2011.07.001Search in Google Scholar

MARTIN, M. E. and J. D. ABER (1997): High spectral resolution remote sensing of forest canopy lignin, nitrogen, and ecosystem processes. Ecological Applications 7: 431-443.10.1890/1051-0761(1997)007[0431:HSRRSO]2.0.CO;2Search in Google Scholar

MASAITIS, G. (2013): The potential of hyperspectral imaging to detect forest tree species and evaluate their condition. PhD thesis, Aleksandras Stulginskis University, Akademija, Lithuania, 150 p. (in Lithuanian with English summary).Search in Google Scholar

MASAITIS, G., G. MOZGERIS and A. AUGUSTAITIS (2013): Spectral reflectance properties of healthy and stressed coniferous trees. iForest 6: 30-36.10.3832/ifor0709-006Search in Google Scholar

MASAITIS, G. and G. MOZGERIS (2012): Some peculiarities of laboratory measured hyperspectral reflectance characteristics of Scots pine and Norway spruce needles. In: Proceedings of the 18th annual international conference Research for Rural Development 2012, Vol. 2, Latvian University of Agriculture, Jelgava, 2012, p. 25-32.Search in Google Scholar

MCLACHLAN, G. (2004): Discriminant analysis and statistical pattern recognition. Wiley, New York, USA, 2004, 551 p.Search in Google Scholar

MIIDLA, H. (1989): Biochemistry of lignin formation. In The Formation of Lignin in Wheat Plants and Its Connection with Mineral Nutrition. Acta Comm. Univ. Tartu 845: 11-23.Search in Google Scholar

MOORTHY, I., J. MILLER and T. L. NOLAND (2008): Estimating chlorophyll concentration in conifer needles with hyperspectral data: An assessment at the needle and canopy level. Remote Sensing of Environment 112: 2824-2838.10.1016/j.rse.2008.01.013Search in Google Scholar

OSBORNE, A. G., T. FEARN and P. HINDLE (1993): Practical NIR spectroscopy with applications in food and beverage analysis. 2nd Edn. Longman Scientific and Technical, Harlow, 240 p.Search in Google Scholar

PERRY, T. O. (1971): Dormancy of trees in winter. Science 8: 29-36.10.1126/science.171.3966.29Search in Google Scholar

PERSSON, A. and B. PERSSON (1992): Survival, growth and quality of Norway spruce (Picea abies (L.) Karst.) provenances at the three Swedish sites of the IUFRO 1964/68 provenance experiment. Department of Forest Yield Research, Swedish University of Agricultural Sciences, Report 29, 67 p.Search in Google Scholar

PRAVDIN, L. F. (1964): Scots pine variation. Intraspecific Taxonomy and Selection, Moskva, 208 p. (in Russian).Search in Google Scholar

PULKKINEN, P. (1993): Frost hardiness development and lignification of young Norway spruce seedlings of southern and northern Finnish origin. Silva Fennica 27: 47-54.10.14214/sf.a15658Search in Google Scholar

ROCK, B. N., J. E. VOGELMANN, D. L. WILLIAMS, A. F. VOGELMANN and T. HOSHIZAKI (1986): Remote detection of forest damage. BioScience 36: 439-445.10.2307/1310339Search in Google Scholar

ROCK, B. N., D. L. WILLIAMS, D. M. MOSS, G. N. LAUTEN and M. KIM (1994): High spectral resolution field and laboratory optical reflectance measurements of red spruce and eastern hemlock needles and branches. Remote Sensing of Environment 47: 176-189.10.1016/0034-4257(94)90154-6Search in Google Scholar

SAVITZKY, A. and M. J. E. GOLAY (1964): Smoothing and Differentiation of Data by Simplified Least Squares Procedures. Analytical Chemistry 36: 1627-1639.10.1021/ac60214a047Search in Google Scholar

SAVOLAINEN, O., F. BOKMA, T. KNÜRR, K. KÄRKKÄINEN, T. PYHÄJÄRVI and W. WACHOWIAK (2007): Adaptation of forest trees to changing climate, pp. 19-28. In: Climate change and forest genetic diversity: Implications for sustainable forest management in Europe, edited by J. KOSKELA, A. BUCK, . TEISSIER DU CROS, Bioversity International, Rome, Italy, ISBN 978-92- 9043-749-9.Search in Google Scholar

SHUTYAEV, A. M. and M. GIERTYCH (1998): Height growth variation in a comprehensive Eurasian provenance experiment of (Pinus sylvestris L.). Silvae Genetica 46: 332-349.Search in Google Scholar

SKRØPPA, T. (1982): Genetic variation in growth rhythm characteristics within and between natural populations of Norway spruce. A preliminary report. Silva Fennica 16: 160-167.Search in Google Scholar

SUNDBLAD, L.-G., M. ANDERSSON, P. GELADI, A. SALO - MANSON and M. SJOSTROM (2001): Fast, nondestructive measurement of frost hardiness in conifer seedlings by VIS+NIR spectroscopy. Tree Physiology 21: 751-757.10.1093/treephys/21.11.75111470661Search in Google Scholar

THOMASSET, M., J. F. FERNÁNDEZ-MANJARRÉS, G. C. DOUGLAS, P. BERTOLINO, N. FRASCARIALACOSTE and T. R. HODKINSON (2013): Assignment testing reveals multiple introduced source populations including potential ash hybrids (Fraxinus excelsior × F. angustifolia) in Ireland. European Journal of Forest Research 132: 195-209.10.1007/s10342-012-0667-9Search in Google Scholar

TREITZ, P. M. and P. J. HOWARTH (1999): Hyperspectral remote sensing for estimating biophysical parameters of forest ecosystems. Progress in Physical Geography 23: 359-390.10.1177/030913339902300303Search in Google Scholar

Vaiphasa, CH., S. ONGSOMWANG, T. VAIPHASA and A. K. SKIDMORE (2005): Tropical mangrove species discrimination using hyperspectral data: A laboratory study. Estuarine, Coastal and Shelf Science 65: 371-379.10.1016/j.ecss.2005.06.014Search in Google Scholar

WANG, Q. and P. LI (2012): Hyperspectral indices for estimating leaf biochemical properties in temperate deciduous forests: Comparison of simulated and measured reflectance data sets. Ecological Indicators 14: 56-65.10.1016/j.ecolind.2011.08.021Search in Google Scholar

ZARCO-TEJADA, P. J., J. R. MILLER, J. HARRON, B. HU, T. L. NOLAND, N. GOEL, G. H. MOHAMMED and P. SAMPSON (2004): Needle chlorophyll content estimation through model inversion using hyperspectral data from boreal conifer forest canopies. Remote Sensing of Environment 89: 189-199.10.1016/j.rse.2002.06.002Search in Google Scholar

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