Estimation of aboveground biomass using aerial photogrammetry from unmanned aerial vehicle in teak (Tectona grandis) plantation in Thailand

##plugins.themes.bootstrap3.article.main##

SASIWIMOL RINNAMANG
KAMPANART SIRIRUEANG
SORAVIS SUPAVETCH
PONTHEP MEUNPONG

Abstract

Abstract. Rinnamang S, Sirirueang K, Supavetch S, Meunpong P. 2020. Estimation of aboveground biomass using aerial photogrammetry from unmanned aerial vehicles in teak (Tectona grandis) plantation in Thailand. Biodiversitas 21: 2369-2376. Thailand is one of the best teak planting locations in the world. Teak is one of the most species planting and a significant source of high-value timber in Thailand. For plantation management, biomass is one of the important factors while determining the production of a plantation and also for sustainable forest management. Unmanned Aerial Vehicles (UAV) have the ability to produce 3D RGB digital images which can be used to study the plantation characteristics. This study aimed to use aerial images and photogrammetry techniques derived from unmanned aerial vehicles (UAV) to estimate teak biomass in Thong Pha Phum plantation, Kanchanaburi Province, Thailand. We conducted our study on 15-and 36-year-old teak stands, and compared the tree dimension between data obtained from field measurement and that from aerial images and photogrammetry techniques. In the 15-year-old stand, the average tree height estimated from the UAV and ground-truthing were 12.34 and 13.06 m, respectively. In the 36-year-old stand, the average tree height from the UAV and ground-truthing were 28.87 and 29.39 m, respectively. We found that in both stands, the difference between data generated from the UAV and ground-truthing data was not significant (p-value = 0.07 and 0.306, respectively). There was also a strong correspondence between tree height estimated from the UAV and that measured on the ground which is indicated by the high R2 (i.e. 0.70 and 0.64 for the 15-and 36-year-old stands, respectively). Using UAV generated data, the total biomass of 15-and 36-year-old stands was estimated to be around 42.07 t ha-1 and 67.13 t ha-1, respectively. The overall results suggest that UAV can be used as an effective tool to survey and monitor stand’s productivity in teak plantation.

##plugins.themes.bootstrap3.article.details##

References
Adão T, Hruška J, Pádua L, Bessa J, Peres E, Morais R, Sousa J. 2017. Hyperspectral imaging: a review on UAV-based sensors, data processing and applications for agriculture and forestry. Remote Sensing 9(11): 1110-1140.
Aicardi I, Dabove P, Lingua AM, Piras M. 2017. Integration between TLS and UAV photogrammetry techniques for forestry applications. iForest - Biogeosciences and Forestry 10(1): 41-47.
Chaturvedi RK, Raghubanshi AS. 2015. Allometric Models for accurate estimation of aboveground biomass of teak in tropical dry forests of India. Forest Science 61(5): 938-949.
Diloksumpun S, Wachrinrat C, Chumsangsri T. 2014. An assessment of carbon storage in biomass of teak (Tectona grandis Linn.f) at Thong Phaphum Plantation. Proceedings of Exhibition on the Research Path Kasetsart University 2011. Kasetsart University, Bangkok, 28 January –5 February 2011.[Thailand]
Durkaya B, Durkaya A, Makineci E, Karaburk T. 2013. Estimating above-ground biomass and carbon stock of individual trees in uneven-aged Uludag Fir stands. Fresenius Environmental Bulletin 22(2): 428-434.
Edson C, Wing MG. 2011. Airborne Light Detection and Ranging (LiDAR) for individual tree stem location, height, and biomass measurements. Remote Sens 3(11): 2494-2528.
Forest Industry Organization. 2016. Sustainable forest management of forest industry organization policy. Bankok, Thailand.
Forest Industry Organization. 2018a. Forest Industry Organization action plan 2018. Bankok, Thailand.
Forest Industry Organization. 2018b. Thong Pha Phum forest plantation management summary. Bankok, Thailand.
Grznárová A, Mokroš M, Surový P, Slavík M, Pondelík M, Mergani? J. 2019. The crown diameter estimation from fixed wing type of UAV imagery. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13: 337-341.
Jayathunga S, Owari T, Tsuyuki S. 2018. The use of fixed–wing UAV photogrammetry with LiDAR DTM to estimate merchantable volume and carbon stock in living biomass over a mixed conifer–broadleaf forest. International Journal of Applied Earth Observation and Geoinformation 73: 767-777.
Kaartinen H, Hyyppä J, Yu X, Vastaranta M, Hyyppä H, Kukko A, Holopainen M, Heipke C, Hirschmugl M, Morsdorf F, Naessert E, Pitkanen J, Popescu S, Soberg S, Wolf BM, Wu J-C. 2012. An international comparison of individual tree detection and extraction using airborne laser scanning. Remote Sensing 4(4): 950-974.
Khosravipour A, Skidmore AK, Wang T, Isenburg M, Khoshelham K. 2015. Effect of slope on treetop detection using a LiDAR Canopy Height Model. ISPRS Journal of Photogrammetry and Remote Sensing 104: 44-52.
Kongmeesup I, Boonyanuphap J. 2019. Estimation of carbon offset for teak plantation in lower northern Thailand. Songklanakarin J. Sci. Technol 41(3): 580-586.
Koonkhunthod N, Sakurai K, Tanaka S. 2017. Composition and diversity of woody regeneration in a 37-year-old teak (Tectona grandis L.) plantation in Northern Thailand. Forest Ecology and Management 247(1-3): 246-254.
Lim YS, La PH, Park JS, Lee MH, Pyeon MW, Kim JI. 2015. Calculation of tree height and canopy crown from drone images using segmentation. Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography 33(6): 605-613.
Lisein J, Pierrot-Deseilligny M, Bonnet S, Lejeune P. 2013. A photogrammetric workflow for the creation of a forest canopy height model from small unmanned aerial system imagery. Forests 4(4): 922-944.
Meunpong P. 2012. Nutrient and carbon storage in forest plantation, Prachuap Khiri Khan province, Thailand. [Dissertation]. Kasetsart University, Bangkok.[Thailand]
Mohan M, Silva CA, Klauberg C, Jat P, Catts G, Cardil A, Hudak AT, 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): 340-357.
Navarro JA, Alfredo N, Fernández-Landa A, Esteban J, Rodríguez-Noriega P, Guillén-Climent ML. 2019. Integration of UAV, Sentinel-1, and Sentinel-2 data for mangrove plantation aboveground biomass monitoring in Senegal. Remote Sens 11(1): 77-100.
Noda I, Himmapan W. 2014. Effects of silvicultural alternatives on model-based financial evaluation of teak (Tectona grandis L.) farm forestry management for small-scale farmers in Northeast Thailand. Open Journal of Forestry 4(5): 558-569.
Otero V, Kerchove RVD, Satyanarayana B, Martínez-Espinosa C, Fisol MAB, Ibrahim MRB, Sulong I, Mohd-Lokman H, Lucas R, Dahdouh-Guebas F. 2018. Managing mangrove forests from the sky: forest inventory using field data and unmanned aerial vehicle (UAV) imagery in the Matang Mangrove Forest Reserve, peninsular Malaysia. Forest Ecology and Management 411: 35-45.
Panagiotidis D, Abdollahnejad A, Surový P, Chiteculo V. 2017. Determining tree height and crown diameter from high-resolution UAV imagery. International Journal of Remote Sensing 38(8-10): 2392-2410.
Pe´rez D, Kanninen M. 2003. Aboveground biomass of Tectona grandis plantations in Costa Rica. Trop. For. Sci. 15(1): 199-213.
Pe´rez D, Kanninen M. 2005. Stand growth scenarios for Tectona grandis plantations in Costa Rica. For. Ecol. Manage 210: 425–441.
Pitkänen J, Maltamo M, Hyyppä J, Yu X. 2004. Adaptive methods for individual tree detection on airborne laser based canopy height model. Proceedings of ISPRS Workshop Laser-Scanners for Forest and Landscape Assessment. In International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences; ISPRS: Vienna, Austria 36(8/W2): 187–191. Freiburg, 3–6 October 2004.[Germany]
Royal Forest Department. 2010. Teak. Royal Forest Department: Bangkok Thailand.
Shahbazi M, Théau J, Ménard P. Recent applications of unmanned aerial imagery in natural resource management. GIScience & Remote Sensing; 2014, 51(4): 339-365.
Somogyi Z, Cienciala E, Mäkipää R, Muukkonen P, Lehtonen A, Weiss P. Indirect methods of large-scale forest biomass estimation. European Journal of Forest Research 2006; 126(2), 197-207.
Tang L, Shao G. Drone remote sensing for forestry research and practices. Journal of Forestry Research 2015; 26(4): 791-797.
Thomkrajang T. 2017. Estimation of carbon sequestion in community forests using UAV technique: a case study of Ban Bu Ta Tong community forests, Tambon Naklang, Sungnoen districts, Nakhonratchasima province. [Dissertation]. Chulalongkorn University, Bangkok.[Thailand]
Thongfak C. 2012. Biomass and carbon storage of Teak (Tectona grandis Linn.f) at Thongphaphum plantation, Kanchanaburi province. [Dissertation]. Kasetsart University, Bangkok.[Thailand]
Viriyabuncha C, Chittachumnonk P, Suthisrisinn C, Samran s, Peawsa-ad K. 2001. Adjusting Equation to Estimate the Above-ground Biomass of Teak Plantation in Thailand. Proceedings of the 7th Silvicultural Seminar. Kasetsart University, Bangkok, 12-14 December 2001. [Thailand]
Warner AJ, Jamroenprucksa M, Puangchit L. 2017. Buttressing impact on diameter estimation in plantation teak ( Tectona grandis L.f.) sample trees in northern Thailand. Agriculture and Natural Resources 51(6): 520-525.
Webster C, Westoby M, Rutter N, Jonas T. 2018. Three-dimensional thermal characterization of forest canopies using UAV photogrammetry. Remote Sensing of Environment 209: 835-847.
Zainuddin K, Jaffri MH, Zainal MZ, Ghazali N, Samad AM. 2016. Verification test on ability to use low-cost UAV for quantifying tree height. Proceedings of the 2016 IEEE 12th International Colloquium on Signal Processing & Its Applications (CSPA). Melaka, 4-6 March 2016.[Malaysia]
Zarco-Tejada PJ, Diaz-Varela R, Angileri V, 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.