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Open AccessArticle

Feasibility of Google Tango and Kinect for Crowdsourcing Forestry Information

Finnish Geospatial Research Institute, Geodeetinrinne 2, FI-02430 Masala, Finland
School of Engineering, Aalto University, P.O. Box 14100, FI-00076 Aalto, Finland
Author to whom correspondence should be addressed.
Forests 2018, 9(1), 6;
Received: 20 November 2017 / Revised: 15 December 2017 / Accepted: 16 December 2017 / Published: 21 December 2017
(This article belongs to the Section Forest Inventory, Quantitative Methods and Remote Sensing)
In this paper, we demonstrate the feasibility of using the Microsoft Kinect and Google Tango frame-based depth sensors for individual tree stem measurements and reconstruction for the purpose of forest inventory. Conventionally field reference data in forest inventory are collected at tree and sample plot level by means of manual measurements (e.g., a caliper), which are both labor-intensive and time-consuming. In this study, color (i.e., red, green and blue channels, RGB) and range images acquired by a Kinect and Tango systems were processed and used to extract tree diameter measurements for the individual tree stems. For this, 121 reference stem diameter measurements were made with tape and caliper. Kinect-derived tree diameters agreed with tape measurements to a 1.90 cm root-mean-square error (RMSE). The stem curve from the ground to the diameter at breast height agreed with a bias of 0.7 cm and random error of 0.8 cm with respect to the reference trunk. For Tango measurements, the obtained stem diameters matched those from tape measurement with an RMSE of 0.73 cm, having an average bias of 0.3 cm. As highly portable and inexpensive systems, both Kinect and Tango provide an easy way to collect tree stem diameter and stem curve information vital to forest inventory. These inexpensive instruments may in future compete with both terrestrial and mobile laser scanning or conventional fieldwork using calipers or tape. Accuracy is adequate for practical applications in forestry. Measurements made using Kinect and Tango type systems could also be applied in crowdsourcing context. View Full-Text
Keywords: laser radar; remote sensing; forestry; Kinect; DBH; point cloud; mobile laser scanning laser radar; remote sensing; forestry; Kinect; DBH; point cloud; mobile laser scanning
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MDPI and ACS Style

Hyyppä, J.; Virtanen, J.-P.; Jaakkola, A.; Yu, X.; Hyyppä, H.; Liang, X. Feasibility of Google Tango and Kinect for Crowdsourcing Forestry Information. Forests 2018, 9, 6.

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