Spatial-temporal analysis on bird habitat discovery in China

Xiaoming Zhan, Yanming Ye*, Yaoxin Zhuo, Benyun SHI, Yizhi Ren, Weitong Hu

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

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.

Original languageEnglish
Title of host publication2017 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages573-578
Number of pages6
ISBN (Electronic)9781538630167
DOIs
Publication statusPublished - 27 Feb 2018
Event2017 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2017 - Shenzhen, China
Duration: 15 Dec 201717 Dec 2017

Publication series

Name2017 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2017
Volume2018-January

Conference

Conference2017 International Conference on Security, Pattern Analysis, and Cybernetics, SPAC 2017
Country/TerritoryChina
CityShenzhen
Period15/12/1717/12/17

Scopus Subject Areas

  • Safety, Risk, Reliability and Quality
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications

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