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计算机系统应用:2018,27(10):248-254
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基于卷积神经网络的候鸟潜在分布预测
苏锦河1,2, 朴英超1, 罗泽1, 阎保平1
(1.中国科学院 计算机网络信息中心, 北京 100190;2.中国科学院大学, 北京 100049)
Mapping Potential Distribution of Wild Bird Using Convolutional Neural Network
SU Jin-He1,2, PIAO Ying-Chao1, LUO Ze1, YAN Bao-Ping1
(1.Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China;2.(University of Chinese Academy of Sciences, Beijing 100049, China)
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本文已被:浏览 67次   下载 91
投稿时间:2018-03-07    修订日期:2018-03-22
中文摘要: 从遥感影像中提取生态位因子在物种潜在分布模型中扮演着重要角色,然而这些模型存在数据质量低和训练样本少等问题.随着先进数据采集设备的应用,所获得的大量动物轨迹数据可以用来对物种潜在栖息地进行标记,进而从遥感影像中提取用于物种分布模型的有效训练样本.本文首先利用DBSCAN算法对动物轨迹数据进行聚类,基于聚类结果将遥感影像按照小区域分成正负样本,然后利用提出一种改进的卷积神经网络进行训练和预测斑头雁在青海湖周边的潜在分布情况.通过和传统基于灰度共生矩阵的方法进行比较,本文提出的方法在各项评价指标上都有一定提升,同时实验结果也表明我们方法能更好的预测斑头雁在青海湖周围的潜在分布情况.
中文关键词: 卷积神经网络  DBSCAN  栖息地  物种分布  候鸟
Abstract:Remote sensing images play an important role in the development of species distribution model. However, low spatial resolution ecological niche derived from remote sensing data and lack of fine-scale presence data requires alternative approaches. With the application of various data acquisition devices, a large number of animal movement data can be considered as the presence data. In this study, we use DBSCAN method to cluster the movement data and each cluster represents a stopover. Then, we split the remote sensing image into 16×16 patches and divide them into positive and negative samples on the basis of clustering result. In addition, a multi-convolutional neural network model is proposed for the training and prediction of the potential distribution of wild geese surrounding Qinghai Lake. We evaluate the proposed system using a real GPS dataset collected on 29 birds over three years. The experiments show that the proposed method outperforms the GLCM method in terms of overall accuracy, F1 score, and AUC. The proposed method also can obtain a better result in a potential distribution prediction experiment.
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基金项目:国家科技部国家科技基础条件平台项目(DKA2017-12-02-18);中国科学院计算机网络信息中心所级项目(ZXRW—201603,ZXRW—201603)
引用文本:
苏锦河,朴英超,罗泽,阎保平.基于卷积神经网络的候鸟潜在分布预测.计算机系统应用,2018,27(10):248-254
SU Jin-He,PIAO Ying-Chao,LUO Ze,YAN Bao-Ping.Mapping Potential Distribution of Wild Bird Using Convolutional Neural Network.COMPUTER SYSTEMS APPLICATIONS,2018,27(10):248-254

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