Can global navigation satellite system signals reveal the ecological attributes of forests?

Forests have important impacts on the global carbon cycle and climate, and they are also related to a wide range of industrial sectors. Currently, one of the biggest challenges in forestry research is effectively and accurately measuring and monitoring forest variables, as the exploitation potential of forest inventory products largely depends on the accuracy of estimates and on the cost of data collection. A low-cost crowdsourcing solution is needed for forest inventory to collect forest variables. Here, we propose global navigation satellite system (GNSS) signals as a novel type of observables for predicting forest attributes and show the feasibility of utilizing GNSS signals for estimating important attributes of forest plots, including mean tree height, mean diameter at breast height, basal area, stem volume and tree biomass. The prediction accuracies of the proposed technique were better in boreal forest conditions than those of the conventional techniques of 2D remote sensing. More importantly, this technique provides a novel, cost-effective way of collecting large-scale forest measurements in the crowdsourcing context. This technique can be applied by, for example, harvesters or persons hiking or working in forests because GNSS devices are widely used, and the field operation of this technique is simple and does not require professional forestry skills. (C) 2016 Elsevier B.V. All rights reserved.