This study focuses on identifying and classifying urban Earthwork-Related Locations (ERLs) in Chengdu using GPS trajectory data from construction waste hauling trucks. The research aims to enhance authorities' capability to manage ERLs for effective urban environmental management. By comparing machine learning models, the study demonstrates that a Random Forest model achieves the highest classification accuracy of 77.8%. The importance of features such as distance from the city center, stay time, and points of interest is highlighted. Model simplification shows that high accuracy can be achieved with a subset of key features.
The study was supported by grants from the National Natural Science Foundation of China and the Natural Science Foundation of Sichuan Province.
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by Lei Yu,Ke Ha... о arxiv.org 03-20-2024
https://arxiv.org/pdf/2402.14698.pdfГлибші Запити