عنوان مقاله [English]
Estimation of allometric tree attributes such as heights that are not directly observed on unmanned aerial vehicle (UAV) imagery is challenging. Therefore, this study aimed to introduce a method to estimate the height of wild pistachio (Pistacia atlantica Desf.) single trees in the Zagros region. Therefore, a 45-ha area in Baneh Research Forest of Fars province was captured by a Phantom IV UAV. An algorithm was then suggested to consider the difference between pixels of ground and crown top as tree height on the digital surface model (DSM) following automatic single tree detection. The heights of 100 trees were estimated on DSMs with spatial resolutions of 3.47, 10, 20, 40, 60, 80, and 100 cm. The results showed that the highest coefficient of determination of 0.89 and the lowest relative root mean square error of 11.8% were returned for heights estimated on DSM with 3.47 cm spatial resolution. Moreover, no significant difference was observed among measured and estimated height values on spatial resolutions of 3.47, 10, and 20 cm, respectively. The tree heights were overestimated on DSM with a spatial resolution of 3.47 cm (bias score 1.15), while they were close to the measured values on 10 cm spatial resolution (bias score 1.01) and were underestimated in other spatial resolutions. In general, the results showed the feasibility to estimate heights of wild pistachio trees on Phantom IV imagery, in particular on UAV imagery with a 10 cm spatial resolution.
- Amini, J. and Sadeghi, Y., 2013. Optical and radar images in modeling the forest biomass in north of Iran. Remote Sensing and GIS, 4(4): 69-82 (In Persian).
- Bennet, N.D., Croke, B.F.W, Guariso, G., Guillaume, J.H.A., Hamilton, S.H., Jakeman, A.J., Marsili-Libelli, S., Newham, L.T.H., Norton, J.P., Perrin, C., Pierce, S.A., Robson, B., Seppelt, R., Voinov, A.A., Fath, B.D. and Andreassian, V., 2013. Characterizing performance of environmental models. Environmental Modelling and Software, 40: 1-20.
- Birdal, A.C., Avdan, U. and Türk, T., 2017. Estimating tree heights with images from an unmanned aerial vehicle. Geomatics, Natural Hazards and Risk, 8(2): 1144-1156.
- Borra-Serrano, I., Peña, J.M., Torres-Sánchez, J., Mesas-Carrascosa, F.J. and López-Granados, F., 2015. Spatial quality evaluation of resampled unmanned aerial vehicle-imagery for weed mapping. Sensors, 15(8): 19689-19708.
- Chenari, A., Erfanifard, S.Y., Dehghani, M. and Pourghasemi, H.R., 2017. Estimation of crown area of wild pistachio single trees using DSM of UAV aerial images in Baneh Research Forest, Fars province. Journal of Wood and Forest Science and Technology, 24(4): 117-130 (In Persian).
- Deo, R.K., Domke, G.M., Russell, M.B., Woodall, C.W. and Andersen, H.E., 2018. Evaluating the influence of spatial resolution of Landsat predictors on the accuracy of biomass models for large-area estimation across the eastern USA. Environmental Research Letters, 13(5): 055004.
- Duncanson, L. and Dubayah, R., 2018. Monitoring individual tree-based change with airborne lidar. Ecology and Evolution, 8(10): 5079-5089.
- Feduck, C., McDermidet, G.J. and Castilla, G., 2018. Detection of coniferous seedlings in UAV imagery. Forests, 9(7): 432.
- Fisher, J.R.B., Acosta, E.A., Dennedy-Frank, P.J., Kroeger, T. and Boucher, T.M., 2018. Impact of satellite imagery spatial resolution on land use classification accuracy and modeled water quality. Remote Sensing in Ecology and Conservation, 4(2): 137-149.
- Franklin, S.E., 2001. Remote Sensing for Sustainable Forest Management. CRC Press, Boca Raton, Florida, 424p.
- Goodbody, T.R.H., Coops, N.C., Marshall, P.L., Tompalski, P. and Crawford, P., 2017. Unmanned aerial systems for precision forest inventory purposes: A review and case study. The Forestry Chronicle, 93(1): 71-81.
- Gulbe, L. and Mednieks, I., 2013. Automatic identification of individual tree crowns in mixed forests using fusion of LIDAR and multispectral data. Technologies of Computer Control, 14(1): 93-99.
- Hansen, M.C., Potapov, P.V., Goetz, S.J., Turubanova, S., Tyukavina, A., Krylov, A., Kommareddy, A. and Egorov, A., 2016. Mapping tree height distributions in Sub-Saharan Africa using Landsat 7 and 8 data. Remote Sensing of Environment, 185: 221-232.
- Iizuka, K., Yonehara, T., Itoh, M. and Kosugi, Y., 2018. Estimating tree height and diameter at breast height (DBH) from digital surface models and orthophotos obtained with an unmanned aerial system for a Japanese cypress (Chamaecyparis obtusa) forest. Remote Sensing, 10(1): 13.
- Lee, J.H., Ko, Y. and McPherson, E.G., 2016. The feasibility of remotely sensed data to estimate urban tree dimensions and biomass. Urban Forestry and Urban Greening, 16: 208-220.
- Lee, W.J. and Lee, C.W., 2018. Forest canopy height estimation using multiplatform remote sensing dataset. Journal of Sensors: 1593129.
- Lin, Y., Jiang, M., Yao, Y., Zhang, L. and Lin, J., 2015. Use of UAV oblique imaging for the detection of individual trees in residential environments. Urban Forestry and Urban Greening, 14(2): 404-412.
- Li, W., Guo, Q., Jakubowski, M.K. and Kelly, M., 2012. A new method for segmenting individual trees from the Lidar point cloud. Photogrammetric Engineering and Remote Sensing, 78(1): 75-84.
- Li, Z., Zhu, Q. and Gold, C., 2004. Digital Terrain Modeling: Principals and Methodology. CRC Press, Boca Raton, Florida, 340p.
- Marvie-Mohadjer, M.R., 2011. Silviculture. University of Tehran Press, Tehran, 418p.
- Miri, N., Darvishsefat, A.A., Zargham, N. and Shakeri, Z., 2017. Estimation of leaf area index in Zagros forests using Landsat 8 data. Iranian Journal of Forest, 9(1): 29-42 (In Persian).
- Mohan, M., Silva, C.A., Klauberg, C., Jat, P., Catts, G., Cardil, A., Hudak, A.T. and Dia, M., 2017. Individual tree detection from unmanned aerial vehicle (UAV) derived canopy height model in an open canopy mixed conifer forest. Forests, 8(9): 340.
- Owji, M.Gh. and Hamzehpour, M., 2012. Vegetation Profile of Wild Pistachio Experimental Forest. Published by Research Institute of Forests and Rangelands, Tehran, 240p (In Persian).
- Panagiotidis, D., Abdollahnejad, A., Surový, P. and Chiteculo, V., 2017. Determining tree height and crown diameter from high-resolution UAV imagery. International Journal of Remote Sensing, 38(8-10): 2392-2410.
- Pir Bavaghar, M., 2011. Evaluation of capability of IRS-P6 satellite data for predicting quantitative attributes of forests (case study: Northern Zagros forests). Iranian Journal of Forest, 3(4): 277-289 (In Persian).
- Puliti, S., Solberg, S. and Granhus, A., 2019. Use of UAV photogrammetric data for estimation of biophysical properties in forest stands under regeneration. Remote Sensing, 11(3): 233.
- Rajabpour Rahmati, M., Darvishsefat, A.A., Baghdadi, N., Namiranian, M. and Soofi Mariv, H., 2015. Estimation of forest canopy height in mountainous areas using ICESat-GLAS data. Iranian Journal of Forest and Poplar Research, 23(1): 90-103 (In Persian).
- Rezayan, F. and Erfanifard, Y., 2016. Estimating biophysical parameters of Persian oak coppice trees using UltraCam-D airborn imagery in Zagros semi-arid woodlands. Arid Environment, 133: 10-18.
- Rokhmana, C.A., 2015. The potential of UAV-based remote sensing for supporting precision agriculture in Indonesia. Procedia Environmental Sciences, 24: 245-253.
- Sagheb Talebi, Kh., Sajedi, T. and Pourhashemi, M., 2014. Forests of Iran: A Treasur from the Past, a Hope for Future. Springer, Dordrecht, 160p.
- Schowengerdt, R.A., 2007. Remote Sensing: Models and Methods for Image Processing. Third Edition, Academic Press, Burlington, Massachusetts, 560p.
- Xiang, H. and Tian, L., 2011. Method for automatic georeferencing aerial remote sensing (RS) images from an unmanned aerial vehicle (UAV) platform. Biosystems Engineering, 108(2): 104-113.
- Yim, J.S., Kim, Y.H., Kim, S.H., Jeong, J.H. and Shin, M.Y., 2011. Comparison of the k-nearest neighbor technique with geographical calibration for estimating forest growing stock volume. Canadian Journal of Forest Research, 41(1): 73-82.
- Yousefi, S., Mirzaee, S. and Zeini Vand, H., 2013. Investigation deforestation trends in Zagros mountain with using GIS and RS (Case study: Marivan). Journal of Applied RS and GIS Techniques in Natural Resources Science, 4(2): 15-23 (In Persian).
- Zahawi, R.A., Dandois, J.P., Holl, K.D., Nadwodny, D., Reid, J.L. and Ellis, E.C., 2015. Using lightweight unmanned aerial vehicles to monitor tropical forest recovery. Biological Conservation, 186: 287-295.
- Zarco-Tejada, P.J., Diaz-Varela, R., Angileri, V. and Loudjani, P., 2014. Tree height quantification using very high resolution imagery acquired from an unmanned aerial vehicle (UAV) and automatic 3D photo-reconstruction methods. European Journal of Agronomy, 55: 89-99.
- Zobeiry, M., 2000. Forest Inventory (Measurement of Tree and Forest). University of Tehran Press, Tehran, 401p (In Persian).