Establishment of the watershed image classified rule-set and feasibility assessment of its application

Cheng Han Lin; Hsin Kai Chuang; Ming Lang Lin; Wen Chao Huang

Establishment of the watershed image classified rule-set and feasibility assessment of its application

Cheng Han Lin, Hsin Kai Chuang, Ming Lang Lin, Wen Chao Huang

Department of Civil Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Extreme weather events result in catastrophic disasters around the world recently. More commonly, these disasters occurred due to multiple reasons that coupled together. To develop disaster prevention strategies, application of satellite images can be effective because of its promptness and vast coverage area. This study established an image classified rule-set which used the object-based image analysis methodology. There are several surface features in the watershed image that were classified based on the proposed rule set, including main channels, secondary channels, sandbars, alluvial fans, landslides and place of the geotechnical damage. The study applied this rule-set in different watersheds and different-resolution satellite imagery, and assessed the feasibility by comparing in-situ data and calculating the error matrix. The results showed that the rule-set logic can be flexible in different watersheds and different images. The classification of the rule-set is reproducible and accurate. As this result we can apply the rule-set to disaster management and land use planning in the future work.

Original language	English
Title of host publication	Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013
Editors	Hamid R. Arabnia, Leonidas Deligiannidis, Joan Lu, Fernando G. Tinetti, Jane You, George Jandieri, Gerald Schaefer, Ashu M. G. Solo, Vladimir Volkov
Publisher	CSREA Press
Pages	462-468
Number of pages	7
ISBN (Electronic)	1601322526, 9781601322524
State	Published - 2013
Event	2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013, at WORLDCOMP 2013 - Las Vegas, United States Duration: 22 Jul 2013 → 25 Jul 2013

Publication series

Name	Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013
Volume	1

Conference

Conference	2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013, at WORLDCOMP 2013
Country/Territory	United States
City	Las Vegas
Period	22/07/13 → 25/07/13

Keywords

Geotechnical damage
Object-based image analysis
Rule-set
Watershed satellite image

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

Lin, C. H., Chuang, H. K., Lin, M. L., & Huang, W. C. (2013). Establishment of the watershed image classified rule-set and feasibility assessment of its application. In H. R. Arabnia, L. Deligiannidis, J. Lu, F. G. Tinetti, J. You, G. Jandieri, G. Schaefer, A. M. G. Solo, & V. Volkov (Eds.), Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013 (pp. 462-468). (Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013; Vol. 1). CSREA Press.

Lin, Cheng Han ; Chuang, Hsin Kai ; Lin, Ming Lang et al. / Establishment of the watershed image classified rule-set and feasibility assessment of its application. Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013. editor / Hamid R. Arabnia ; Leonidas Deligiannidis ; Joan Lu ; Fernando G. Tinetti ; Jane You ; George Jandieri ; Gerald Schaefer ; Ashu M. G. Solo ; Vladimir Volkov. CSREA Press, 2013. pp. 462-468 (Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013).

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abstract = "Extreme weather events result in catastrophic disasters around the world recently. More commonly, these disasters occurred due to multiple reasons that coupled together. To develop disaster prevention strategies, application of satellite images can be effective because of its promptness and vast coverage area. This study established an image classified rule-set which used the object-based image analysis methodology. There are several surface features in the watershed image that were classified based on the proposed rule set, including main channels, secondary channels, sandbars, alluvial fans, landslides and place of the geotechnical damage. The study applied this rule-set in different watersheds and different-resolution satellite imagery, and assessed the feasibility by comparing in-situ data and calculating the error matrix. The results showed that the rule-set logic can be flexible in different watersheds and different images. The classification of the rule-set is reproducible and accurate. As this result we can apply the rule-set to disaster management and land use planning in the future work.",

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author = "Lin, {Cheng Han} and Chuang, {Hsin Kai} and Lin, {Ming Lang} and Huang, {Wen Chao}",

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Lin, CH, Chuang, HK, Lin, ML & Huang, WC 2013, Establishment of the watershed image classified rule-set and feasibility assessment of its application. in HR Arabnia, L Deligiannidis, J Lu, FG Tinetti, J You, G Jandieri, G Schaefer, AMG Solo & V Volkov (eds), Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013. Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013, vol. 1, CSREA Press, pp. 462-468, 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013, at WORLDCOMP 2013, Las Vegas, United States, 22/07/13.

Establishment of the watershed image classified rule-set and feasibility assessment of its application. / Lin, Cheng Han; Chuang, Hsin Kai; Lin, Ming Lang et al.
Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013. ed. / Hamid R. Arabnia; Leonidas Deligiannidis; Joan Lu; Fernando G. Tinetti; Jane You; George Jandieri; Gerald Schaefer; Ashu M. G. Solo; Vladimir Volkov. CSREA Press, 2013. p. 462-468 (Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013; Vol. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Lin, Cheng Han

AU - Chuang, Hsin Kai

AU - Lin, Ming Lang

AU - Huang, Wen Chao

PY - 2013

Y1 - 2013

N2 - Extreme weather events result in catastrophic disasters around the world recently. More commonly, these disasters occurred due to multiple reasons that coupled together. To develop disaster prevention strategies, application of satellite images can be effective because of its promptness and vast coverage area. This study established an image classified rule-set which used the object-based image analysis methodology. There are several surface features in the watershed image that were classified based on the proposed rule set, including main channels, secondary channels, sandbars, alluvial fans, landslides and place of the geotechnical damage. The study applied this rule-set in different watersheds and different-resolution satellite imagery, and assessed the feasibility by comparing in-situ data and calculating the error matrix. The results showed that the rule-set logic can be flexible in different watersheds and different images. The classification of the rule-set is reproducible and accurate. As this result we can apply the rule-set to disaster management and land use planning in the future work.

AB - Extreme weather events result in catastrophic disasters around the world recently. More commonly, these disasters occurred due to multiple reasons that coupled together. To develop disaster prevention strategies, application of satellite images can be effective because of its promptness and vast coverage area. This study established an image classified rule-set which used the object-based image analysis methodology. There are several surface features in the watershed image that were classified based on the proposed rule set, including main channels, secondary channels, sandbars, alluvial fans, landslides and place of the geotechnical damage. The study applied this rule-set in different watersheds and different-resolution satellite imagery, and assessed the feasibility by comparing in-situ data and calculating the error matrix. The results showed that the rule-set logic can be flexible in different watersheds and different images. The classification of the rule-set is reproducible and accurate. As this result we can apply the rule-set to disaster management and land use planning in the future work.

KW - Geotechnical damage

KW - Object-based image analysis

KW - Rule-set

KW - Watershed satellite image

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M3 - 會議論文篇章

AN - SCOPUS:85072955720

T3 - Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013

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EP - 468

BT - Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013

A2 - Arabnia, Hamid R.

A2 - Deligiannidis, Leonidas

A2 - Lu, Joan

A2 - Tinetti, Fernando G.

A2 - You, Jane

A2 - Jandieri, George

A2 - Schaefer, Gerald

A2 - Solo, Ashu M. G.

A2 - Volkov, Vladimir

PB - CSREA Press

T2 - 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013, at WORLDCOMP 2013

Y2 - 22 July 2013 through 25 July 2013

ER -

Lin CH, Chuang HK, Lin ML, Huang WC. Establishment of the watershed image classified rule-set and feasibility assessment of its application. In Arabnia HR, Deligiannidis L, Lu J, Tinetti FG, You J, Jandieri G, Schaefer G, Solo AMG, Volkov V, editors, Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013. CSREA Press. 2013. p. 462-468. (Proceedings of the 2013 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2013).

Establishment of the watershed image classified rule-set and feasibility assessment of its application

Abstract

Publication series

Conference

Keywords

UN SDGs

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