Sessile oak (Quercus petraea (Mattuschka) Liebl.) trees variability according to an analysis of multispectral images taken from UAV – first results

Krzysztof Będkowski, Krzysztof Stereńczak



The paper presents first results of the use of multispectral aerial images to identify the outum phenophases of sessile oak. Observed phenophases are represented with three leaf colors – green, yellow and brown. Color composition of images in three spectral bands: blue, green and red, taken by digital non metric Sigma DP2 cameras, which were carried by Unmanned Aerial Vehicle (UAV) were used. Pictures were taken on 17 October 2011. Two observers made visual crowns classification of 556 oak trees into three groups: green, yellow and brown, on the basis of the dominant color of the leafs. It was found that among observers there is a large compliance in classification (79.7%). Additionally, observations of the spring growth of leafs on 54 trees crowns images recorded from seven positions were evaluated. Although the results may indicate the existence of certain trends, the clear relationship between autumn and spring phases of trees growing can not be noted now (due to small number of sample and short time of observations). The use of UAV to monitor the length of the individual tree growing season has been confirmed. 


phenology, sessile oak, Quercus petraea, UAV

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Bobinac M., Batos B., Miljković D. & Radulović S., 2012, Polycyclism and phenological variability in the common oak (Quercus robur L.), Archives of Biological Sciences, Belgrade, 64 (1): 97–105.

Clark A. F., Woods J. C. & Oechsle O., 2010, A low-cost airborne platform for ecological monitoring. Int. Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVIII, Part 5, Com. V.

Cheak S. F., 2004, Detecting near-UV and near-IR wavelengths with the FOVEON image sensor, Naval Postgraduate School, Monterey, California, USA.

Crawley M. J. & Akhteruzzaman M., 1988, Individual variation in the phenology of oak trees and its consequences for herbivorous insects, Functional Ecology 2 (3): 409–415. DOI 10.2307/2389414

Eisenbeiss, H., Lambers K. & Sauerbier M., 2005, Photogrammetric recording of the archaeological site of Pinchango Alto (Palpa, Peru) using a mini helicopter (UAV), Int. Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIV-5/C34: 238–243.

Greer J. D.; Hoppus M. L. & Lachowski H. M., 1990, Color infrared photography for resource management – unique attributes improve vegetation mapping and resource management, Journal of Forestry 88 (7): 12–17.

Grenzdörffer G. J, Engelb A. & Teichert B., 2008, The photogrammetric potential of low-cost UAV’s in forestry and agriculture, Int. Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVII. Part B1.

Gruen A., 2012. First civilian photogrammetric UAV flight over Singapore. first-civilian-photogrammetric-uav-flight-over-singapore. html (29.04.2012). Idrisi 2009, Idrisi Taiga Manual, Clark Labs, Worcester, USA.

Jankowicz B., 2002a, Zastosowanie niskopułapowych lotów bezzałogowych dla fotogrametrycznego pozyskiwania informacji o terenach wiejskich [The Use of low-altitude flights for photogrammetric acquisition of data regarding arable areas], Archiwum Fotogrametrii Kartografii i Teledetekcji 12a: 145–150.

Jankowicz B., 2002b, Przydatność obrazów rejestrowanych kamerami APS (Advanced Photo System) z nalotów niskopułapowych dla fotogrametrycznego monitoringu obszarów wiejskich [Usability of images taken by APS (Advanced Photo System) cameras for photogrammetric monitoring of arable areas], Archiwum Fotogrametrii Kartografii i Teledetekcji 12a: 151–153.

Jankowicz B., 2007, Analiza zastosowania bezzałogowych fotogrametrycznych nalotów niskopułapowych w kontekście szybkiego pozyskiwania geoinformacji [Analysis of unmanned air low-height photogrammetric flights for quick collection of geoinformation], Archiwum Fotogrametrii Kartografii i Teledetekcji 17a: 329–338.

Jaszczak R., 2000, Charakterystyka wskaźników uszkodzenia koron drzew sosny zwyczajnej (Pinus sylvestris L.) różnych klas biosocjalnych [Description of tree crown damage indices in scots pine (Pinus Sylvestris L.) of different biosocial classes], Sylwan CXLIV No. 9: 65–76.

Jenkins J. P., Braswell B. H., Frokling S. E. & Aber J. D., 2002, Detecting and predicting spatial and interannual patterns of temperate forest springtime phenology in the eastern U.S., Geophysical Research Letters 29. DOI: 10.1029/2001GL014008

Kadomatsu M., 1997, Differences in phenology of Quercus collected from northern China, eastern Hokkaido and western Honshu, Research Bulletin of the Hokkaido University Forests 54 (2): 188–201.

Królikowski J., 2011, Latać każdy może [Everybody can fly], Geodeta 7 (194): 48–51.

Kumar V. 2012, Autonomous agile aerial robots, TED Conference., 3PY&feature=player_embedded (12.05.2012).

Lechowicz M. J., 1984, Why do temperate deciduous trees leaf out at different times? Adaptation and ecology of forest communities, American Naturalist 124 (6): 821– 842.

Miścicki S., 1981, Zależność między przyrostem miąższości a barwą korony sosny na lotniczych zdjęciach spektrostrefowych z rejonu słabych uszkodzeń przemysłowych drzewostanów [Relationship between volume increment and colour of pine crowns on air spectro-zonal photos from the region of weak industrial damege in forests stands], Sylwan 5: 9–19.

Morin X., Roy J., Sonie L. & Chuine I., 2010, Changes in leaf phenology of three European oak species in response to experimental climate change, New Phytologist 186 (4): 900–910. DOI: 10.1111/j.1469-8137.2010.03252.x

Muraoka H. & Koizumi H., 2009, Satellite Ecology (SATECO) – linking ecology, remote sensing and micrometeorology, from plot to regional scale, for the study of ecosystem structure and function, Journal of Plant Research 122: 3–20. DOI 10.1007/s10265-008-0188-2

Oliveira G., Correia O., Martins-Loução M. A. & Catarino F. M., 1994, Phenological and growth patterns of the Mediterranean oak Quercus suber L., Trees 9: 41–46. DOI 10.1007/BF00197868

Richardson A. D., Braswell B. H., Hollinger D. Y. & Jenkins J. P., Ollinger S. V., 2009, Near-surface remote sensing of spatial and temporal variation in canopy phenology, Ecological Applications 19: 1417–1428. DOI 10.1890/08-2022.1

Sass-Klaassen U., Sabajo C. R. & den Ouden J., 2011, Vessel formation in relation to leaf phenology in pedunculate oak and european ash, Dendrochronologia 29: 171–175. DOI 10.1016/j.dendro.2011.01.002

Schwartz M. D., 1998, Green-wave phenology, Nature 394: 839–840.

Seiwa K., 1999, Changes in leaf phenology are dependent on tree height in Acer mono, a deciduous broad-leaved tree, Annals of Botany 83: 355–361.

Stone Ch. & Haywood A., 2006, Assessing canopy health of native eucalypt forests, Ecological Management & Restoration 7: 24–30. DOI: 10.1111/j.1442-8903.2006.00288.x

Taxus, 2010, Taxus SI Sp. z o.o. Samolot do fotografii z powietrza, Dokumentacja techniczna [An airplane for aerial photography. Technical data], Warszawa.

Waddell K. J., Fox C. W., White K. D. & Mousseau T. A., 2001, Leaf abscission phenology of a scrub oak: consequences for growth and survivorship of a leaf mining beetle, Oecologia 127: 251–258. DOI 10.1007/s004420000576

Wesołowski A. & Rowiński P., 2006, Timing of bud burst and tree-leaf development in a multispecies temperate forest, Forest Ecology and Management 237: 387–393. DOI 10.1016/j.foreco.2006.09.061

Zmarz A., 2011, Zastosowanie bezzałogowych statków latających do pozyskania danych obrazowych o lesie [Applying unmanned aerial vehicles for obtaining forests’ image data], Dep. of Forest Management, Geomatics and Economics, Warsaw University of Life Sciences – SGGW, Warsaw (PhD thesis).

Zmarz A., Będkowski K., Miścicki S., Plutecki W., 2012, Ocena stanu zdrowotnego świerka na podstawie analizy zdjęć wielospektralnych wykonanych fotograficznymi aparatami cyfrowymi przenoszonymi przez bezzałogowy statek latający [Assesment of norway spruce health using multispectral images acquired from unmanned aerial vehicle with non-metric cameras], Archiwum Fotogrametrii, Kartografii i Teledetekcji 23: 541–550.

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