中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 成都山地灾害与环境研究所
  3. 中国科学院水利部成都山地灾害与环境研究所
  4. 山地灾害与地表过程重点实验室
Landslide Detection of Hyperspectral Remote Sensing Data Based on Deep Learning With Constrains

文献类型：期刊论文

作者Ye, Chengming2; Li, Yao1,9,10; Cui, Peng1,9,10; Liang, Li8; Pirasteh, Saeid7; Marcato, Jose, Jr.6; Goncalves, Wesley Nunes4,6; Li, Jonathan3,5
刊名IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
出版日期2019-12-01
卷号12期号:12页码:5047-5060
ISSN号1939-1404
关键词Terrain factors Feature extraction Hyperspectral imaging Deep learning Support vector machines Deep belief network (DBN) deep learning feature extraction hyperspectral data landslide
DOI10.1109/JSTARS.2019.2951725
通讯作者Li, Yao(yaolicd@hotmail.com)
英文摘要Detecting and monitoring landslides are hot topics in remote sensing community, particularly with the development of remote sensing technologies and the significant progress of computer vision. To the best of our knowledge, no study focused on deep learning-based methods for landslide detection on hyperspectral images. We proposes a deep learning framework with constraints to detect landslides on hyperspectral image. The framework consists of two steps. First, a deep belief network is employed to extract the spectral-spatial features of a landslide. Second, we insert the high-level features and constraints into a logistic regression classifier for verifying the landslide. Experimental results demonstrated that the framework can achieve higher overall accuracy when compared to traditional hyperspectral image classification methods. The precision of the landslide detection on the whole image, obtained by the proposed method, can reach 97.91%, whereas the precision of the linear support vector machine, spectral information divergence, and spectral angle match are 94.36%, 84.50%, and 86.44%, respectively. Also, this article reveals that the high-level feature extraction system has a significant potential for landslide detection, especially in multi-source remote sensing.
WOS关键词SPECTRAL-SPATIAL CLASSIFICATION ; IMAGE CLASSIFICATION ; WENCHUAN EARTHQUAKE ; SOIL-EROSION ; INVENTORY ; FOREST ; INTERFEROMETRY ; BIODIVERSITY ; REGRESSION ; FEATURES
资助项目Strategic Priority Research Program of the Chinese Academy of Sciences[XDA23090203] ; Key Research Program of Frontier Sciences, CAS[QYZDY-SSW-DQC006] ; Key Program of Sichuan science and technology department[2018SZ0350]
WOS研究方向Engineering ; Physical Geography ; Remote Sensing ; Imaging Science & Photographic Technology
语种英语
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
WOS记录号WOS:000515698700030
资助机构Strategic Priority Research Program of the Chinese Academy of Sciences ; Key Research Program of Frontier Sciences, CAS ; Key Program of Sichuan science and technology department
源URL[http://ir.imde.ac.cn/handle/131551/34057]  
专题成都山地灾害与环境研究所_山地灾害与地表过程重点实验室
通讯作者Li, Yao
作者单位1.Chinese Acad Sci, Key Lab Mt Hazards & Earth Surface Proc, Chengdu 610041, Peoples R China
2.Chengdu Univ Technol, Minist Educ, Key Lab Earth Explorat & Informat Technol, Chengdu 610059, Peoples R China
3.Univ Waterloo, Dept Geog & Environm Management, Waterloo, ON N2L 3G1, Canada
4.Univ Fed Mato Grosso do Sul, Fac Comp Sci, BR-79070900 Campo Grande, MS, Brazil
5.Univ Waterloo, Dept Syst Design Engn, Waterloo, ON N2L 3G1, Canada
6.Univ Fed Mato Grosso do Sul, Fac Engn Architecture & Urbanism & Geog, BR-79070900 Campo Grande, MS, Brazil
7.Southwest Jiaotong Univ, Fac Geosci & Environm Engn, Chengdu 611756, Peoples R China
8.Chengdu Univ Technol, Coll Management Sci, Chengdu 610059, Peoples R China
9.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
10.Chinese Acad Sci, Inst Mt Hazards & Environm, Chengdu 610041, Peoples R China
推荐引用方式
GB/T 7714		 Ye, Chengming,Li, Yao,Cui, Peng,et al. Landslide Detection of Hyperspectral Remote Sensing Data Based on Deep Learning With Constrains[J]. IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,2019,12(12):5047-5060.
APA Ye, Chengming.,Li, Yao.,Cui, Peng.,Liang, Li.,Pirasteh, Saeid.,...&Li, Jonathan.(2019).Landslide Detection of Hyperspectral Remote Sensing Data Based on Deep Learning With Constrains.IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING,12(12),5047-5060.
MLA Ye, Chengming,et al."Landslide Detection of Hyperspectral Remote Sensing Data Based on Deep Learning With Constrains".IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING 12.12(2019):5047-5060.

入库方式： OAI收割

来源：成都山地灾害与环境研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。