Very High Resolution Multiangle Urban Classification Analysis

被引:188
作者
Longbotham, Nathan [1 ]
Chaapel, Chuck [2 ]
Bleiler, Laurence [2 ]
Padwick, Chris [2 ]
Emery, William J. [1 ]
Pacifici, Fabio [2 ]
机构
[1] Univ Colorado, Dept Aerosp Engn Sci, Boulder, CO 80309 USA
[2] Digital Globe Inc, Longmont, CO 80503 USA
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2012年 / 50卷 / 04期
关键词
Digital height map; image sequence analysis; morphology; multiangle reflectance; spectral analysis; texture; urban classification; very high spatial resolution; CHRIS-PROBA IMAGES; MISR; MAP;
D O I
10.1109/TGRS.2011.2165548
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
070403 [天体物理学]; 070902 [地球化学];
摘要
The high-performance camera control systems carried aboard the DigitalGlobe WorldView satellites, WorldView-1 and WorldView-2, are capable of rapid retargeting and high off-nadir imagery collection. This provides the capability to collect dozens of multiangle very high spatial resolution images over a large target area during a single overflight. In addition, WorldView-2 collects eight bands of multispectral data. This paper discusses the improvements in urban classification accuracy available through utilization of the spatial and spectral information from a WorldView-2 multiangle image sequence collected over Atlanta, GA, in December 2009. Specifically, the implications of adding height data and multiangle multispectral reflectance, both derived from the multiangle sequence, to the textural, morphological, and spectral information of a single WorldView-2 image are investigated. The results show an improvement in classification accuracy of 27% and 14% for the spatial and spectral experiments, respectively. Additionally, the multiangle data set allows the differentiation of classes not typically well identified by a single image, such as skyscrapers and bridges as well as flat and pitched roofs.
引用
收藏
页码:1155 / 1170
页数:16
相关论文
共 53 条
[1]
Classification of ASAS multiangle and multispectral measurements using artificial neural networks [J].
Abuelgasim, AA ;
Gopal, S ;
Irons, JR ;
Strahler, AH .
REMOTE SENSING OF ENVIRONMENT, 1996, 57 (02) :79-87
[2]
[Anonymous], WORLDVIEW 1 SPAC DAT
[3]
[Anonymous], WORLDVIEW 2 SPAC DAT
[4]
Object-based land cover classification using airborne LiDAR [J].
Antonarakis, A. S. ;
Richards, K. S. ;
Brasington, J. .
REMOTE SENSING OF ENVIRONMENT, 2008, 112 (06) :2988-2998
[5]
[6]
The PROBA/CHRIS mission: A low-cost smallsat for hyperspectral multiangle observations of the earth surface and atmosphere [J].
Barnsley, MJ ;
Settle, JJ ;
Cutter, MA ;
Lobb, DR ;
Teston, F .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2004, 42 (07) :1512-1520
[7]
Bellman R., 1961, Adaptive Control Processes: A Guided Tour, DOI DOI 10.1515/9781400874668
[8]
MODTRAN4 radiative transfer modeling for atmospheric correction [J].
Berk, A ;
Anderson, GP ;
Bernstein, LS ;
Acharya, PK ;
Dothe, H ;
Matthew, MW ;
Adler-Golden, SM ;
Chetwynd, JH ;
Richtsmeier, SC ;
Pukall, B ;
Allred, CL ;
Jeong, LS ;
Hoke, ML .
OPTICAL SPECTROSCOPIC TECHNIQUES AND INSTRUMENTATION FOR ATMOSPHERIC AND SPACE RESEARCH III, 1999, 3756 :348-353
[9]
Bishop CM., 1995, NEURAL NETWORKS PATT
[10]
Random forests [J].
Breiman, L .
MACHINE LEARNING, 2001, 45 (01) :5-32