文献类型：期刊文献

英文题名：An Automatic Identification Method of Crested Ibis (Nipponia nippon) Habitat Based on Spatiotemporal Density Detection

作者：Jiang, Xian[1,2] Yang, Tingdong[1,2] Liu, Dongping[3,4] Zheng, Yili[5] Chen, Yan[1,2] Li, Fan[1,2]

第一作者：Jiang, Xian;蒋娴

通信作者：Chen, Y[1];Li, F[1];Chen, Y[2];Li, F[2]|[a0005b420cde33cd954a9]陈艳;

机构：[1]Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China;[2]Natl Forestry & Grassland Adm, Key Lab Forestry Remote Sensing & Informat Syst, Beijing 100091, Peoples R China;[3]Chinese Acad Forestry, Ecol & Nat Conservat Inst, Key Lab Forest Protect Natl Forestry & Grassland, Beijing 100091, Peoples R China;[4]Chinese Acad Forestry, Environm & Nat Conservat, Beijing 100091, Peoples R China;[5]Beijing Forestry Univ, Sch Technol, Beijing 100013, Peoples R China

年份：2022

卷号：12

期号：17

外文期刊名：ANIMALS

收录：;Scopus(收录号：2-s2.0-85137780876);WOS:【SCI-EXPANDED(收录号:WOS:000851148100001)】；

基金：The research was supported by Fundamental Research Funds for the Central PublicWelfare Research Institutes: Visual Analysis of Animal Trajectory Monitoring Data-Taking Crested Ibis as an Example (CAFYBB2021SY008).

语种：英文

外文关键词：crested ibis; habitat; overnight site; foraging site; spatial density; temporal density

摘要：Simple Summary The trajectory data of crested ibis (Nipponia nippon Temminck, 1835) have been obtained by HQBG3621L backpack-style tracker. By combining the spatial and temporal features of the trajectory data, an improved spatiotemporal clustering-based DBSCAN method was adopted to detect crested ibis's stopping points and identify the crested ibis's habitat. The clustering results are consistent with those from remote sensing images and field surveys. To address the current challenges of the heavy workload, time-consuming nature and labor-intensiveness involved in existing crested ibis's (Nipponia nippon Temminck, 1835) habitat identification approaches, this paper proposes an automatic habitat identification method based on spatiotemporal density detection. With consideration of the characteristics of the crested ibis's trajectory data, such as aggregation, repeatability, and uncertainty, this method achieves detecting the crested ibis's stopping points by using the spatial characteristics of the trajectory data. On this basis, an improved spatiotemporal clustering-based DBSCAN method is proposed in this paper, incorporating temporal characteristics of the trajectory data. By combining the spatial and temporal features, the proposed method is able to accurately identify the roosting and foraging sites among the crested ibis's stopping points. Supported by remote sensing images and field investigations, it was found that the method proposed in this paper has a good clustering effect and can effectively identify the crested ibis's foraging sites and overnight roosting areas. Specifically, the woodland, farmland, and river areas are the common foraging sites for the crested ibis, while the woodland with large trees is their common overnight site. Therefore, the method proposed in this paper can provide technical support for identifying and protecting the crested ibis's habitats.