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1.
Environ Monit Assess ; 195(6): 678, 2023 May 16.
Article in English | MEDLINE | ID: mdl-37191833

ABSTRACT

Tree diameter measurement is one of the most important stages of forest inventories to assess growing stock, aboveground biomass, and landscape restoration options, among others. This study investigates the accuracy of measuring tree diameters using a Light Detection and Ranging (LiDAR)-equipped smartphone vs. a normal caliper (reference data) and the opportunity to use low-cost smartphone-based applications in forest inventories. To estimate the diameter at breast height (DBH) of single trees, we used a smartphone with a third-party app that automatically analyzed three-dimensional (3D) point clouds. For two different measurement techniques, we compared the two measurement techniques based on DBH data from 55 Calabrian pine (Pinus brutia Ten.) and 50 oriental plane (Platanus orientalis L.) trees using the paired-sample t-test and Wilcoxon signed-rank test. Mean absolute error (MAE), mean squared error (MSE), root mean square error (RMSE), percent bias (PBIAS), and coefficient of determination (R2) were used as precision and error statistics. Statistical differences were observed between the reference and smartphone-based DBH according to the paired-sample t-test and Wilcoxon signed-rank test. The R2 values obtained were determined as 0.91, 0.88, and 0.88 for Calabrian pine, oriental plane, and all tree species (105 trees), respectively. In addition to the overall accuracy performance of the comparison between reference and estimations, MAE, MSE, RMSE, and PBIAS values for the DBH of 105 tree stems were calculated as 1.56 cm, 5.42 cm, 2.33 cm, and - 5.10%, respectively. The estimation accuracies increased in regular stem forms compared with forked stems particularly observed on plane trees. Further experiments are needed to investigate the uncertainties associated with trees of different stem forms, species (coniferous or deciduous), different work environments, and different types of LiDAR and LiDAR-based app scanners.


Subject(s)
Pinus , Trees , Smartphone , Environmental Monitoring/methods , Forests , Biomass
2.
Environ Monit Assess ; 191(1): 32, 2018 Dec 28.
Article in English | MEDLINE | ID: mdl-30591964

ABSTRACT

Well-maintained pavements reduce occurring severe accidents on horizontal curves. For this reason, the monitoring and evaluation of pavement conditions are important. This study evaluates pavement conditions considering volumetric degradation or displacement on 11 horizontal curves in forest roads, depending on meteorological conditions, traffic effects, and curve parameters. Within this context, pavement displacement (degradation) was investigated and measured with terrestrial laser scanning (TLS) for a year on a monthly basis. In this study, two multiple regression models were developed to estimate the degradation values of a forest road. According to model 1, which was developed to estimate the loss volume values, the adjusted R2 was 0.658. For model 2, which was developed to estimate the gain volume values, the adjusted R2 was 0.490. Validations of models were evaluated with different statistical tests. In conclusion, volumetric degradation can be calculated with TLS-based data. Forest road designers should determine horizontal curve characteristics, taking into consideration the pavement degradation and traffic safety.


Subject(s)
Accidents, Traffic , Automobile Driving , Environment Design , Environmental Monitoring/methods , Forests , Humans , Surface Properties , Weather
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