Improving models for environmental applications of LiDAR: Novel approaches based on soft computing

Garcia-Gutierrez Jorge

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Improving models for environmental applications of LiDAR: Novel approaches based on soft computing

机译：LiDAR环境应用的改进模型：基于软计算的新颖方法

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This work proposes novel methodologies to improve the use of Light Detection And Ranging (LiDAR) for environmental purposes, especially for thematic mapping (LiDAR only or fused with other remote sensors) and the estimation of forest variables. The methodologies make use of well-known techniques from soft computing (machine learning and evolutionary computation) and their adaptation to develop LiDAR-derived products.

机译：这项工作提出了新颖的方法，以改善用于环境目的的光检测和测距（LiDAR）的使用，尤其是用于主题制图（仅LiDAR或与其他遥感器融合）和森林变量的估计。这些方法利用了软计算（机器学习和进化计算）中的众所周知的技术，并对其进行了改编来开发LiDAR衍生产品。

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来源
《AI communications》 |2016年第1期|213-214|共2页
作者
Garcia-Gutierrez Jorge;
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作者单位

Univ Seville, Dept Comp Languages & Syst, Seville, Spain;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种 eng
中图分类
关键词
LiDAR; machine learning; remote sensing; soft computing;

机译：LiDAR;机器学习;遥感;软计算;

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Improving models for environmental applications of LiDAR: Novel approaches based on soft computing

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