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Manual versus Digital Classification of UAV Images in Oak Phenological Studies
Corresponding Author(s) : Krzysztof Będkowski
Geomatics and Environmental Engineering,
Vol. 19 No. 5 (2025): Geomatics and Environmental Engineering
Abstract
This research concerns the phenological phenomenon of the autumn discolorations of sessile oak leaves as the trees prepare for winter dormancy. Sessile oak trees were categorized into five classes according to the general colors of their crowns: from green to brown. Low-altitude UAV-acquired images from the visible B, G, and R bands were used, compared, and evaluated against the results of several classification methods: those that were carried out in the field, visually based on orthomosaic observations, and four variants of digital classification.
The analysis showed that those methods that were based on observer assessments were highly subjective. At the same time, there was also the problem of the reference data to which the results of the individual methods could be referred. It was expected that the analyzed phenomenon of tree-crown discoloration would be better visible in aerial photographs than in field observations; However, visual color classifications using orthomosaics can be too subjective (as has been shown). It is recommended to use supervised digital classification with a careful selection of reference (training) objects.
To switch from pixel-classification results to individual tree classifications, a novel approach was adopted in which the class value that was most abundant within the images of each canopy (determined by the supervised classification method selected) could be used. Among the supervised digital-classification methods that were applied, the results that were closest to the classification performed in the field were obtained by using the ML and Fisher algorithms (followed by kNN).
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- Stachak A.: Dwie fenologiczne formy buka w Puszczy Bukowej pod Szczecinem oraz w Szczecinie [Two phenological forms of beech in the Beech Forest near Szczecin and in Szczecin itself]. Sylwan, vol. 112(8), 1968, pp. 59–62.
- Fijałkowski D.: Zmienność dębów szypułkowego (Quercus robur L.) i bezszypułkowego (Quercus sessilis Ehrh.) w lasach Lubelszczyzny [Variation of pedunculate (Quercus robur L.) and durmast (Quercus sessilis Ehrh.) oaks in forests of Lublin province]. Sylwan, vol. 112(12), 1968, pp. 41–47.
- Fijałkowski D.: Badania nad okresami rozwijania się i zrzucania liści u dębu szypułkowego Quercus robur L. [Studies of periods of developing and falling down of leaves in Quercus robur L.]. Annales Universitatis Mariae CurieSkłodowska. Sectio C, Biologia, vol. 23, 1968, pp. 203–212.
- Hernik I.: Fenologiczne formy dębu szypułkowego [Phenological forms of the English oak]. Sylwan, vol. 117(7), 1973, pp. 61–69.
- Dolnicki A., Kraj W.: Leaf morphology and the dynamics of frost-hardiness of shoots in two phenological forms of European beech (Fagus silvativa L.) from southern Poland. Electronic Journal of Polish Agricultural Universities, Forestry, vol. 4(2), 2001, 01. http://www.ejpau.media.pl/volume4/issue2/forestry/art-01.html.
- Chmura D.J.: Fenologia wiosennego rozwoju polskich proweniencji dębu szypułkowego (Quercus robur L.) i bezszypułkowego (Q. petraea [Matt.] Liebl.) [Bud burst phenology of Polish provenances of pedunculate (Quercus robur L.) and sessile (Q. petraea [Matt.] Liebl.) oaks]. Sylwan, vol. 146(4), 2002, pp. 97–103.
- Crawley M.J., Akhteruzzaman M.: Individual variation in the phenology of oak trees and its consequences for herbivorous insects. Functional Ecology, vol. 2(3), 1988, pp. 409–415. https://doi.org/10.2307/2389414.
- Csóka G.: Variation in Quercus robur susceptibility to galling wasps (Hymenoptera: Cynipidae) linked to tree phonology, [in:] Prince P.W., Mattson W.J., Baranchikov Y.N. (eds.), The Ecology and Evolution of Gall-Forming Insects [Microform], General Technical Report NC-174, U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station, St. Paul, pp. 148–152.
- Mopper S., Simberloff D.: Differential herbivory in an oak population: The role of plant phenology and insects performance. Ecology, vol. 76(4), 1995, pp. 1233–1241. https://doi.org/10.2307/1940930.
- Visser M.E., Holleman L.J.M.: Warmer springs disrupt the synchrony of oak and winter moth phenology. Proceedings of the Royal Society B: Biological Sciences, vol. 268(1464), 2001, pp. 289–294. https://doi.org/10.1098/rspb.2000.1363.
- Waddell K.J., Fox C.W., White K.D., Mousseau T.A.: Leaf abscission phenology of a scrub oak: consequences for growth and survivorship of a leaf mining beetle. Oecologia, vol. 127(2), 2001, pp. 251–258. https://doi.org/10.1007/s004420000576.
- Kot I., Rubinowska K., Michałek W.: Changes in chlorophyll fluorescence and pigments composition in oak leaves with galls of two cynipid species (Hymeniptera, Cnipidae). Acta Scientiarum Polonorum Hortorum Cultus, vol. 17(6), 2018, pp. 147–157. https://doi.org/10.24326/asphc.2018.6.15.
- Ekholm A., Tack A.J.M., Bolmgren K., Roslin T.: The forgotten season: the impact of autumn phenology on a specialist insect herbivore community on oak. Ecological Entomology, vol. 44(3), 2019, pp. 425–435. https://doi.org/10.1111/een.12719.
- Morin X., Roy J., Sonié L., Chuine I.: Changes in leaf phenology of three European oak species in response to experimental climate change. New Phytologist, vol. 186(4), 2010, pp. 900–910. https://doi.org/10.1111/j.1469-8137.2010.03252.x.
- Vitasse Y., Delzon S., Dufrêne E., Pontailler J.-Y., Louvet J.-M., Kremer A., Michalet R.: Leaf phenology sensitivity to temperature in European trees: Do withinspecies populations exhibit similar responses? Agricultural and Forest Meteorology, vol. 149(5), 2009, pp. 735–744. https://doi.org/10.1016/j.agrformet.2008.10.019.
- Vitasse Y., François C., Dolpierre N., Dufrêne E., Kremer A., Chuine I., Delzon S.: Assessing the effects of climate change on the phenology of European temperate trees. Agricultural and Forest Meteorology, vol. 151(7), 2011, pp. 969–980. https://doi.org/10.1016/j.agrformet.2011.03.003.
- Fisher J.I., Mustard J.F., Vadeboncoeur M.A.: Green leaf phenology at Landsat resolution: Scaling from the field to the satellite. Remote Sensing of Environment, vol. 100(2), 2006, pp. 265–279. https://doi.org/10.1016/j.rse.2005.10.022.
- Polgar C.A., Primack R.B.: Leaf-out phenology of temperate woody plants: From trees to ecosystems. New Phytologist, vol. 191(4), 2011, pp. 926–941. https://doi.org/10.1111/j.1469-8137.2011.03803.x.
- Lisein J., Michez A., Claessens H., Lejeune P.: Discrimination of deciduous tree species from time series of unmanned aerial system imagery. PLoS ONE, vol. 10(11), 2015, e0141006. https://doi.org/10.1371/journal.pone.0141006.
- Będkowski K., Stereńczak K.: Sessile oak (Quercus petraea (Mattuschka) Liebl.) trees variability according to an analysis of multispectral images taken from UAV – first results. Ecological Questions, vol. 17, 2013, pp. 25–33. https://doi.org/10.12775/ecoq-2013-0013.
- Łoziński A., Będkowski K.: Rozpoznawanie jesiennych faz fenologicznych dębu bezszypułkowego (Quercus petraea Liebl.) na ortomozaikach zdjęć lotniczych uzyskanych z wykorzystaniem drona [Monitoring of sessile oak (Quercus petraea Liebl.) autumn phenology using orthomosaics made on a basis of aerial images acquired with drone]. Teledetekcja Środowiska, t. 55, 2016, pp. 5–14.
- Będkowski K., Szymański P.: Dynamics of autumn discoloration of tree crowns in sessile oak stand based on the time series of low-altitude aerial photographs. Sylwan, vol. 167(10), 2023, pp. 650−665. https://doi.org/10.26202/sylwan.2023027.
- Boyer M., Miller J., Belanger M., Hare E, Wu J.: Senescence and spectral reflectance in leaves of northern pin oak (Quercus palustris Muenchh). Remote Sensing of Environment, vol. 25(1), 1988, pp. 71–87. https://doi.org/10.1016/0034-4257(88)90042-9.
- Olędzki J.R.: Badania zróżnicowania własności optyczno-spektralnych środowiska geograficznego [Studies on differentiation of optical spectral properties of geographic environment]. Teledetekcja Środowiska, t. 23, 1993, pp. 7–35.
- Demarez V., Gastellu-Etchegorry J.P., Mougin E., Marty G., Proisy C., Dufrêne E., Le Dantec V.: Seasonal variation of leaf chlorophyll content of a temperate forest. Inversion of the PROSPECT model. International Journal of Remote Sensing, vol. 20(5), 1999, pp. 879–894. https://doi.org/10.1080/014311699212975.
- Merzlyak M.N., Gitelson A.A., Chivkunova O.B., Rakitin V.Yu.: Non-destructive optical detection of pigment changes during leaf senescence and fruit ripening. Physiologia Plantarum, vol. 106(1), 1999, pp. 135–141. https://doi.org/10.1034/j.1399-3054.1999.106119.x.
- Sims D.A., Gamon J.A.: Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages. Remote Sensing of Environment, vol. 81(2–3), 2002, pp. 337–354. https://doi.org/10.1016/S0034-4257(02)00010-X.
- Estrella N., Menzel A.: Responses of leaf colouring in four deciduous tree species to climate and weather in Germany. Climate Research, vol. 32, 2006, pp. 253–267. https://doi.org/10.3354/cr032253.
- Keskitalo J., Bergquist G., Gardeström P., Jansson S., 2005. A cellular timetable of autumn senescence. Plant Physiology, vol. 139(4), 2005, pp. 1635–1648. https://doi.org/10.1104/pp.105.066845.
- Lim P.O., Kim H.J., Nam H.G.: Leaf senescence. Annual Review of Plant Biology, vol. 58, 2007, pp. 115–136. https://doi.org/10.1146/annurev.arplant.57.032905.105316.
- University of Haifa: Why more autumn leaves are red in America and yellow in Europe: New theory. ScienceDaily, 17 August 2009. https://www.sciencedaily.com/releases/2009/08/090813142150.htm [access: 10.08.2024].
- Plutecki W., Zmarz A., Sanko I.: A truly photogrammetric UAV. GIM International, no. 4, 2013. https://www.gim-international.com/content/article/a-truly-photogrammetric-uav [access: 28.06.2024].
- Clark University. Center for Geospatial Analytics: TerrSet. https://www.clarku.edu/centers/geospatial-analytics/terrset/ [access: 25.02.2025].
- Congalton R.S.: A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, vol. 37(1), 1991, pp. 35–46. https://doi.org/10.1016/0034-4257(91)90048-B.
References
Stachak A.: Dwie fenologiczne formy buka w Puszczy Bukowej pod Szczecinem oraz w Szczecinie [Two phenological forms of beech in the Beech Forest near Szczecin and in Szczecin itself]. Sylwan, vol. 112(8), 1968, pp. 59–62.
Fijałkowski D.: Zmienność dębów szypułkowego (Quercus robur L.) i bezszypułkowego (Quercus sessilis Ehrh.) w lasach Lubelszczyzny [Variation of pedunculate (Quercus robur L.) and durmast (Quercus sessilis Ehrh.) oaks in forests of Lublin province]. Sylwan, vol. 112(12), 1968, pp. 41–47.
Fijałkowski D.: Badania nad okresami rozwijania się i zrzucania liści u dębu szypułkowego Quercus robur L. [Studies of periods of developing and falling down of leaves in Quercus robur L.]. Annales Universitatis Mariae CurieSkłodowska. Sectio C, Biologia, vol. 23, 1968, pp. 203–212.
Hernik I.: Fenologiczne formy dębu szypułkowego [Phenological forms of the English oak]. Sylwan, vol. 117(7), 1973, pp. 61–69.
Dolnicki A., Kraj W.: Leaf morphology and the dynamics of frost-hardiness of shoots in two phenological forms of European beech (Fagus silvativa L.) from southern Poland. Electronic Journal of Polish Agricultural Universities, Forestry, vol. 4(2), 2001, 01. http://www.ejpau.media.pl/volume4/issue2/forestry/art-01.html.
Chmura D.J.: Fenologia wiosennego rozwoju polskich proweniencji dębu szypułkowego (Quercus robur L.) i bezszypułkowego (Q. petraea [Matt.] Liebl.) [Bud burst phenology of Polish provenances of pedunculate (Quercus robur L.) and sessile (Q. petraea [Matt.] Liebl.) oaks]. Sylwan, vol. 146(4), 2002, pp. 97–103.
Crawley M.J., Akhteruzzaman M.: Individual variation in the phenology of oak trees and its consequences for herbivorous insects. Functional Ecology, vol. 2(3), 1988, pp. 409–415. https://doi.org/10.2307/2389414.
Csóka G.: Variation in Quercus robur susceptibility to galling wasps (Hymenoptera: Cynipidae) linked to tree phonology, [in:] Prince P.W., Mattson W.J., Baranchikov Y.N. (eds.), The Ecology and Evolution of Gall-Forming Insects [Microform], General Technical Report NC-174, U.S. Department of Agriculture, Forest Service, North Central Forest Experiment Station, St. Paul, pp. 148–152.
Mopper S., Simberloff D.: Differential herbivory in an oak population: The role of plant phenology and insects performance. Ecology, vol. 76(4), 1995, pp. 1233–1241. https://doi.org/10.2307/1940930.
Visser M.E., Holleman L.J.M.: Warmer springs disrupt the synchrony of oak and winter moth phenology. Proceedings of the Royal Society B: Biological Sciences, vol. 268(1464), 2001, pp. 289–294. https://doi.org/10.1098/rspb.2000.1363.
Waddell K.J., Fox C.W., White K.D., Mousseau T.A.: Leaf abscission phenology of a scrub oak: consequences for growth and survivorship of a leaf mining beetle. Oecologia, vol. 127(2), 2001, pp. 251–258. https://doi.org/10.1007/s004420000576.
Kot I., Rubinowska K., Michałek W.: Changes in chlorophyll fluorescence and pigments composition in oak leaves with galls of two cynipid species (Hymeniptera, Cnipidae). Acta Scientiarum Polonorum Hortorum Cultus, vol. 17(6), 2018, pp. 147–157. https://doi.org/10.24326/asphc.2018.6.15.
Ekholm A., Tack A.J.M., Bolmgren K., Roslin T.: The forgotten season: the impact of autumn phenology on a specialist insect herbivore community on oak. Ecological Entomology, vol. 44(3), 2019, pp. 425–435. https://doi.org/10.1111/een.12719.
Morin X., Roy J., Sonié L., Chuine I.: Changes in leaf phenology of three European oak species in response to experimental climate change. New Phytologist, vol. 186(4), 2010, pp. 900–910. https://doi.org/10.1111/j.1469-8137.2010.03252.x.
Vitasse Y., Delzon S., Dufrêne E., Pontailler J.-Y., Louvet J.-M., Kremer A., Michalet R.: Leaf phenology sensitivity to temperature in European trees: Do withinspecies populations exhibit similar responses? Agricultural and Forest Meteorology, vol. 149(5), 2009, pp. 735–744. https://doi.org/10.1016/j.agrformet.2008.10.019.
Vitasse Y., François C., Dolpierre N., Dufrêne E., Kremer A., Chuine I., Delzon S.: Assessing the effects of climate change on the phenology of European temperate trees. Agricultural and Forest Meteorology, vol. 151(7), 2011, pp. 969–980. https://doi.org/10.1016/j.agrformet.2011.03.003.
Fisher J.I., Mustard J.F., Vadeboncoeur M.A.: Green leaf phenology at Landsat resolution: Scaling from the field to the satellite. Remote Sensing of Environment, vol. 100(2), 2006, pp. 265–279. https://doi.org/10.1016/j.rse.2005.10.022.
Polgar C.A., Primack R.B.: Leaf-out phenology of temperate woody plants: From trees to ecosystems. New Phytologist, vol. 191(4), 2011, pp. 926–941. https://doi.org/10.1111/j.1469-8137.2011.03803.x.
Lisein J., Michez A., Claessens H., Lejeune P.: Discrimination of deciduous tree species from time series of unmanned aerial system imagery. PLoS ONE, vol. 10(11), 2015, e0141006. https://doi.org/10.1371/journal.pone.0141006.
Będkowski K., Stereńczak K.: Sessile oak (Quercus petraea (Mattuschka) Liebl.) trees variability according to an analysis of multispectral images taken from UAV – first results. Ecological Questions, vol. 17, 2013, pp. 25–33. https://doi.org/10.12775/ecoq-2013-0013.
Łoziński A., Będkowski K.: Rozpoznawanie jesiennych faz fenologicznych dębu bezszypułkowego (Quercus petraea Liebl.) na ortomozaikach zdjęć lotniczych uzyskanych z wykorzystaniem drona [Monitoring of sessile oak (Quercus petraea Liebl.) autumn phenology using orthomosaics made on a basis of aerial images acquired with drone]. Teledetekcja Środowiska, t. 55, 2016, pp. 5–14.
Będkowski K., Szymański P.: Dynamics of autumn discoloration of tree crowns in sessile oak stand based on the time series of low-altitude aerial photographs. Sylwan, vol. 167(10), 2023, pp. 650−665. https://doi.org/10.26202/sylwan.2023027.
Boyer M., Miller J., Belanger M., Hare E, Wu J.: Senescence and spectral reflectance in leaves of northern pin oak (Quercus palustris Muenchh). Remote Sensing of Environment, vol. 25(1), 1988, pp. 71–87. https://doi.org/10.1016/0034-4257(88)90042-9.
Olędzki J.R.: Badania zróżnicowania własności optyczno-spektralnych środowiska geograficznego [Studies on differentiation of optical spectral properties of geographic environment]. Teledetekcja Środowiska, t. 23, 1993, pp. 7–35.
Demarez V., Gastellu-Etchegorry J.P., Mougin E., Marty G., Proisy C., Dufrêne E., Le Dantec V.: Seasonal variation of leaf chlorophyll content of a temperate forest. Inversion of the PROSPECT model. International Journal of Remote Sensing, vol. 20(5), 1999, pp. 879–894. https://doi.org/10.1080/014311699212975.
Merzlyak M.N., Gitelson A.A., Chivkunova O.B., Rakitin V.Yu.: Non-destructive optical detection of pigment changes during leaf senescence and fruit ripening. Physiologia Plantarum, vol. 106(1), 1999, pp. 135–141. https://doi.org/10.1034/j.1399-3054.1999.106119.x.
Sims D.A., Gamon J.A.: Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages. Remote Sensing of Environment, vol. 81(2–3), 2002, pp. 337–354. https://doi.org/10.1016/S0034-4257(02)00010-X.
Estrella N., Menzel A.: Responses of leaf colouring in four deciduous tree species to climate and weather in Germany. Climate Research, vol. 32, 2006, pp. 253–267. https://doi.org/10.3354/cr032253.
Keskitalo J., Bergquist G., Gardeström P., Jansson S., 2005. A cellular timetable of autumn senescence. Plant Physiology, vol. 139(4), 2005, pp. 1635–1648. https://doi.org/10.1104/pp.105.066845.
Lim P.O., Kim H.J., Nam H.G.: Leaf senescence. Annual Review of Plant Biology, vol. 58, 2007, pp. 115–136. https://doi.org/10.1146/annurev.arplant.57.032905.105316.
University of Haifa: Why more autumn leaves are red in America and yellow in Europe: New theory. ScienceDaily, 17 August 2009. https://www.sciencedaily.com/releases/2009/08/090813142150.htm [access: 10.08.2024].
Plutecki W., Zmarz A., Sanko I.: A truly photogrammetric UAV. GIM International, no. 4, 2013. https://www.gim-international.com/content/article/a-truly-photogrammetric-uav [access: 28.06.2024].
Clark University. Center for Geospatial Analytics: TerrSet. https://www.clarku.edu/centers/geospatial-analytics/terrset/ [access: 25.02.2025].
Congalton R.S.: A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, vol. 37(1), 1991, pp. 35–46. https://doi.org/10.1016/0034-4257(91)90048-B.