Segmentation of individual trees in urban MLS point clouds using a deep learning framework based on cylindrical convolution network

IF 7.5 1区地球科学 Q1 Earth and Planetary Sciences

International Journal of Applied Earth Observation and Geoinformation Pub Date : 2023-09-01 DOI:10.1016/j.jag.2023.103473

Tengping Jiang, Shan Liu, Qinyu Zhang, Xin Xu, Jian Sun, Yongjun Wang

引用次数: 0

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基于圆柱卷积网络的深度学习框架在城市MLS点云中对树木进行分割

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Applied Earth Observation and Geoinformation 地学-遥感

CiteScore

10.20

自引率

8.00%

发文量

审稿时长

7.2 months

期刊介绍： The International Journal of Applied Earth Observation and Geoinformation publishes original papers that utilize earth observation data for natural resource and environmental inventory and management. These data primarily originate from remote sensing platforms, including satellites and aircraft, supplemented by surface and subsurface measurements. Addressing natural resources such as forests, agricultural land, soils, and water, as well as environmental concerns like biodiversity, land degradation, and hazards, the journal explores conceptual and data-driven approaches. It covers geoinformation themes like capturing, databasing, visualization, interpretation, data quality, and spatial uncertainty.