Rybakov G. K. Estimation of Mean Tree Stand Volume Using High-Resolution Aerial RGB Imagery and Digital Surface Model, Obtained from sUAV and Trestima Mobile Application
How to cite: Rybakov G. K. Estimation of mean tree stand volume using high-resolution aerial RGB imagery and digital surface model, obtained from sUAV and Trestima mobile application // Sibirskij Lesnoj Zurnal (Sib. J. For. Sci.). 2017. N. 3: 3–18 (in English with Russian abstract).
© Rybakov G. K., 2017
This study considers a remote sensing technique for mean volume estimation based on a very high-resolution (VHR) aerial RGB imagery obtained using a small-sized unmanned aerial vehicle (sUAV) and a high-resolution photogrammetric digital surface model (DSM) as well as an innovative technology for field measurements (Trestima). The study area covers approx. 220 ha of forestland in Finland. The work concerns the entire process from remote sensing and field data acquisition to statistical analysis and forest volume wall-to-wall mapping. The study showed that the VHR aerial imagery and the high-resolution DSM produced based on the application of the sUAV have good prospects for forest inventory. For the sUAV based estimation of forest variables such as Height, Basal Area and mean Volume, Root Mean Square Error constituted 6.6 %, 22.6 % and 26.7 %, respectively. Application of Trestima for estimation of the mean volume of the standing forest showed minor difference over the existing Forest Management Plan at all the selected forest compartments. Simultaneously, the results of the study confirmed that the technologies and the tools applied at this work could be a reliable and potentially cost-effective means of forest data acquisition with high potential of operational use.