The efficiency of augmented reality technology in smartphones for estimating the height of trees (case study: green space conifers of Lorestan factulty agriculture and natural resources)

Document Type : Research Paper

Authors

1 Ph.D. Student, Forestry Group, Faculty of Agriculture and Natural Resources, University of Lorestan, Khorramabad, I.R. Iran

2 Assoc., Prof., Forestry Group, Faculty of Agriculture and Natural Resources, University of Lorestan, Khorramabad, I.R. Iran

Abstract

Achieving sustainable forest management at different levels depends on basic information measurement to understand the use of this data correctly. The height of trees is one of the most important components of forest measurement that it forms the body of many forestry research works. Therefore, much effort is being made to measure it faster and more accurately. Nowadays, smartphones have a variety of technologies for measuring the height of trees. In this research, the researcher tried to evaluate the efficiency of height measurement technology based on augmented of additional reality by carefully checking the height of some trees. For this purpose, the number of 75 coniferous trees in the Faculty of Agriculture and Natural Resources of Lorestan University was randomly selected and their height was measured by using the trupulse 360 (reference tool) and Augmented reality technology available in both iPhone 8 and Samsung S 8 smartphones. Paired comparisons of data were performed by using paired t-test and the correlation between data, the mean square error and the relative mean square error was measured too. By using the height measurement application, the highest correlation and the lowest RMSE value for iPhone8 were obtained, 0.989, 0.285 m and 4/97% respectively. By using the popular and current technology-based application, the RMSE was estimated to be 0.354 meters and 8/56% for the iPhone and 0.377 meters and 14/5% for the Samsung Galaxy. It seems the technologies in the new smartphones have this ability to replace the traditional tree height measurement tools.

Keywords


[1]. Shamsoddini, A. (2016). Pine forest structural parameter retrieval using radar images. Journal of Spatial Planning, 20(1): 53-78.
[3]. Karimzadeh Jafari, E., Naghavi, H., Adeli, K., and Latifi, H. (2017). Investigating the feasibility of Timber volume estimating using Landsat 8 satellite images. In: National Conference on Knowledge and Innovation in Wood and Paper Industry with Environmental Approach. Dec.20. Karaj, Iran, 1-10.
[4]. Sasanifar, S., and Namiraninan, M. (2017). Survey equality of two instrument of measurement set of distance and azimuth (Trupulse360) and sonto Clinometers in measurement of tree height. Journal of the Conservation and Utilization of Natural Resources, 6 (1): 15-26.
[5]. Vastaranta, M.,Melkas, T., Holopainen, M., Kaartinen, H., Hyyppä, J., and Hyyppä, H.(2009). Laser-based field measurements in tree-level forest data acquisition. The photogrammetric Journal of Finland. 21: 51-61.
[6]. Liang, X., Litkey, P., Hyyppä, J., Kaartinen, H., Vastaranta, M., and Holopainen, M. (2012). Automatic stem mapping using single-scan terrestrial laser scanning. geoscience and remote sensing, IEEE Transact, 59: 661-670.
[7]. Vastaranta, M., Latorre, E.G., Luoma, V., Saarinen, N., Holopainen, M., and Hyyppä, J. (2015). Evaluation of a smartphone app for forest sample plot measurements. Forests, 6: 1179-1194.
[8]. Wang, Y., Lehtomaki, M., Liang, X., Pyörälä, J., Kukko, A., Jaakkola, A., Liu, J., Feng, Z., Chen, R. and Hyyppä, J. (2019). Is field-measured tree height as reliable as believed – A comparison study of tree height estimates from field measurement, airborne laser scanning and terrestrial laser scanning in a boreal forest. ISPRS Journal of Photogrammetry and Remote Sensing, 147: 132–145.
[9]. Goodwin, AN. (2004). Measuring tall trees height from the ground. Tasforests, 15: 85-97.
[10]. Avery, T.E., and Burkhart, H. (2011). Forest Measurements. 5th Ed., McGraw-Hill. New York.
[11]. Pariyar, S., and Mandal, R.A. (2019). Comparative tree height measurement using different instrument .International Journal of Ecology and Environmental Sciences, 1(2): 12-17.
[12]. Lim, K., Treitz, P., Wulder, M., St-Onge, B., and Flood, M. (2003). LiDAR remote sensing of forest structure. Progress in Physical Geography, 27: 88–106.
[13]. Fan, Y., Feng, Z., Mannan, A., Khan, T.U., Shen, Ch., and Saeed, S. (2018). Estimating tree position, diameter at breast height, and tree height in real-time using a mobile phone with RGB-D SLAM. Remote Sensing, 10(11): 1845-1855.
[14]. Bijak, S., and Sarzyński, J. (2015). Accuracy of smartphone applications in the field measurements of tree height. Folia Forestalia Polonica, 57 (4): 240–244.
[15]. Itoh, T., Eizawa, J., Yano, N., Matsue, K., and Naito, K. (2010). Development of software to measure tree heights on the smartphone. Journal of the Japanese Forest Society, 92 (3): 221–225.
[16]. Villasante, A., and Fernandez, C. (2014). Measurement errors in the use of smartphones as low-cost forestry hypsometers. Silva Fennica, 48 (5): 1114. 1125.
[17]. Xinmei, W., Aijun, X., and Tingting, Y. (2019). Passive measurement method of tree height and crown diameter using a smartphone. Journal and Magezines of IEEE Access, 8: 11669-11678.
[18]. Höllerer, T.H., and Feiner, S.K. (2004). Mobile Augmented Reality. Telegeoinformatics: Location-Based Computing and Services.
[19]. Alkandari, A., Almuntairi, N.M., Alhayyan, W., and Almoiri, A. (2019). Google project tango and arcore under the view of augmented reality. Journal of computational and Theoretical Nanoscience, 16(3): 294-300.
[20]. Follott, M., Nock, C.A., Buteau, C., and Messier, C. (2016). Testing a new approach to quality growth response to pruning among three temperate three species. Arboriculture & Urban Forestry, 42(3): 133-145.
[21]. Momeni, M. and Ghayoumi, A.F. (2012). Statistical analysis with SPSS. 7th Ed., Shayegan Treasure Publishing, Tehran.