Exploration in mapping kernel-based home range models from remote sensing imagery with conditional adversarial networks
文献类型：期刊论文
| 作者 | Zheng, Ruobing1,2; Wu, Guoqiang1; Yan, Chao3; Zhang, Renyu4; Luo, Ze2; Yan, Baoping2 |
| 刊名 | Remote sensing
 |
| 出版日期 | 2018-11-01 |
| 卷号 | 10期号:11页码:16 |
| 关键词 | Home range Remote sensing Deep learning Generative adversarial networks Habitat mapping Bar-headed geese |
| ISSN号 | 2072-4292 |
| DOI | 10.3390/rs10111722 |
| 通讯作者 | Luo, ze(luoze@cnic.cn) |
| 英文摘要 | Kernel-based home range models are widely-used to estimate animal habitats and develop conservation strategies. they provide a probabilistic measure of animal space use instead of assuming the uniform utilization within an outside boundary. however, this type of models estimates the home ranges from animal relocations, and the inadequate locational data often prevents scientists from applying them in long-term and large-scale research. in this paper, we propose an end-to-end deep learning framework to simulate kernel home range models. we use the conditional adversarial network as a supervised model to learn the home range mapping from time-series remote sensing imagery. our approach enables scientists to eliminate the persistent dependence on locational data in home range analysis. in experiments, we illustrate our approach by mapping the home ranges of bar-headed geese in qinghai lake area. the proposed framework outperforms all baselines in both qualitative and quantitative evaluations, achieving visually recognizable results and high mapping accuracy. the experiment also shows that learning the mapping between images is a more effective way to map such complex targets than traditional pixel-based schemes. |
| WOS关键词 | HABITAT SUITABILITY ; SPACE USE ; WATERFOWL ; QUALITY ; ERROR |
| WOS研究方向 | Remote Sensing |
| WOS类目 | Remote Sensing |
| 语种 | 英语 |
| WOS记录号 | WOS:000451733800053 |
| 出版者 | MDPI |
| URI标识 | http://www.irgrid.ac.cn/handle/1471x/2374266 |
| 专题 | 计算机网络信息中心 |
| 通讯作者 | Luo, Ze |
| 作者单位 | 1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 2.Chinese Acad Sci, Comp Network Informat Ctr, E Sci Technol & Applicat Lab, Beijing 100190, Peoples R China 3.Vanderbilt Univ, Dept Elect Engn & Comp Sci, Nashville, TN 37240 USA 4.Toyota Technol Inst, Chicago, IL 60637 USA |
| 推荐引用方式 GB/T 7714 | Zheng, Ruobing,Wu, Guoqiang,Yan, Chao,et al. Exploration in mapping kernel-based home range models from remote sensing imagery with conditional adversarial networks[J]. Remote sensing,2018,10(11):16. |
| APA | Zheng, Ruobing,Wu, Guoqiang,Yan, Chao,Zhang, Renyu,Luo, Ze,&Yan, Baoping.(2018).Exploration in mapping kernel-based home range models from remote sensing imagery with conditional adversarial networks.Remote sensing,10(11),16. |
| MLA | Zheng, Ruobing,et al."Exploration in mapping kernel-based home range models from remote sensing imagery with conditional adversarial networks".Remote sensing 10.11(2018):16. |
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来源：计算机网络信息中心
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