Automatic Classification Method for Multitemporal Data using Reference Map

A new automatic classification method with high and stable accuracy for multitemporal data is presented in this paper. This method is based on prior condition that a classified map of the target area already exists, or at least one of the multitemporal data had been classified. The classified map is...

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Published inJournal of the Japan society of photogrammetry and remote sensing Vol. 31; no. 3; pp. 25 - 33
Main Authors HONG, Sunpyo, FUKUE, Kiyonari, HASHINO, Tsukasa, SHIMODA, Haruhisa, SAKATA, Toshibumi
Format Journal Article
LanguageEnglish
Published Japan Society of Photogrammetry and Remote Sensing 1992
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Abstract A new automatic classification method with high and stable accuracy for multitemporal data is presented in this paper. This method is based on prior condition that a classified map of the target area already exists, or at least one of the multitemporal data had been classified. The classified map is used as a reference map to specify training areas of classification categories. The new automatic classification method consists of five steps, i. e., extraction of training data using the reference map, detection of changed pixels based upon the homogeneity of training data, clustering of changed pixels, reconstruction of training data, and maximum likelihood classification. In order to evaluate the performance of this method, each temporal Landsat TM data were classified by using this method and a conventional method. As a result, we could get classified maps with high reliability and fast throughput, without a skilled operator.
AbstractList A new automatic classification method with high and stable accuracy for multitemporal data is presented in this paper. This method is based on prior condition that a classified map of the target area already exists, or at least one of the multitemporal data had been classified. The classified map is used as a reference map to specify training areas of classification categories. The new automatic classification method consists of five steps, i. e., extraction of training data using the reference map, detection of changed pixels based upon the homogeneity of training data, clustering of changed pixels, reconstruction of training data, and maximum likelihood classification. In order to evaluate the performance of this method, each temporal Landsat TM data were classified by using this method and a conventional method. As a result, we could get classified maps with high reliability and fast throughput, without a skilled operator.
Author HONG, Sunpyo
HASHINO, Tsukasa
SHIMODA, Haruhisa
FUKUE, Kiyonari
SAKATA, Toshibumi
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  fullname: SHIMODA, Haruhisa
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  fullname: SAKATA, Toshibumi
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References 10) A. Singh, 1989: Digital change detection techniques using remotely-sensed data, Inter. J. Remote Sensing, Vol. 10, No. 6, 989-1003.
25) アンナートN, 洪善杓, 下田陽久, 坂田俊文, 1991: 高解像度衛星データに対するUNSPERVISED LEARNINGの最適化 (II) , 日本写真測量学会学術講演会発表論文集A-6.
15) R. A. Weismiller, et. al., 1977: Change detection in coastal zone environment, Photogrammetric Engineering and Remote Sensing, Vol. 43, 1533-1539.
21) K. Fukue, Y. Matumae, et. al., 1987: Evaluations of unsupervised methods for land-cover/use classifications of Landsat TM data, Inter. Archives of Photogrammetry and Remote Sensing. Vol. 27, Part B, 180-194
1) W. J. Todd, 1977: Urban and regional land use change detected by using Landsat data, J. of Research by the US Geological Survey, Vo. 5, 527-534.
7) J. R. Anderson, 1977: Land use and land cover changes-A framework for monitoring, J. of Research by the Geological Survey, Vol. 5, 143-153.
9) S. Hong, et. al., 1990: A high accuracy landcover classification method of multi-temporal images using Dempster-Shafer model, Proc. 11th Asian Conference on Remote Sensing, p. 8. 1-p. 8. 8.
5) A. J. Richardson, A. K. Milne, 1983: Mapping fire burns and vegetation regeneration using principal components analysis, Proc. of IGARSS'83.
11) J. R. Jenson, D. L. Toll, 1982: Detecting residential land use development at the urban fringe, Photogrammetric Engineering and Remote Sensing, Vo. 48, 629-643.
19) 高木幹雄, 下田陽久監修, 1991: 画像解析ハンドブック, 東京大学出版会, 645-668.
14) J. R. Jenson (editor) , 1983: Urban/suburban land use analysis, Manual of Remote Sensing. Vol. 2, second edition (American Society of Photogrammerty) , 1571-1666.
12) R. F. Nelson, 1983: Detcting forest canopy change due to insect activity using Landsat MSS, Photogrammetric Engineering and Remote Sensing, Vol. 49, 1303-1314.
24) 昭和60-62年度科学研究費補助金特定研究 (1) 研究成果報告書, 1988: 陸地における衛星データの利用技術に関する研究, 12-25.
18) P. H. Swain, S. M. Davis (editor) , 1978: Remote Sensing-The Quantitative Approach, McGRAW-HILL, 302-306.
2) S. Gordon, 1980: Utilizing Landsat imagery to monitor land use change-A case study of Ohio, Remote Sensing of Environment, Vo. 9, 189-196.
6) J. R. Shepard, 1964: A concept of change detection, Photogrammetric Engineering. Vol. 30, 648-651.
8) 橋野司, 福江潔也, 下田陽久, 坂田俊文, 1990: 多時期画像を用いた土地被覆分類の高精度化, 日本写真測量学会平成2年度学術講演会発表論文集F-2.
20) H. Shimoda, et. al., 1987: Effects of spatial resolutions to landcover classification accuracies for SPOT HRV and Landsat TM data, Inter. Archives of Photogrammetry and Remote Sensing. Vol. 27, Part B, 544-553.
23) 洪善杓, 福江潔也, 下田陽久, 坂田俊文, 1991: クラスとカテゴリーの対応関係に関する検討, 日本写真測量学会秋季学術講演会論文集B-3.
16) G. F. Byrne, et. al., 1980: Monitoring land cover change by pricipal component analysis of multitemporal Landsat data, Remote Sensing of Environment, Vol. 10, 175-184.
4) C. J. Tucker, 1979: Red and photographic infrared liner combinations for monitoring vegetation, Remote Sensing of Environment, vol. 8, 127-150.
22) 竹内, 1991: 画像情報の曖昧さを考慮した土地被覆変化の抽出, 写真測量とリモートセンシング, Vol. 30, No. 4, 65-70.
17) 瀬戸, 古村, 1990: 異種データ間比較による変化解析方式の一提案, 日本リモートセンシング学会誌, Vol. 10, No. 1, 5-17.
3) J. P. Howarth, E. Boasson, 1983: Landsat digital enhancements for change detection in urban environment, Remote Sensing of Environment, Vo.13, 149-160.
13) J. E. Colwell, F. P. Weber, 1981: Forest change detection, Proceedings of the 15th Inter. Symp. on Remote Sensing of environment (Ann Arbor) .
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