Exploiting Spectral and Spatial Information in Hyperspectral Urban Data With High Resolution

被引：193
|
作者：
Dell'Acqua, F. [1 ]
Gamba, P. [1 ]
Ferrari, A. [1 ]
Palmason, J. A. [2 ]
Benediktsson, J. A. [2 ]
Arnason, K. [2 ]
机构：
[1] Univ Pavia, Dept Elect, I-27100 Pavia, Italy
[2] Univ Iceland, IS-107 Reykjavik, Iceland
来源：
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS | 2004年 / 1卷 / 04期
关键词：
Hyperspectral imaging; morphology; multiclassification; urban remote sensing;
D O I：
10.1109/LGRS.2004.837009
中图分类号：
P3 [地球物理学]; P59 [地球化学];
学科分类号：
0708 ; 070902 ;
摘要：
Very high resolution hyperspectral data should be very useful to provide detailed maps of urban land cover. In order to provide such maps, both accurate and precise classification tools need, however, to be developed. In this letter, new methods for classification of hyperspectral remote sensing data are investigated, with the primary focus on multiple classifications and spatial analysis to improve mapping accuracy in urban areas. In particular, we compare spatial reclassification and mathematical morphology approaches. We show results for classification of DAIS data over the town of Pavia, in northern Italy. Classification maps of two test areas are given, and the overall and individual class accuracies are analyzed with respect to the parameters of the proposed classification procedures.
引用
收藏
页码：322 / 326
页数：5
相关论文
共 50 条
  • [31] Deep Spatial-Spectral Information Exploitation for Rapid Hyperspectral Image Super-Resolution
    Hu, Jing
    Li, Yunsong
    Zhao, Minghua
    Zhang, Yaling
    2019 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2019), 2019, : 3109 - 3112
  • [32] Spatial/spectral analysis of hyperspectral image data
    Plaza, A
    Martínez, P
    Plaza, J
    Pérez, R
    2003 IEEE WORKSHOP ON ADVANCES IN TECHNIQUES FOR ANALYSIS OF REMOTELY SENSED DATA, 2004, : 298 - 307
  • [33] A challenge for high spatial, spectral, and temporal resolution data fusion
    King, RL
    IGARSS 2000: IEEE 2000 INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOL I - VI, PROCEEDINGS, 2000, : 2602 - 2604
  • [34] Autonomous determination of endmembers in high spatial and spectral resolution data
    Winter, EM
    Simi, C
    Hill, A
    Lasota, C
    Winter, ME
    ALGORITHMS FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY VI, 2000, 4049 : 504 - 510
  • [35] THE ESTIMATION OF HIGH RESOLUTION URBAN SURFACE TEMPERATURE USING HYPERSPECTRAL SPECTRAL MIXTURE ANALYSIS
    Liu, Kai
    Su, Hongbo
    Wang, Weimin
    Li, Xueke
    2015 7TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS), 2015,
  • [36] Partially surpervised classification of optical high spatial resolution images in urban environment using spectral and textural information
    De Martino, M
    Macchiavello, G
    Serpico, SB
    IGARSS 2004: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM PROCEEDINGS, VOLS 1-7: SCIENCE FOR SOCIETY: EXPLORING AND MANAGING A CHANGING PLANET, 2004, : 77 - 80
  • [37] Miniaturization of High-Spectral-Spatial Resolution Hyperspectral Imagers on Unmanned Aerial Systems
    Hill, Samuel L.
    Clemens, Peter
    NEXT-GENERATION SPECTROSCOPIC TECHNOLOGIES VIII, 2015, 9482
  • [38] Key Information Retrieval in Hyperspectral Imagery through Spatial-Spectral Data Fusion
    Mianji, Fereidoun A.
    Zhang, Ye
    Babakhani, Asad
    RADIOENGINEERING, 2010, 19 (04) : 734 - 744
  • [39] Using Tri-training to Exploit Spectral and Spatial Information for Hyperspectral Data Classification
    Huang, Rui
    He, Wenyong
    PROCEEDINGS OF INTERNATIONAL CONFERENCE ON COMPUTER VISION IN REMOTE SENSING, 2012, : 30 - 33
  • [40] Spectral Unmixing-Based Clustering of High-Spatial Resolution Hyperspectral Imagery
    Mylona, Eleftheria A.
    Sykioti, Olga A.
    Koutroumbas, Konstantinos D.
    Rontogiannis, Athanasios A.
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2017, 10 (08) : 3711 - 3721
12345