GNSS/INS-based positioning must be revised for forest mapping, especially inside the forest. This study deals with the issue of the processability of GNSS/INS-positioned MLS data collected in the forest environment. G...
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GNSS/INS-based positioning must be revised for forest mapping, especially inside the forest. This study deals with the issue of the processability of GNSS/INS-positioned MLS data collected in the forest environment. GNSS time-based point clustering processed the misaligned MLS point clouds collected from skid trails under a forest canopy. The points of a point cloud with two misaligned copies of the forest scene were manually clustered iteratively until two partial point clouds with the single forest scene were generated using a histogram of GNSS time. The histogram's optimal bin width was the maximum bin width used to create the two correct point clouds. The influence of GNSS outage durations, signal strength statistics, and point cloud parameters on the optimal bin width were then analyzed using correlation and regression analyses. The results showed no significant influence of GNSS outage duration or GNSS signal strength from the time range of scanning the two copies of the forest scene on the optimal width. The optimal bin width was strongly related to the point distribution in time, especially by the duration of the scanned plot's occlusion from reviewing when the maximum occlusion period influenced the optimal bin width the most (R2 = 0.913). Thus, occlusion of the sub-plot scanning of tree trunks and the terrain outside it improved the processability of the MLS data. Therefore, higher stem density of a forest stand is an advantage in mapping as it increases the duration of the occlusions for a point cloud after it is spatially tiled.
The pollution, changing according to various standards, is directly proportional to water quality in rivers. In this study, data and restrictions prescribed for standards of water quality such as Turkish Standards Ins...
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The pollution, changing according to various standards, is directly proportional to water quality in rivers. In this study, data and restrictions prescribed for standards of water quality such as Turkish Standards Institute (TSI), European Commission (EC), and the World Health Organization (WHO) were used to determine water pollution. For this purpose, correlation analysis was made to identify strong relationships between data. regression analysis and Arti fi cial Neural Networks (ANN) models are developed based on these standards by data obtained from correlation analysis. The Lower Sakarya River is selected as application area, and measurement of the water quality values of this river is used in these models. Pollution control flows in the river are obtained by the ANN models and regression analysis. The obtained results are compared with regard to these standards. (C) 2016 Sharif University of Technology. All rights reserved.
Autonomic functions of the body and gas exchange have been studied in one athlete (master of sports in skiing, aged 27 years, with a maximal oxygen consumption of 67 mL/(min kg));during a 6-h indoor ultra-marathon rac...
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