Spatial-temporal analysis on bird habitat discovery in China

机译：中国鸟类栖息地发现的时空分析

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摘要

Exploring migration patterns through uncovering migratory birds' habitat information is very important in biology, which has scientific significance in animal habitat conservation and avian influenza control. In this paper, we convert the traditional biology problem into a computational study and use data mining techniques to analyze the spatial and temporal distribution of bird-watching data in China. First, we present an improved hierarchical clustering algorithm (IHDBSCAN) to identify the habitats/stopovers of migrant birds. Then, we use a kernel smoothing method to fit the temporal distribution of bird observation in each spatial cluster. A hierarchical cluster tree is generated where the leaf nodes indicate different bird habitats/stopovers. Finally, the results is visualized on the map of China. Experimental results show that the proposed algorithm can effectively find the spatial and temporal distribution of Anseriformes' habitats.

机译：通过揭示候鸟的栖息地信息来探索迁徙方式在生物学中非常重要，这在保护动物栖息地和控制禽流感方面具有科学意义。在本文中，我们将传统的生物学问题转化为计算研究，并使用数据挖掘技术来分析中国观鸟数据的时空分布。首先，我们提出一种改进的层次聚类算法（IHDBSCAN），以识别迁徙鸟类的栖息地/中途停留地。然后，我们使用核平滑法来拟合每个空间簇中鸟类观测的时间分布。生成层次聚类树，其中叶节点指示不同的鸟类栖息地/中途停留。最后，结果在中国地图上可视化。实验结果表明，该算法可以有效地找到无形动物栖息地的时空分布。

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来源
《2017 International Conference on Security, Pattern Analysis, and Cybernetics》|2017年|573-578|共6页
会议地点 Shenzhen(CN)
作者
Xiaoming Zhan; Yanming Ye; Yaoxin Zhuo; Benyun Shi; Yizhi Ren; Weitong Hu;
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作者单位

School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China;

School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China;

School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, China;

School of Cyberspace, Hangzhou Dianzi University, Hangzhou 310018, China;

School of Cyberspace, Hangzhou Dianzi University, Hangzhou 310018, China;

School of Cyberspace, Hangzhou Dianzi University, Hangzhou 310018, China;

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原文格式 PDF
正文语种 eng
中图分类
关键词
Birds; Clustering algorithms; Kernel; Data mining; Partitioning algorithms; Security; Pattern analysis;

机译：鸟类;聚类算法;内核;数据挖掘;分区算法;安全性;模式分析;;

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1. 雪雀属鸟类栖息地在中国的分布 [J] . 屈延华, 雷富民, 尹祚华动物学报（英文版） . 2002,第004期
2. Assessment of habitat change on bird diversity and bird–habitat network of a Coral Island, South China Sea [J] . Li Yingcan, Chen Zhiwen, Peng Chao, BMC Evolutionary Biology . 2021,第a期

机译：南海珊瑚岛鸟类多样性和鸟居网络的栖息地变化评估
3. The influence of land use change on the spatial-temporal variability of habitat quality between 1990 and 2010 in Northeast China [J] . Limin Dai, Shanlin Li, Bernard J.Lewis, 林业研究（英文版） . 2019,第006期

机译：1990-2010年中国东北土地利用变化对生境质量时空变异的影响
4. Spatial-Temporal Dynamics of China’s Terrestrial Biodiversity: A Dynamic Habitat Index Diagnostic [J] . Chunyan Zhang, Danlu Cai, Shan Guo, Remote Sensing . 2016,第3期

机译：中国陆地生物多样性的时空动态：动态生境指数诊断
5. Spatial-temporal analysis on bird habitat discovery in China [C] . Xiaoming Zhan, Yanming Ye, Yaoxin Zhuo, International Conference on Security, Pattern Analysis, and Cybernetics . 2017

机译：中国鸟类栖息地发现的空间时间分析
6. The study of seasonal composition and dynamics of wetland ecosystems and wintering bird habitat at Poyang Lake, PR China using object-based image analysis and field observations. [D] . Dronova, Iryna. 2012

机译：利用基于对象的图像分析和实地观察研究PR阳湖湿地生态系统的季节组成和动态以及越冬鸟类的栖息地。
7. Assessment of habitat change on bird diversity and bird–habitat network of a Coral Island South China Sea [O] . Yingcan Li, Zhiwen Chen, Chao Peng, 2021

机译：南海珊瑚岛鸟类多样性与鸟居网络的栖息地变化评估
8. Spatial-Temporal Dynamics of China’s Terrestrial Biodiversity: A Dynamic Habitat Index Diagnostic [O] . Chunyan Zhang, Danlu Cai, Shan Guo, 2016

机译：中国陆地生物多样性的时空动态：动态栖息地指数诊断

Spatial-temporal analysis on bird habitat discovery in China

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