4.8 Review

Atmospheric cloud modeling methods in computer graphics: A review, trends, taxonomy, and future directions

出版社

ELSEVIER
DOI: 10.1016/j.jksuci.2020.11.030

关键词

Atmospheric cloud; Cloud modeling; Cloud shape; Driven methods; Computer graphics; Visualization

资金

  1. Universiti Teknologi Malaysia

向作者/读者索取更多资源

This article provides an in-depth review of atmospheric cloud modeling methods, analyzing research trends, categorizing methods, and summarizing specific methods, providing a comprehensive understanding for researchers and practitioners.
The modeling of atmospheric clouds is one of the crucial elements in the natural phenomena visualization system. Over the years, a wide range of approaches has been proposed on this topic to deal with the challenging issues associated with visual realism and performance. However, the lack of recent review papers on the atmospheric cloud modeling methods available in computer graphics makes it difficult for researchers and practitioners to understand and choose the well-suited solutions for developing the atmospheric cloud visualization system. Hence, we conducted a comprehensive review to identify, analyze, classify, and summarize the existing atmospheric cloud modeling solutions. We selected 113 research studies from recognizable data sources and analyzed the research trends on this topic. We defined a taxonomy by categorizing the atmospheric cloud modeling methods based on the methods' similar characteristics and summarized each of the particular methods. Finally, we underlined several research issues and directions for potential future work. The review results provide an overview and general picture of the atmospheric cloud modeling methods that would be beneficial for researchers and practitioners.(c) 2020 The Authors. Published by Elsevier B.V. on behalf of King Saud University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据