circumference; photogrammetry; Agisoft PhotoScan; point clouds; stem disk; Benin
Abstract :
[en] There is an increase in the use of photogrammetric point clouds for tree attribute mensuration. Stem diameter and circumference can be estimated from point clouds using stem disks of varying thicknesses along the bole. However, there is a dearth of information on the effect of the thickness of point cloud-based stem disks on the accuracy of diameter and circumference estimations. In this study, we outlined a GIS-based procedure for analysing Structure from Motion-derived photogrammetric point clouds with a view to providing an optimal disk thickness for accurate circumference estimates. Geo-referenced point clouds were created from photographs of 30 trees belonging to five savanna species. For each tree, 20 horizontal stem disks, with increasing thicknesses of 1 to 20 mm were made at breast height using the open source QGIS software. The resulting cross-sections were manually delineated and digitised. The difference between reference (manually measured) and point cloud-based circumferences at breast height was expressed as mean absolute percent error (MAPE) and compared across tree species, size and disk thickness. We found significant effects of species identity, tree size and disk thickness on MAPE. A stem disk of 7 mm in thickness provided consistently lower MAPE values ( < 6%). This suggests that the accuracy of tree stem circumference estimations from photogrammetric point clouds depends on stem disk thickness.
Disciplines :
Agriculture & agronomy Life sciences: Multidisciplinary, general & others
Author, co-author :
Akpo, H. A.
Atindogbé, G.
Obiakara, M. C.
Gbedolo, M. A.
Laly, F. G.
Lejeune, Philippe ; Université de Liège - ULiège > Département GxABT > Gestion des ressources forestières et des milieux naturels
Fonton, N.
Language :
English
Title :
Accuracy of tree stem circumference estimation using close range photogrammetry: Does point-based stem disk thickness matter?
Bauwens, S., Fayolle, A., Gourlet-Fleury, S., Ndjele, L.M., Mengal, C., Lejeune, P., Terrestrial photogrammetry: a non-destructive method for modelling irregularly shaped tropical tree trunks. Methods Ecol. Evol. 8:4 (2017), 460–471, 10.1111/2041-210X.12670.
Bemis, S.P., Micklethwaite, S., Turner, D., James, M.R., Akciz, S., Thiele, S.T., Bangash, H.A., Ground-based and UAV-based photogrammetry: a multi-scale, high-resolution mapping tool for structural geology and paleoseismology. J. Struct. Geol. 69 (2014), 163–178, 10.1016/j.jsg.2014.10.007.
Burkhart, H.E., Tomé, M., Modeling Forest Trees and Stands. 2012, Springer, Netherlands, 10.1007/978-90-481-3170-9.
Fang, Rong, Strimbu, Bogdan, Stem measurements and taper modeling using photogrammetric point clouds. Remote Sens., 9(7), 2017, 716, 10.3390/rs9070716.
Forsman, M., Börlin, N., Holmgren, J., Estimation of tree stem attributes using terrestrial photogrammetry with a camera rig. Forests, 7(12), 2016, 61, 10.3390/f7030061.
Huang, H., Zhang, H., Chen, C., Tang, L., Three-dimensional digitization of the arid land plant Haloxylon ammodendron using a consumer-grade camera. Ecol. Evol. 8:11 (2018), 5891–5899, 10.1002/ece3.4126.
Iglhaut, J., Cabo, C., Puliti, S., Piermattei, L., O'Connor, J., Rosette, J., Structure from motion photogrammetry in forestry: a review. Curr. For. Rep. 5:3 (2019), 155–168, 10.1007/s40725-019-00094-3.
Koreň, M., Mokroš, M., Bucha, T., Accuracy of tree diameter estimation from terrestrial laser scanning by circle-fitting methods. Int. J. Appl. Earth Observ. Geoinf. 63 (2017), 122–128, 10.1016/j.jag.2017.07.015.
Liang, X., Jaakkola, A., Wang, Y., Hyyppä, J., Honkavaara, E., Liu, J., Kaartinen, H., The use of a hand-held camera for individual tree 3d mapping in forest sample plots. Remote Sens. 6:7 (2014), 6587–6603, 10.3390/rs6076587.
Mikita, T., Janata, P., Surový, P., Forest stand inventory based on combined aerial and terrestrial close-range photogrammetry. Forests, 7(12), 2016, 165, 10.3390/f7080165.
Miller, J., Morgenroth, J., Gomez, C., 3D modelling of individual trees using a handheld camera: accuracy of height, diameter and volume estimates. Urban For. Urban Green. 14:4 (2015), 932–940, 10.1016/j.ufug.2015.09.001.
Mokroš, M., Liang, X., Surový, P., Valent, P., Čerňava, J., Chudý, F., Tunák, D., Saloň, Š., Merganič, J., Evaluation of close-range photogrammetry image collection methods for estimating tree diameters. ISPRS Int. J. Geoinf., 7(3), 2018, 93, 10.3390/ijgi7030093.
Mokroš, M., Výbošťok, J., Tomaštík, J., Grznárová, A., Valent, P., Slavík, M., Merganič, J., High precision individual tree diameter and perimeter estimation from close-range photogrammetry. Forests, 9(11), 2018, 696, 10.3390/f9110696.
Morgenroth, J., Gomez, C., Assessment of tree structure using a 3D image analysis technique—a proof of concept. Urban For. Urban Green. 13:1 (2014), 198–203, 10.1016/j.ufug.2013.10.005.
Piermattei, L., Karel, W., Wang, D., Wieser, M., Mokroš, M., Surový, P., Koreň, M., Tomaštík, J., Pfeifer, N., Hollaus, M., Terrestrial structure from motion photogrammetry for deriving forest inventory data. Remote Sens., 11(8), 2019, 950, 10.3390/rs11080950.
Surový, P., Yoshimoto, A., Panagiotidis, D., Accuracy of Reconstruction of the Tree Stem Surface Using Terrestrial Close-Range Photogrammetry. Remote Sens., 8(2), 2016, 123, 10.3390/rs8020123.
Szeliski, R., Computer Vision: Algorithms and Applications. 1st ed., 2010, Springer-Verlag, London, 10.1007/978-1-84882-935-0.
West, P.W., Tree and Forest Measurement. 3rd ed., 2015, Springer International Publishing, 10.1007/978-3-319-14708-6.
Zakari, S., Tente, B.A.S., Yabi, I., Toko, I.I., Evolution Hydroclimatique, Perceptions Et Adaptation Des Agroéleveurs Dans L'extrême Nord Du Bénin (Afrique de L'ouest). 2015, 399–405.