Abstract
In present forest surveys, some problems occur because of the cost and time required when using external tools to acquire tree measurement. Therefore, it is of great importance to develop a new cost-saving and time-saving ground measurement method implemented in a forest geographic information system (GIS) survey. To obtain a better solution, this paper presents the design and implementation of a new ground measurement tool in which mobile devices play a very important role. Based on terrestrial photogrammetry, location-based services (LBS), and computer vision, the tool assists forest GIS surveys in obtaining important forest structure factors such as tree position, diameter at breast height (DBH), tree height, and tree species. This paper selected two plots to verify the accuracy of the ground measurement tool. Experiments show that the root mean square error (RMSE) of the position coordinates of the trees was 0.222 m and 0.229 m, respectively, and the relative root mean square error (rRMSE) was close to 0. The rRMSE of the DBH measurement was 10.17% and 13.38%, and the relative Bias (rBias) of the DBH measurement was −0.88% and −2.41%. The rRMSE of tree height measurement was 6.74% and 6.69%, and the rBias of tree height measurement was −1.69% and −1.27%, which conforms to the forest investigation requirements. In addition, workers usually make visual observations of trees and then combine their personal knowledge or experience to identify tree species, which may lead to the situations when they cannot distinguish tree species due to insufficient knowledge or experience. Based on MobileNets, a lightweight convolutional neural network designed for mobile phone, a model was trained to assist workers in identifying tree species. The dataset was collected from some forest parks in Beijing. The accuracy of the tree species recognition model was 94.02% on a test dataset and 93.21% on a test dataset in the mobile phone. This provides an effective reference for workers to identify tree species and can assist in artificial identification of tree species. Experiments show that this solution using the ground measurement tool saves time and cost for forest resources GIS surveys.
Highlights
In the forest inventory, smartphone technology is widely used in field data collection [1,2].Combine geographic information system (GIS) software based on field maps with electronic devices for forest GIS surveys [3]
Combine GIS software based on field maps with electronic devices for forest GIS surveys [3]
In the experiment of two plots, the measurement results of the tree position by the ground measurement tool showed that the root mean square error (RMSE) of the tree position was 0.222 m and 0.229 m, respectively, and the data accuracy was within the standard accuracy requirements of the forest resource inventory
Summary
In the forest inventory, smartphone technology is widely used in field data collection [1,2].Combine GIS (geographic information system) software based on field maps with electronic devices (such as mobile phones or tablets) for forest GIS surveys [3]. When workers use GIS software on their smartphones to make forestry mapping or landscape mapping, the whole operation process mainly includes three steps: (1) Draw geometric figures such as tree position (point), shape (polygon) of small classes on the map; (2) Collect attribute data of trees or sub-compartment; (3) The collected attribute data are input into the GIS software to correspond with the geometric data on the map and generate. In the second step, collecting attribute data such as DBH (diameter at breast height), tree height, and position is the most time-consuming and laborious in the whole operation process [4,5,6,7], because workers usually use some independent equipment to assist in the Forests 2019, 10, 643; doi:10.3390/f10080643 www.mdpi.com/journal/forests. When encountering trees on steep slopes and cliffs in forests, which cannot be touched, only naked eye estimations can be used, which makes measurement accuracy difficult to guarantee
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