Development and Testing of a New Ground Measurement Tool to Assist in Forest GIS Surveys

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.

Internal Tree Trunk Decay Detection Using Close-Range Remote Sensing Data and the PointNet Deep Learning Method

“…In the latter mentioned field, the method is used mainly to identify tree species or tree damage in aerial images [38,54,55]. In some studies from the field of forest inventory, even terrestrial photography is used for tree species determination or pest detection, but no studies were found examining the relationship between internal tree stem decay and its shape in 3D space [56,57]. Nevertheless, the task of object classification is common.…”

Supporting Operational Tree Marking Activities through Airborne LiDAR Data in the Frame of Sustainable Forest Management

“…More specifically, the forest manager is recommended to use a GIS mobile application, which can serve as a complementary tool for forest management since it enables faster and more accurate (compared to the use of study) field data collection, reliable data analysis, and an efficient real-time update of the collected sddata whenever required [40,42]. For decades, researchers have been developing mobile GIS applications for a variety of environmental field surveys, including forest tree measurements [42][43][44][45][46]. Nowadays, a number of mobile GIS applications exist, either open-source or proprietary, such as QField (https://qfield.org/, accessed on 1 October 2023), ArcGIS Field Maps (https://www.esri.…”

Multipurpose GIS Portal for Forest Management, Research, and Education

“…It has been shown that a GIS is useful for forest navigation and data collection, and because it provides instant access to geographic data, accurate site surveying, and flexible data collection a mobile GIS a valuable tool for forest research. Mobile applications for timber harvesting, forest mapping, wildfire prevention, and logistics have been developed for use with a GIS [38][39][40][41] and are being used by foresters; in contrast, mobile GIS and global navigation satellite systems are only occasionally used in teaching, or in student activities, coursework, or final projects. However, no significant differences were found in the use of mobile devices among the target groups.…”